Operations management ii

transcript

Operations Management - II

Manimay Ghosh, Ph.D.

Road Map

Inventory Control Material Requirement Planning Aggregate Planning Scheduling Quality Management and SPC Lean Manufacturing

Inventory

Inventory: Stock of items held by the organization

Goals in Operations w.r.t Inventory Carrying the right amount of inventory and

ensuring that neither overstocking nor shortages occur is the ultimate goal of inventory management

Keep the level of inventory in the supply chain as low as possible

Moving the inventory, in its continually changing form, as fast as possible through the supply chain for delivery to the final client

What is Inventory Management? Inventory management encompasses

processes that ensures product availability while reducing investment costs

Why do we need Inventory Management? Largest (physical and financial sense) and

most difficult asset to manage for an organization

Two Views of Inventory

Pressure for high inventory Pressure for low inventory

Pressure for High Inventory

To achieve economies of scale in production (cycle inventory) Immediate delivery not possible

Crude oil, iron ore, coal can’t always be supplied on time

To protect against unanticipated events (strikes, weather) To protect against price increases and take advantage of quantity

discount To satisfy periods of high seasonal demand Economies of scale offered by transportation companies

One truck load or one ship load can reduce unit transportation cost

Decoupling Inventory

Pressure for Low Inventory

Holding costs Cost of coordinating production Quality issue Increased waste

Forms of Manufacturing Inventories Manufacturing Inventory: Items that contribute to or

become part of a firm’s product.

Raw material Physical inputs at the start of the production process.

Work-in-process Inventory between the start and end points of a product routine (yet

to become finished products)

Types of Manufacturing Inventory(Work-in-process)

Manufacturing Inventory

Finished goods End item ready to be sold at

the end of routine Maintenance / Repair /

Operating Supplies (MRO) Oil, lubricants, cotton waste,

wood dust Pens, papers, files, envelopes

Pipeline or Transit Stock Inventory ordered but not yet

received

Manufacturing Inventory Types

Service Inventory

Inventory: Tangible goods to be sold and the supplies necessary to administer the services in various types of service organizations (hospitals, banks)Hospitals: (medicines, syringes, blood,

sutures, glucose bottles, bandages etc.)Banks: brochures, pamphlets, currency notes,

Levels of Inventory

High LevelsTying more financial capital

High interest charges

Low LevelsStock outs Lost sales

Goal of Materials Manager

Optimal Level of Inventory

Key QuestionsWhat should be the size of order to the

supplier?

When should the order be placed?

Measures of Inventory Management Inventory turnover

Costs of goods sold --------------------------------------------------------

Average aggregate inventory value

Cost of goods sold is finished goods valued at cost, not the final sale price

Average aggregate inventory value is the total value at cost of all items (RM, WIP, Finished goods) being held in inventory

Measures of Inventory Management Days (or weeks) of inventory in hand

average aggregate value of inventory = --------------------------------------------------

(cost of goods sold) / 365 days

Selective Control of Inventory

FSN Classification Based on movement of inventory

F: fast moving, S: slow moving, N: non-moving

VED Classification Based on criticality of items

V: Vital, E: essential, D: desirable

ABC Classification Based on cost of items consumed

ABC Classification System

ABC classification method divides inventory items into three groups A items (high rupee volume)

B items (moderate rupee volume)

C items (low rupee volume)

Note: Rupee volume is a measure of importance; an item low in cost but high in volume can be more important than a high-cost item with low volume.

ABC Classification System

In ABC analysis each class of inventory requires different levels of inventory monitoring and control – the higher the value of the inventory, the tighter the control

ABC Inventory Planning

A items 10 to 20% of # of items 60 to 70% of annual rupee value of inventory Tight inventory control

B items Represent 30% of # items and 15% of inventory value

C items 50 to 60% of # of items 10 to 15% of annual rupee value of inventory Less stringent inventory control

ABC Analysis

ABC Inventory PlanningItem No Annual Rupee Usage % of Total Value

22 95000 40.69

68 75000 32.13

27 25000 10.71

3 15000 6.43

82 13000 5.57

54 7500 3.21

36 1500 0.64

19 800 0.34

23 425 0.18

41 225 0.1

233,450 100%

ABC Inventory Planning

Classification Item No. Annual Rupee Usage % of Total

A 22, 68 Rs 170,000 72.90%

B 27, 03, 82 53,000 22.7

C 54, 36, 19, 23, 41 10,450 4.4

A Typical ABC Breakdown

Key Use of ABC Concepts

Use in customer serviceFocus on essential aspects

Guide to cycle countingPhysical counting of items in inventory

To avoid discrepancy indicated by inventory records and actual quantities

ABC Analysis

Annual Rupee Value Review Period Rs >10,000 ≤30 days Rs 3,000 – 10,000 ≤45 days Rs 250 – 3,000 ≤90 days <= Rs 250 ≤180 days

Experts recommend following accuracy:A items: ±0.2%, B: ± 1%, C: ± 5%

Independent vs. Dependent DemandIndependent demand

Influenced by market conditions, i.e., originates outside the system (say cars, bicycles, refrigerators, washing machines)

Uncertain

Dependent demand Depends on demand of independent items, i.e., make up

independent demand products Known Example: Subassemblies, components parts

Independent Demand

B(4) C(2)

D(2) E(1) D(3) F(2)

Dependent Demand

Independent demand is uncertain. Dependent demand is certain.

Inventory

Managing Independent Demand

This chapter focuses on managing independent demand

Inventory Costs

Types of costs Ordering costs (costs associated with placing an order and receiving

inventory, independent of order size). Assigned to entire batch Identification of sources of supply Price negotiation, purchase order generation Follow-up and receipt of materials Inspecting goods upon arrival for quality and quantity Stationery, postage, telephone and electricity bills Transportation costs

Set-up Costs When a firm produces its own inventory, the cost of machine set-up

such as arranging tools, drawings, cleaning the machine, adjusting the machine are all parts of set-up costs

Inventory Costs

Holding or Carrying costs (in warehouse) Cost of storage facilities (rent, if rented) Electricity Cost of capital tied up in inventory Material handling Interest charges Insurance and taxes Pilferage, scrap, & obsolescence Cost of personnel Software for maintaining inventory status

Inventory Costs

Shortage Costs (or stock out costs)Loss of profits Loss of goodwillLate charges

Basic Inventory Control Systems Two types

Fixed order quantity model (Q – Model)

Also known as Perpetual system or Continuous inventory System

Event or quantity triggered

Fixed time period model (P-model)

Also known as Periodic Review System

Time Triggered

Economic Order Quantity (EOQ) Model Assumptions

Annual demand for item is constant and uniform throughout Lead time is constant Price per unit of product constant Inventory holding cost is based on avg. inventory Ordering or set-up costs are constant Instantaneous replenishment There are no quantity discounts Inventory incurred no cost in transit

Q-Model

Lead Time: Time between placing an order and its receipt

Reorder Point: The inventory level at which a new order should be placed.

Q-Model

QInventory on hand

Demand Rate

Avg. Inventory (Q/2)

Reorder Pt.

Order PlacedOrder Receipt

L = Lead TimeR = Reorder Point

Average Inventory Levels and Number of Orders

Total Cost Curve

Minimum Total Cost

The total cost curve reaches its minimum where the carrying and ordering costs are equal.

Q Model

Q opt=

Reorder Point, R = d×L

Where, d = average daily demandL = Lead time in days

(constant demand, so no safety stock)

The square root formula is the EOQ, also referred as economic lot size

Q answers the “how much” question directly

Reorder Point in EOQ

When to Reorder with EOQ

If demand and lead time are both constant, the reorder point is

ROP = d X LT

where d = Demand rate (units per

day or week)

LT = Lead time in days or

Q-Model

Optimal number of orders = D / Q

Time between orders = Q / D

Fixed Order Quantity Model(Q-model)Total Annual Cost = Annual Purchase Cost + Annual Ordering Cost + Annual Holding Cost

TC = PD + (D/Q)×S + (Q/2)×H

Where, TC = Total annual costD = DemandP = Unit costQ = Quantity to be orderedS = Ordering cost or set-up costR = reorder pointL = Lead TimeH = Annual holding or storing cost per unit of average

inventory

Q Model

Item cost (P×D) is not a function of the order quantity – there are no quantity discounts– so the amount PD is constant. Therefore, the value of Q that minimizes the equation is the value that minimizes the sum of the ordering costs and holding costs, called the total inventory cost or total stock cost. This quantity is called Economic Order Quantity (EOQ).

EOQ with Purchasing Cost

Adding purchasing cost does not change EOQ

Total Cost Curve Near EOQ

The Total Cost Curve is flat near EOQ

Little’s Law

Average Inventory Average Flow time = ----------------------------------------

Flow Rate (or Average demand)

The average amount of inventory in a system is equal to the product of average demand and the average time a unit is in the system

Observation

If demand increases by a factor k, the optimal lot size increases by factor √k. The number of orders placed per year should also increase by a factor √k. Flow time attributed to cycle inventory should decrease by a factor of √k.

Production Order Quantity Model or EPQ Model It is a variant of EOQ model Assumptions

Annual demand knownUsage rate constantUsage occurs continually, but production

occurs periodicallyProduction rate constantNo quantity discounts

Production Quantity Model

Production Order Quantity Model

Stock out Occurrence

Excessive Consumption During Lead Time

Undue Stretching of Lead Time by Supplier

When to Reorder with EOQ

When variability is present in demand or lead time, it creates the possibility that actual demand will exceed expected demand

Therefore, it is necessary to carry safety stock to avoid stock out

Safety Stock

EOQ model assumed deterministic demand Demand in reality varies from day-to-day

Probability of stock out during lead time Need to keep safety stock in addition to expected

demand To hedge against the possibility of stock out

Amount of safety stock depends on Service Level

Probability that inventory on hand during lead time in sufficient to meet expected demand, i.e., the probability that stock out will not occur.

Safety Stock Avoids Stock Out Caused by Excessive Consumption

Safety Stock Avoids Stock Out by Undue Stretching of LT by Suppliers

Fixed Order Qty Model With Safety Stock

Service Level

Probability that the demand will not exceed supply during lead time

Example: Service level of 95% implies a probability of 95% that demand will not exceed supply during lead time, and probability of stock out is 5%

Service Level = 100% - Stock out risk

Lead Time Demand

Normal Distribution Curve During Lead Time

Probabilistic Models - When to Order?

Reorder Point

Safety Stock (SS)

Lead Time

Service Level P(Stockout)

Place order

Receive order

Safety Stock

Reorder Point (ROP)

If expected demand during lead time and its standard deviation are available, then

ROP = d×L + safety stock ROP = Expected demand during lead time + ZσdLT

Where, z = # standard deviations

σdLT = The standard deviation of demand during

lead time

ZσdLT = Safety StockNote: Smaller the risk manager is willing to accept, the greater the value of Z

Other Three Probabilistic Models1. Demand is variable, and LT constant

2. Lead time is variable, demand constant

3. Both lead time and demand are variable

Demand and LT Variable

Demand Variable and LT Constant

LT Variable and Demand Constant

Managing Inventory (Key Learning) Inventory costs money, inventory hides problems Reduce inventory

Reducing lot sizes (EOQ) Lowering order costs through E-bidding Reducing receiving costs Automated payment of invoices Examine holding cost. If understated, larger H will

reduce EOQ Reducing set-up costs

Automation and process improvements

Managing Inventory (Key Learning)

Reduce safety stock Better forecasting models to reduce the unpredictability of

demand Collaborating Planning Forecasting and Replenishment

(CPFR) Reduce variability in demand by working with customers Reduce lead time

Bringing suppliers close to the buyer, reduce throughput time of suppliers

Reliable method of transportation Faster method of transportation

Impact of Location on Inventory(Key Learning) Questions related to inventory

How much to order?When to order?Where to stock inventories?

Square Root Rule

Inventory Related to Number of Locations

Managing Inventory (Key Learning) Reduce number of locations

Major effort by many firms to reduce the number of warehouses and distribution centres

Substantial reduction in inventories due to consolidation

Bar Code – 3 Litre Diet Coke

Manufacturer identificationnumber

Specific Item Number

Check digit

Quantity Discount Model

Price reductions for large orders offered to customers to induce them to buy in large quantities

TC = (Q/2)H + (D/Q)S + PD Carrying Cost Ordering Cost Purchasing Cost

Advantages to Disadvantages of Buyer on Discounts Advantages

Reduces units cost of materials # of orders few, low ordering costs Low transportation costs Chances of stock out less

Disadvantages High carrying costs High fund requirement Low stock turnover Deterioration of stocks

Advantages to Disadvantages of Seller on Discounts Advantages

Clear glut in the inventoryLess carrying costs of inventories

Discount - Incremental

In incremental discount increasing rates of discounts are offered for higher range of quantities purchased. Hence, under this discount offer there shall be multiple unit costs for the same item in a lot. The ranges of quantity at which price changes are called price breakers

Price Discount Model

Two general casesCarrying cost is constant (Rs 5 per unit per

Carrying cost is a % of purchase price (say 20% of unit price)

Total Cost Curve with Constant Carrying Cost

When carrying costs are constant, all curves have same minimum points at the same quantity

Quantity DiscountsWith Constant CarryingCosts

Total Cost with Carrying Cost as % of Unit Price

When carrying costs are % of unit price, minimum points don’t line up

Procedure for Determining Overall EOQ when Carrying Costs are Constant

Compute the common minimum point

If the feasible minimum point is on the lowest price range, that is the optimal quantity

If the minimum point is in any other range, compute the total cost for the minimum point and for the price breaks of all lower unit costs. Compare the total costs; the quantity (minimum point or price break) that yields the lowest total cost is the optimal order quantity

Problems

Carrying costs are constant

Determining Best Purchase Quantity when Carrying Costs are % of Price

Begin with lowest unit price, compute the minimum points for each price range until you find a feasible minimum point (i.e. until a minimum point falls in the quantity range for its price)

If the minimum point for the lowest unit price is feasible, it is the optimal order quantity. If the minimum point is not feasible in the lowest price range, compare the total cost at the price breaks for all lower prices with the total cost of the feasible minimum point. The quantity which yields the lowest total cost is the optimum

Problems

Carrying Costs are % of price

Total Annual Costs With Quantity Discounts

Fixed Time Period Model(P-Model) or Periodic Review System

Inventory checked only at fixed intervals of time, rather than on a continuous basis

Time between orders is constant On-hand inventory is counted Only the amount necessary to bring the total

inventory up to a pre-specified target is ordered (order size varies depending on on-hand inventory)

P-Model

OI – OrderInterval

P-Model

Fixed Time Period Model(P-Model) or Periodic Review System

Order Qty = Avg. demand + Safety Stock - Inventory on hand

P Model

Advantages Practical approach if the inventory withdrawals can’t be closely

monitored Inventory counted only before the next review period Convenient administratively More appropriate for C-items

Disadvantages No tally of inventory during review period Possibility of stock out Large amount of safety stock because need to protect against

shortages during order interval and lead time

Differences (Q vs. P Models)

Q model Order Qty: Q fixed When order: ROP triggered Record keep: Each time

material withdrawn Size of Inv: Less than P

model Time to maintain: High If Higher than normal

demand – Shorter time between orders

Type of items: High priced, critical, important items

A items

P model Order Qty: variable (varies

each time order is placed due to demand variability)

When order: Review period (time triggered)

Record keep: Counted only at review period

Administration: Easy Size of Inv.: Larger than Q

model Type of items: Retail, drugs

Appropriate when large number of items ordered from same supplier resulting in consolidation and lower freight rates

Choosing Between Q and P

Not an easy decisionPart science and part human judgment It depends on variety of factors

Total SKUs monitored Computerized or manual system ABC profile Strategic focus

Cost minimization or customer service

Choosing Between Q and P

P system The P system should be used when orders may be placed at specified

intervals Weekly order and delivery of FMCG products to a grocery store The P system is ideal when items are ordered from same supplier, and

delivered in same shipment Shipments can be consolidated resulting in lower freight rates

Ordering for multiple products at the same time Provides scheduled replenishment and less record keeping Often used for inexpensive items

Q system Often used for expensive items

Inventory Records and Accuracy Inventory records differ from physical count Inventory accuracy refers to how closely they match How to keep up-to-date inventory records

Keep store room locked Educating employees Putting fence up to ceiling around storage area to

prevent unauthorised access to pull items clandestinely

Cycle counting at regular intervals

Zhou Bicycle Company

Fixed Time Period Model

Material Requirements Planning (MRP)

The logic for determining the number of parts, components, and materials needed to produce a product.

It also provides a schedule specifying when each of these materials, parts, and components should be ordered and produced

Independent vs. Dependent Demand Independent demand

Influenced by market conditions, i.e., originates outside the system (say cars, bicycles, refrigerators, washing machines)

Uncertain

Dependent demand Depends on demand of independent items, i.e., make up

independent demand products Known Example: Subassemblies, components parts

Independent vs. Dependent Demand

Demand Pattern for Independent versus Dependent Items

Attribute Dependent Demand

Independent Demand

Nature of Demand No uncertainty Uncertainty

Goal Meet requirements exactly

Meet demand for a targeted service level

Service Level 100% 100% difficult

Demand occurrence

Often lumpy Often continuous

Estimation of demand

By production planning

By forecasting

How much to order?

Known with certainty

Estimate based on past consumption

Key Differences: Dependent vs. Independent Demand

Material Requirements Planning (MRP)

MRP is a technique that has been employed since the 1940s and 1950s.

Joe Orlicky is known as the Father of MRP The use and application of MRP grew through the

1970s and 1980s as the power of computer hardware and software increased.

MRP gradually evolved into a broader system called manufacturing resource planning (MRP II).

Material Requirements Planning (MRP) MRP is a computerized inventory system

developed specifically to manage dependent demand items

MRP works backward from the due date using lead times to determine when and how much to order for Subassemblies, component parts & raw

materials

MRP MRP begins with a schedule for finished goods

that is converted into a schedule of requirements for subassemblies, component parts and raw materials needed to produce the finished items in the specified time frame

MRP designed to answer the following questions

• What is needed ?

• How much is needed?

• When is it needed ?

MRP thus works with finished products, or end items, and their constituent parts, called lower level items

According to one study, 80% of high performing manufacturing plants have implemented MRP

MRP works well for assembling complex discrete products produced in batches Example: computers, consumer durables, furniture,

watches, trucks, generators, motors, machine tools

Inputs and Outputs of MRP

MRPMPS

BOM MRP Inventory Records

Planned OrderRelease

Work Order Purchase order ReschedulingNotices

Master Production Schedule

A time table that specifies what (end item) is to be made and when

Time period used for planning is called a time bucket

MPS shows how many of each individual item must be completed each period

Aggregate Production Plan and MPS -- Amplifiers

How does MPS differ from AP-Motors

Aggregate Production Plan - Cars

Hundai Motors:Month # of Cars

Jan 10,000Feb 12,000Mar 8,000April 11,000May 7,000

Weeks of January

I II III IV Total

Santro 1,200 2,000 2,500 700 6,400

Accent 700 950 1,300 250 3,200

Sonata 100 50 200 50 400

2,000 3,000 4,000 1,000 10,000

MASTER PRODUCTION SCHEDULE

1. Master Production Schedule (MPS) Master production schedule states

which end items are to be produced, when these are needed, and in what quantities.• Example: A master schedule for end item

Comes from: customer orders, forecasts and orders from warehouses to build up seasonal inventories, and interplant transfers

MPS and Planning Horizon

2. Bill of Materials (BOM)

A document that lists the components, their description, sequence in which the product is created and the quantity of each required to make one unit of a product Thus relationship between end items and lower level

items is described by the BOM It depicts exactly how a firm makes the item in the

master schedule Extremely important to have BOM correct to have

accurate material estimates

2. Bill of Materials (BOM)

The BOM file is often called the product structure file or product tree because it shows how a product is put together

Assembly Diagram & Product Structure Tree

Product Structure Tree of Sub-Assembly

Product Structure Tree of Product X With Levels

Visual description of the requirements in a bill of materials, where all components are listed by levels

(Highest)

(Lowest)

Indented Parts List for Meter A and Meter B

A Product Structure Tree

Note: Restructuring the BOM so that multiple occurrences of a component all coincide with the lowest level at which the component occurs

BOM & Product Structure Tree (An Example)

Partial Bill of Materials for a Bicycle

3. Inventory Record

Third input in MRP It tells us about the status of inventory of an item

at present, or in a given interval of time in the coming future On hand On Order (scheduled receipt) Lead time Lot size Low Level Code (LLC)

Outputs of MRP(Primary Reports) Planned order receipt – A schedule indicating the

quantity that is planned to arrive at the beginning of a period

Planned Order release – Authorizes the execution of planned orders (work order + purchase order). To determine planned order release, count backward from the planned order receipt using the lead time

Order changes report – Changes to planned order, including revisions for due dates or order quantities and cancellation of orders

Outputs of MRP(Secondary Reports) Performance control report – evaluate

system performance, deviations from plans, missed deliveries, and stock outs

Exception reports – attention to major discrepancies such as late and overdue orders, requirements for non-existence parts, reporting errors

MRP Terminologies

Gross Requirements: Total demand for an item during each time period. For end items, these quantities are shown in the master production schedule For components, these quantities are derived from the planned

order releases of their immediate parents

Scheduled Receipts: Orders that have been released and scheduled to be received from vendors by the beginning of a period

Projected On-Hand: The expected amount of inventory that will be on hand at the beginning of each time period (SR + Avl inv from last period)

MRP Terminologies

Net requirements: The actual amount needed in each time period

Planned Order Receipts: The quantity expected to be received from a vendor or in-house shop at the beginning of the period in which it is shown. It is the amount of an order that is required to meet a net requirement in the period. Under lot-for-lot ordering, this quantity will equal net requirements.

Under lot-size ordering, this quantity may exceed net requirements. Any excess is added to available inventory in the next time period.

MRP Terminologies

Planned Order Release: Indicates a planned amount to order in the beginning of each time period; equals planned-order receipts offset by lead time.

Format of MRP

Week Number 0 1 2 3 4 5 6 7 8

Item:Gross requirements

Scheduled receipts

Projected on hand

Net requirements

Planned-order receipts

Planned-order releases

MRP Explosion

The MRP process of determining requirements for lower level items (subassemblies, components, raw materials) based on the master production schedule

Planned Order Report

PERIOD

ITEM 1 2 3 4 5

A X1 X2 X3

B Y1 Y2

C Z1 Z2 Z3

Lot Sizing in MRP Systems

Lot-for-lot (L4L)Sets planned orders to exactly match

the net requirements. Eliminates holding costs

Economic order quantity (EOQ)Balances setup and holding costs

Lot Sizing in MRP Systems

Least total cost (LTC) Balances carrying cost and setup cost for various

lot sizes, and selects the one where they are most nearly equal

Least unit cost (LUC) Adds ordering and inventory carrying costs for

each trial lot size and divides by number of units in each lot size, picking the lot size with the lowest unit cost

Lot-for-Lot

Class Exercise

Problem 1

Basic Data

Cost per item: Rs 10 Order cost: Rs 47 Inventory carrying cost/week: 0.5% of unit cost

Weekly net requirements:

1 2 3 4 5 6 7 8

50 60 70 60 95 75 60 55

Rs 376

Lot Size: EOQ

Rs171.0577.05 94

Least Total Cost

Rs140.5046.5 94

Least Unit Cost

Rs153.5059.5 94

Lot Size Cost Comparisons

L4L: Rs 376 EOQ: Rs 171.05 Least Total Cost: Rs 140.50 Least Unit Cost: Rs 153.50

Preferred method: Least Total Cost

MRP and Capacity Planning

MRP , as it was originally introduced, considered only materials. MRP does not compare the planned orders to the available capacity. Most MRP plans assume infinite loading; that is an infinite amount of capacity is available, which is not realistic. Individual machines or work centres may have capacity shortages and backlogs of work to be completed

We therefore need capacity planning.

Two Approaches to Capacity Planning Rough-cut capacity planning

Uses the MPS (end item) as the source of product demand information

Capacity determination at critical work centres Capacity Requirement Planning

Completed at the component level rather than at the end item level

Uses planned order release from MRP Capacity determination at all work centres

Focused on criticalwork centres

Rough-Cut Capacity and CRP

Capacity Requirements Planning (CRP) CRP determines if all the work centres

involved have the capacity to implement the MRP plan.

A load profile compares weekly loads needs against a profile of actual capacity.

CAPACITY REQUIREMENT PLANNING

Workload for a Work Center

Capacity

Work center Effective Capacity/week (2 machines):

(# machines)×(# shifts)× (# of hours/shift)× (# days/week)×

(utilization)×(efficiency) Utilization: Time working / Time available

Efficiency: Actual output / standard output

Load: Standard hours of work assigned to a production facility

Load % = (Load / Capacity)×100%

Scheduled Workload for a Work Center

2m/c * 2 shifts/day * 10 hours/shift * 5 days/week * 85%(m/c Util) * 0.95 (m/c efficiency) =161.5 hrs/week

Capacity Levelling

Work Overtime Selecting an alternative work center Subcontract Scheduling part of work of week 11 into

week 10 Renegotiate due date

Safety Stock

It would seem that an MRP inventory system should not require safety stock. Practically, however, there may be exceptions. Typically SS built-into projected on-hand inventory

Why is safety stock necessary? Two types of uncertainties are prevalent

A. The quantity of components received (soln: SS)I. Poor quality may result in quantity loss

II. Reliability in supplier may result in quantity uncertainty

B. Timing of the receipts (solution: safety time)A. Machine breakdowns, fluctuations in staffing

Updating MRP Schedules

Updating MRP schedule is required because Customers may cancel or amend order Suppliers could default on supply Unexpected disruptions in manufacturing

Two techniques of updating Regeneration, i.e., re plan the whole system (run MRP from

scratch, updated periodically, 100% replacement of the existing information)

Net change Instead of running the entire MRP system, schedules of

components pertaining to portions where changes have happened are updated.

Applies to sub-set of data as opposed to regeneration

MRP Dynamics - System Nervousness MRP systems work best under conditions of reasonable

stability Frequent changes in an MRP system leads to major

changes in the order profiles for lower level subassemblies or components creating havoc for purchasing and production departments. This is called system nervousness Two tools are helpful in reducing system nervousness Time fences

Freezing the Master Schedule

Time Fences in MPSTime Fences in MPS

Period

“frozen”(firm orfixed)

“slushy”somewhat

“liquid”(open)

1 2 3 4 5 6 7 8 9

Time Fences divide a scheduling time horizon into three sections or phases, referred as frozen, slushy, and liquid.

Strict adherence to time fence policies and rules.

Pegging

Tracing upward in the BOM from the component to the parent item. By pegging upward, the production planner can determine the cause for the requirement and make a judgement about the necessary for a change in schedule

Reduction in inventory Increased customer satisfaction due to

meeting delivery schedules Faster response to market changes Improved labor & equipment utilization Better inventory planning & scheduling

MRP Benefits

Benefits of MRP

Ability to easily determine inventory usage by backflushing

Back flushing: Exploding an end item’s bill of materials to determine the quantities of the components that were used to make the item.

MRP – Problems Encountered

Data integrity is low Not frequent updates of databases when

changes takes place Uncertainties related to lead time and

quantity delivered

Requirements of Successful MRP System

Computer and necessary software Accurate and up-to-date

Master schedules Bills of materials Inventory records

User knowledge Management support

Evolved from MRP in 1980s Didn’t replace or improve MRP. Rather expanded the scope

to include capacity requirements planning and to involve other functional areas of the organization: Purchasing, Manufacturing, Marketing, Finance,

Logistics MRP II employed common database and an integrated

platform where sales, inventory, purchasing transactions were updated in both inventory and accounting applications

Manufacturing Resource Planning (MRP II)

MarketMarketDemandDemand

ProductionProductionplanplan

Problems?Problems?

Rough-cutRough-cutcapacity planningcapacity planning

YesYes NoNo YesYesNoNo

FinanceFinance

MarketingMarketing

ManufacturingManufacturing

AdjustAdjustproduction planproduction plan

MasterMasterproduction scheduleproduction schedule

MRPMRP

CapacityCapacityplanningplanning

Problems?Problems?RequirementsRequirements

schedulesschedules

An Overview of MRP II

Aggregate Sales and Operations Planning

Planning Level and Activities

Planning Stages in Operation

Aggregate Planning (or Sales and Operations Planning)

It is the process of planning the quantity and timing of output over the intermediate time horizon (often 3-18 months) by adjusting the production rate, employment, inventory, and other controllable variables

The term has been coined by companies to refer to the process that helps companies keep demand and supply in balance

Minimize long-run costs of meeting forecasted demand

Aggregate planning is a big picture approach to production plan to meet the demand throughout the year or so.

It is not concerned with individual products, but with a single aggregate product representing all products.

For example, in a TV manufacturing plant, the aggregate planning does not go into all models and sizes. It only deals with a single representative aggregate TV.

All models are lumped together and represent a single product; hence the term aggregate planning.

Aggregate Planning

What does Aggregate Mean?

Overall terms Product families or product lines rather than individual

products, thus the term aggregate In other words, one “collapses” a multi-product firm to

a single-product firm, the “product” being aggregate units of production

Big picture approach to planning Aggregate, for example # bicycles to be produced,

but would not identify bicycles by colour, size, type etc.

How does MPS differ from AP

Aggregation (Example)

Suppose a bicycle manufacturer makes three models (Standard, Deluxe, Sports)

Time: Standard: 30 m/c hours, Deluxe: 60 m/c hours, Sports: 90 m/c hours

Thus manufacturing 1 deluxe model is equivalent to manufacturing 2 standard models. 1 sports model is equivalent to manufacturing 3 standard models from resource consumption perspective

Thus a monthly demand of 1000 standard cycles, 500 deluxe, and 250 sports can be aggregated as 2750 standard models on the basis of machine hours

Identifying Aggregate Units of Production (Basic Data)

Family

Material Cost/ Unit

($)Revenue/ Unit ($)

Setup Time/Ba

tch (hour)

Average Batch Size

Production Time/ Unit

(hour)

Net Production Time/Unit

(hour)

Percentage Share of

Units Sold

A 15 54 8 50 5.60 5.76 10

B 7 30 6 150 3.00 3.04 25

C 9 39 8 100 3.80 3.88 20

D 12 49 10 50 4.80 5.00 10

E 9 36 6 100 3.60 3.66 20

F 13 48 5 75 4.30 4.37 15

Identifying Aggregate Units of ProductionProduct Family

Material cost/Unit (Rs)

Revenue / unit (Rs)

Prodn. Time /unit (includes setup time)

% share of units sold

A 15 54 5.76 10

B 7 30 3.04 25

C 9 39 3.88 20

D 12 49 5.00 10

E 9 36 3.66 20

F 13 48 4.37 15

Material cost / aggregate unit = 15*0.10+7*0.25+9*0.20+12*0.10+9*0.20+13*0.15 = Rs 10Revenue / aggregate unit = 54*0.10+30*0.25+39*0.20+49*0.10+36*0.20+48*0.15 = Rs 40Production time / agg. unit = 5.76*0.1+3.04*.25+3.88*0.20+5*0.1+3.66*0.20+4.37*0.15 = 4 hrs

Building a Rough Master Production Schedule Disaggregate an aggregate plan

Family

Setup Time/B

atch (hour)

Average Batch Size

Production Time/Unit

(hour)Production

Quantity

Number of

Setups

Setup Time

(hours)

Production Time

(hours)

A 8 50 5.60 258 5 40 1,445

B 6 150 3.00 646 4 24 1,938

C 8 100 3.80 517 5 40 1,965

D 10 50 4.80 258 5 50 1,238

E 6 100 3.60 517 5 30 1,861

F 5 75 4.30 387 5 25 1,664

Aggregate Size: Worm Gear Box (input shaft)

Size(input shaft)

Facing(mins)

Turning(mins)

Thread Mill(mins)

Key way(Mins)

HT(mins)

Thread Grind(mins)

Cyl Grind(mins)

Total(Hrs)

% market Share

400 5 20 20 2 480 15 15 9.28 15

500 5 22 25 3 480 20 20 9.58 25

600 6 23 27 4 480 25 25 9.83 20

700 7 25 30 5 480 30 30 10.11 6

800 8 30 32 6 480 35 35 10.43 15

1000 10 35 35 7 480 35 40 10.7 10

1200 12 38 40 8 480 40 40 10.96 9

Why Aggregate Planning?

Provides for fully loaded facilities, thus minimizingOverloading and under loadingMinimizing cost over the planning period

Adequate production capacity to meet expected aggregate demandOptimize balance between demand and

supply

Why Aggregate Planning?

A plan for orderly and systematic change of production capacity to meet peaks and valleys of expected customer demand

Getting the most output for the amount of resources available, which is important in times of scarce production resources

Steps in Aggregate Planning

1. Begin with sales forecast for each product that indicates the quantities to be sold in each time period (usually months, or quarters) over the planning horizon (3-18 months)

2. Total all the individual product or service forecast into one aggregate demand.

3. Determine capacities (regular time, OT, subcontracting) for each period

4. Determine unit costs for regular time, OT, subcontracting, holding inventories, back orders, layoffs etc.

5. Identify company policy (chase, level, mixed)

6. Develop alternative plans and compute cost for each

7. Select the best alternative that satisfies company’s objectives

Strategies for Meeting Demand

ProactiveAlter demand to match capacity

ReactiveAlter capacity to match demand

MixedSome of each

Proactive strategies Influencing Demand

Offer discounts and promotions

Increase advertising in slack periods

Counter seasonal products Lawnmowers (summer) and snow-blowers (winter)

Reactive StrategiesChanging inventory levelsVary workforce size (hiring and lay-off)Varying shiftsVarying working hoursVarying production through overtime or idle

timeSubcontracting

Inputs and Costs in AP

Decision Variable Costs

Varying work force size Hiring, training, firing costs

Using Overtime Overtime costs

Varying inventory levels Holding costs

Accepting back orders Back order costs

Subcontracting others Subcontracting costs

Outputs of Aggregate Planning

Total cost of a plan Projected levels of

Inventory heldOutput from

Regular time, overtime

EmploymentSubcontracting

Graphical Method

Popular techniquePopular technique

Easy to understand and useEasy to understand and use

Trial-and-error approaches that do Trial-and-error approaches that do not guarantee an optimal solutionnot guarantee an optimal solution

Require only limited computationsRequire only limited computations

Graphical MethodMonth Expected

DemandProduction Days

Demand /day

Avg. daily demand

Jan 900 22 41 50

Feb 700 18 39 50

March 800 21 38 50

April 1200 21 57 50

May 1500 22 68 50

June 1100 20 55 50

6,200 124

Graphical Method

Note: Forecast differs from average demand

Aggregate Planning Techniques

Two pure forms of aggregate planning strategies

Level Production Maintain constant workforce and

adjust inventory

Chase DemandHiring and Firing people

Aggregate Planning Techniques

Mixed Strategy Combination of

Overtime, under time, & subcontractingPart Time employeesHiring and firing InventoryBackordering

Note: When one alternative: Pure Strategy When two or more are selected: Mixed strategies

Level Production Strategy

It is an aggregate planning in which monthly production is uniform

Requires no overtime, no change in work force levels, and no subcontracting Toyota and Nissan follow this strategy Finished goods inventory go up or down to buffer the

difference between demand and production

Works when demand is stable

Level Production Strategy

LEVEL PRODUCTION STRATEGY

Assume begin inventory: 2000

Chase Production Strategy

It attempts to achieve output rates that match demand forecast for that period.

This strategy can be accomplished by: Vary workforce levels (hiring and firing)

Service businesses use because they don’t have the option to build inventory of their product

Chase Production Strategy

CHASE DEMAND STRATEGY

Chase vs. Level

Chase Approach

Advantages Investment in inventory

is low

Labor utilization in high

Disadvantages The cost of adjusting

output rates and/or workforce levels

Level Approach

Advantages Stable output rates and

workforce

Disadvantages Greater inventory costs

Increased overtime and idle time

Resource utilizations vary over time

Mixed Strategy

For most firms, neither a chase strategy nor a level strategy is likely to prove ideal, so a combination of options must be achieved to meet demand and minimize cost

More complex than pure ones but typically yield a better strategy

OVERTIME & SUBCONTRACTING

Linear Programming Approaches to AP Finds minimum cost solution related to

regular labour time, overtime, subcontracting, caring inventory, and costs associated with changing the size of workforce

Mathematical Techniques to Aggregate Planning Linear Programming

Optimal solutionsCost minimizationProfit maximization

Appropriate when cost and variable relationships are linear

Application in industry limited

Transportation Method in AP

Transportation Method (An Example)

Total Costs

Period Demand Regular Production

Overtime Subcontract End Inventory

1 900 1000 100 0 500

2 1500 1200 150 250 600

3 1600 1300 200 500 1000

4 3000 1300 200 500 0

Total 7000 4800 650 1250 2100

Total Cost: 4800×$20+650×$25+1250×$28+2100×$3 = $153,550

Transportation Method(Second Example – Prob 7)

Transportation Method: Cost of Plan Period 1: 50($0)+300($50)+50($65)+50($80)=$22,250 Period 2: 400($50)+50($65)+100($80)=$31,250 Period 3: 50($81)+450($50)+50($65)+200($80)=$45,800

Total Cost: $99,300

Simulation Models in AP

Development of computerized model under variety of conditions to find reasonably acceptable solutions

Advantages Lends itself to problems that are difficult to solve

mathematically Experimenting system behaviour without any risk Compresses time to understand system Understand system behaviour under wide range of

conditions

Simulation Models in AP

LimitationsSimulation does not produce optimal

solutions, it merely indicates approximate behaviour for a set of inputs

Simulations are based on models, and models are only approximation of reality

Summary of Aggregate Planning Techniques

Technique Solution Approach

Characteristics

Spreadsheet Heuristic (trial and error)

Intuitively appealing, easy to understand, solution not optimal

Linear Programming Optimizing Computerized

Simulation Heuristic (trial and error)

Computerized models can be examined under various scenarios

Business Plan

Scheduling

Specifies when labour, equipment, and facilities are needed to produce a product or a service

Scheduling deals with timing of operations

Scheduling occurs in every organization

Classroom Schedule Chart

Gantt Progress ChartGantt Progress Chart

Plymouth

Pontiac

Job 4/20 4/22 4/23 4/24 4/25 4/264/214/17 4/18 4/19

Current Current date date

Scheduled activity time

Actual progress

Start activity

Finish activity

Nonproductive time

Gantt Progress Chart for an Auto Parts Company

Gantt Workstation Chart Gantt Workstation Chart

Gantt Workstation Chart for Hospital Operating Rooms

Dealing with the Problem Complexity through Decomposition

Aggregate Planning

Master Production Scheduling

Materials Requirement Planning

Aggregate UnitDemand

End Item (SKU)Demand

Corporate Strategy

Capacity and Aggregate Production Plans

SKU-level Production Plans

Manufacturingand Procurementlead times

Component Production lots and due dates

Part processplans

(Plan. Hor.: 1 year, Time Unit: 1 month)

(Plan. Hor.: a few months, Time Unit: 1 week)

(Plan. Horizon.: a few months, Time Unit: 1 week)

Shop floor-level Production Control(Plan. Hor.: a day or a shift, Time Unit: real-time)

Reasons for Planning for Short-Term Additional information becomes available

Order cancellation, new orders, terms of existing orders Random occurrence of events

Breakdown of machines, absenteeism, delays in raw material supply, revision of job priorities

Fine tune planning and decision making

Focus on micro-resources Single machine, set of workers and so on Such focus is neither possible nor warranted in medium or lon-

term planning

Scheduling

Scheduling takes place inHigh-volume systems Intermediate-volume systemsLow-volume systems

Scheduling

Categorize scheduling techniques asForward schedulingBackward scheduling

Scheduling Techniques

Forward SchedulingRefers to situation in which the system takes

an order and then schedules each operation that must be completed forward

Applications Hospitals and clinics Fine-dining restaurants Machine tool manufacturers

For special machines

Backward Scheduling

Backward SchedulingStarts from some date in future (due date)

and then schedules the required operations in reverse sequence

Applications Assembly programs in manufacturing Holding conferences Scheduling surgery Marriages

Forward Vs. Backward Scheduling

Start processing when order is received regardless of due date

Schedule the job’s last activity so it is finished right before the due date

Objectives of Scheduling

Meeting customer due dates Minimizing job lateness Minimizing response time Minimizing time in system Maximizing machine or labour utilization

Job Shop Scheduling

Job shop scheduling also known as production control or shop floor control

Responsibilities of production control dept. are Loading Sequencing Dispatching Monitoring Preparing various reports (scrap, performance,

rework)

Loading

Loading is a capacity control technique that decides which jobs to assign to which work centers

Loading Work Centers

Infinite loading Finite loading

Sequencing

When more than one job is assigned to a machine or activity, the operator needs to know the order in which to process the jobs. The process of prioritizing jobs is called sequencing

Dispatching

Administrative process of releasing of a work order from the production planning department to production authorizing processing of jobs Shop paperwork

Monitoring

Maintaining progress on each job until completed

Priority Rules for Job Sequencing (n Jobs on One M/c)

Single Dimension RulesFirst Come First Served (FCFS)Shortest Processing Time (SPT)Earliest Due Date (EDD)Longest Processing Time (LPT)Smallest Critical Ratio

Performance measures

Flow time: Length of time a job is at a particular work station (Processing time + Transport time + any waiting due to breakdown, parts non-availability, quality problems etc.)

Makespan: Total time needed to complete a group of jobs. It is the time between start of the first job in the group and the completion time of the last job in the group

Performance Measures

Job Tardiness is the difference between a late job’s due date and its completion time

Metrics

Average flow time per job Utilization Average job tardiness Average # jobs in the system (WIP)

Sequencing (An Example)Job Processing

Time (days)Job Due Date

C 8 18

D 3 15

E 9 23

FCFS Job Seq(1)

Proc Time (days)

Flow Time (days)

Job Due Date (4)

Job Tardiness(3) - (4)

A 6 0+6 = 6 8 0

B 2 6+2 = 8 6 2

C 8 8+8 = 16 18 0

D 3 16+3 = 19 15 4

E 9 19+9 = 28 23 5

TOTAL 28 77 11

AVG. 77/5 =15.4 days

11 / 5 = 2.2 days

FIRST COME FIRST SERVED (FCFS)

Metrics

Avg. flow Time = Sum of total flow time / # jobs = 77 /5 = 15.4 days

Utilization = Total proc. time / Sum of total flow time

28 / 77 = 36.4% Avg # jobs in system = Sum of flow time /

Total job processing time

77 days / 28 days = 2.75 jobs Avg job tardiness = Total late / # jobs = 11 / 5 = 2.2 days

SPT Job Seq(1)

Proc Time(2)

Flow Time(3)

Job Due Date(4)

Job Tardiness

B 2 0+2 =2 6 0

D 3 2+3=5 15 0

A 6 5+6 =11 8 3

C 8 11+18 =19

E 9 19+9 =28 23 5

Total 28 65 9

SMALLEST PROCESSING TIME (SPT)

SPT Metrics

Avg. flow time = 65 / 5 = 13 days Utilization = 28 / 65 = 43.1% Avg. # jobs in the system = 65 / 28 = 2.32

jobs Avg job lateness = 9 / 5 = 1.8 days

EDD Job Seq(1)

Proc Time(2)

Flow Time(3)

Job Due Date(4)

Job Tardiness

B 2 2 6 0

A 6 8 8 0

D 3 11 15 0

C 8 19 18 1

E 9 28 23 5

TOTAL 28 68 6

EARLIEST DUE DATE (EDD)

LPT Job Seq Proc Time Flow Time Job Due Date

Job Tardiness

E 9 9 23 0

C 8 17 18 0

A 6 23 8 15

D 3 26 15 11

B 2 28 6 22

TOTAL 28 103 48

Longest Processing Time (LPT)

Sequencing Rule

Avg. Flow Time

Util. (%) Avg. # jobs in system

Average tardiness

(days)

FCFS 15.4 36.4 2.75 2.2

SPT 13.0 43.1 2.32 1.8

EDD 13.6 41.2 2.43 1.2

LPT 20.6 27.2 3.68 9.6

Critical Ratio (CR)

Time Remaining until due date

CR = ----------------------------------

Workdays remaining

Due Date – Today’s Date

CR =----------------------------- Workdays remaining (remaining processing time)

Critical Ratio (CR)

If CR < 1.0, Job falling behind schedule If CR = 1.0, Job on schedule If CR > 1.0, Job ahead of schedule

Priority Rule (FCFS)

Advantages For service systems

Dominant priority rule Appear fair to

customers

Simplicity

Disadvantage Long jobs will tend to

delay other jobs

Priority Rule (EDD)

Advantages Addresses due dates Intuitively appealing Minimizes tardiness

Disadvantages Ignores processing

time Long waiting for other

jobs Shop congestion High In-process

inventories

Priority Rules (SPT)

Advantages Lowest avg.

completion time Lower WIP

Lower tardiness Better customer service

levels

Lowest avg. # jobs in the system

Less congestion Ideal where shop is

highly congested

Disadvantage Tend to make long

jobs wait

Solution- truncated SPT

Sequencing (n Jobs on 2 Machines) Johnson’s Rule

Objective is to minimize processing time for sequencing a group of jobs through two work centers

Developed by S M Johnson in 1954 for job shop scheduling

Examples (2 work centres)

A book binding operation where books must first pass through binding before going to trimming

Finished products must pass through inspection before packaging

A medical clinic where patient goes for registration and then consulting

Steps – Johnson’s Rule

1. All the jobs are to be listed, and the time that each requires on a machine is to be shown. Set up a one-dimensional matrix to represent the desired sequence with the number of slots equal to # of jobs

2. Select the job with the shortest activity time. If the shortest time lies with the first machine, the job is scheduled first. If the shortest time lies with the second machine, schedule the job last.

Steps – Johnson’s Rule

3. Once a job is scheduled, eliminate it

4. Repeat steps 2 and 3 to the remaining jobs until all the slots in the matrix have been filled or all jobs have been sequenced

5. If a tie for the shortest processing time occurs in the same work station, the competing two job sequences need to be evaluated by comparing cumulative processing times. The lowest cumulative processing time would be the recommended sequence

Johnson’s Rule (Conditions)

Job time (set up + proc time) must be known for each work center

All jobs follow same two-step sequence All units in a job must be completed at the first

work center before moving to second work center

Johnson’s Rule (An Example)

Jobs Work Center 1(hrs)

Work Center 2(hrs)

D 10 7

E 7 12

Johnson’s Rule

B E D C A

Johnson’s Rule

Work Center 1

Work Center 2

3 7 10 8 5

6 12 7 4 2

B E D C A

Johnson’s Rule

Gantt Chart

Makespan – 35 hours

Johnson’s rule – 3 work centres

Three work centres is an extension of the previous model (2 work-centres)

Examples A book binding operation where books pass through

printing and binding before going for trimming Finishing products, which pass through inspection,

painting, before going to packaging A medical centre where patients see a doctor, pass

onto x-ray, and then consult a specialist

Johnson’s rule can be applied if either of the following two criteria applies: The smallest time at the first processing operation is

at least as great as the largest duration on the second processing operation

The smallest duration on the third processing operation is at least as great as the largest duration on the second operation.

Johnson’s rule – 3 work centresBeauty Products Pre-preparation

(hour)Preparation(hour)

Finishing(hour)

Baby Blue 7 1 3

Virgin White 6 4 2

Shy Pink 8 5 4

Daring Purple 9 2 5

Sensuous Black 10 3 7

Minimum of 1st operation, i.e., 6 >= maximum of second operation, i.e., 5Therefore, Johnson’s rule can be applied

Johnson’s rule – 3 work centresBeauty products Work centre 1

Operation time (hour)Work centre 2Operation time (hour)

Baby Blue (BB) 7+1 = 8 1+3 = 4

Virgin White (VW) 6+4 = 10 4+2 = 6

Shy Pink (SP) 8+5 = 13 5+4 = 9

Daring Purple (DP) 9+2 = 11 2+5 = 7

Sensuous Black (SB) 10+3 = 13 3+7 = 10

Apply Johnson’s rule with two work centres

Sequence: SB SP DP VW BB

Scheduling a Set Number of Jobs on the Same no. of Machines

Some work centres have enough of the right kinds of machines to start all jobs at the same time

Assignment Method (special case of transportation method) There are n “things” to be distributed to n “destination” Each thing must be assigned to one and only one

destination Only one criteria can be used (min cost or max profit)

Assignment Method

Job A B C D E

I Rs 5 Rs 6 Rs 4 Rs 8 Rs 3

II Rs 6 Rs 4 Rs 9 Rs 8 Rs 5

III Rs 4 Rs 3 Rs 2 Rs 5 Rs 4

IV Rs 7 Rs 2 Rs 4 Rs 5 Rs 3

V Rs 3 Rs 6 Rs 4 Rs 5 Rs 5

Five jobs, 5 machines, Cost of each job given. Devise min cost assignment.

Shop Configuration

Refers to the manner in which machines are organized on the shop floor and the flow pattern of the jobs utilizing these machines

Two alternative configurationsFlow shopJob shop

Introduction-Elements of the Job Shop Scheduling Problems

An assembly line is a classic example of flow shop

Every car goes through all the stations one by one in the same sequences;

Same tasks are performed on each car in each station; Its operations scheduling is simplified as assembly line balancing; An assembly balancing problem is to determine the number of stations

and to allocate tasks to each station.

Flow shop: Each of the n

jobs must be processed through the m machines in the same order.

Each job is processed exactly once on each machine.

A Pure Flow Shop

As there are n jobs, there are n! ways in which one can draw up alternative schedules in the shop

In flow shop resources are organized one after another in the order the jobs areprocessed

Since all jobs follow the same order of visiting machines, the scheduling functionIs essentially reduced to one of ordering the jobs in front of the first machine.

Job Shop

Low volume job shop operations are designed for flexibility

Each product or service may have its own routing (scheduling is much more difficult)

Bottlenecks move around depending upon the products being produced at any given time

Introduction-Job Shop

A job shop is organized by machines which are grouped according to their functions.

Introduction-Job Shop

Not all jobs are assumed to require exactly the same number of operations, and some jobs may require multiple operations on a single machine (Reentrant system, Job B twice in work center 3 ).

Each job may have a different required sequencing of operations.No all-purpose solution algorithms for solving general job shop problems

;Operations scheduling of shop floor usually means job shop scheduling;

Job Shop

Since there are n! ways of rank-ordering jobs in front of a machine and sincethere are m machines in the shop, and all jobs are processed on all machines, the number of alternatives that one can draw for a job shop is given by (n!)m

Job 1: 1-4-2-5-6Job 2: 3-2-1-4-6-7Job 3: 2-3-4-7-5-6

Job Shop

Scheduling n jobs on m machines

Number of alternative schedules (n!)m

Complex

Likely solution - Simulation

Some Insights

Bad newsReal world > 2 machinesProcess times are not deterministicReal world production scheduling problems

are hard Hard to find optimal solutions to realistic size

scheduling problems Far from exact science

Minimizing Scheduling Difficulties Good News

Setting realistic due datesFocus on bottlenecks

Schedule this resource and propagate the schedule to non-bottleneck resource

Bottleneck Scheduling

Common approachSimplify problem by breaking into pieces

Scheduling bottleneck stations and then propagating that schedule to non-bottleneck stations

Old Oregon Wood Store

Scheduling – United Airlines

Lean Manufacturing

Minus-Cost Principle

Cost + Profit = Selling Price

Profit = Price – Cost

Toyota Production System(Lean Manufacturing)

Taiichi Ohno (1912-1990), Toyota executive pioneered the conceptTo do more and more with less and less

Less human effort Less equipment Less time Less space Less capital

Toyota Production System

Toyota Production System System for absolute elimination of waste80% waste elimination15% production system5% kanban

Drive out waste so that all work adds value and satisfies customer’s need

Lean Production(Levels of Abstraction) Lean production has been described at

three levels1. Philosophical perspective

A. Elimination of waste (Womack and Jones,1996)

2. Implementation of tools and techniques

3. System design using three rules

What is Waste?

Waste is defined as any activity that does not add value to a product from customer’s perspective

Fujio Cho, Toyota’s president defined“Anything other than the minimum amount of

equipment, materials, parts, and workers essential for production”

Seven Categories of Muda

Muda means Waste1. Overproduction

2. Unnecessary Inventory

3. Transportation

4. Over Processing

5. Waiting

6. Unnecessary motion

7. Product Defects

Overproduction

Unnecessary Inventory

The “Rocks in the Stream” Concept

Production Problems

Lowering the “Water” Level

Production Problems

InventoryReductions

CRUNCH!

Transportation

Waiting

Unnecessary Motion

Overprocessing

Defects

How Time is Spent by a Typical Part in a Batch Production Machine Shop

Time on M/c

Moving and WaitingTime in factory

Time on m/c

30% 70%

Cutting Loading, positioning,gauging

Class Exercise

Students identify waste in their organization

Wastes in IT Sector

How long did you wait to start a scheduled meeting?

How many reports you created that nobody read?

How much time you waited for a decision from your superior?

How much rework you did while developing the software?

Activities

Value-addedMakes a product more complete

Non-value-addedDoes not add value in the customer’s eyes

and customer unwilling to pay

Required non-value-added

Value-added Activity

An activity that makes a product a more complete product, in the eyes of the customer

The value is defined from customer’s point of view

End result is the receipt of cash for our actions

Required Non-Value Added Activity Activity for which the customer is likely to

We can change and improve the method of performing these activities

Non-Value Added Activity

The activity that consumes time and resources but does not advance the product to a more complete or finished state. Adds no value in the customer’s eyes and that customer is unwilling to pay for

Seven categories of waste Overproduction, unnecessary motion, transport,

process, waiting, unnecessary motion

Basic Words

Seven forms of waste composed of non-value added activities, add cost

The value added activities, generate revenues

Conversion TimeConversion Time

Value-added

Start of productionfor a single item

Components of Components of Lead TimeLead Time

Nonvalue-added

Wait TimeWait Time Move TimeMove Time Down TimeDown Time

End of productionfor a single item

Total Lead Time

Relationship Between Setup Relationship Between Setup Times and Lead TimesTimes and Lead Times

Long Long Setup Setup TimesTimes

Large Large Batch Batch SizesSizes

Large Large InventoryInventory

Longer Lead Times

Value Stream Mapping

Process mapping tool that enables all stakeholders of an organization to visualize and understand a process

To differentiate value from waste Eliminate waste

Chinese Proverb: “One picture is worth ten thousand words”

Value Stream Map

Walking and drawing the processing steps (material and information) for one product family from door to door in your plant

Value Stream Mapping

To maximize value and eliminate waste1. Form inter-disciplinary team2. Mapping the current key process how it actually

operates Identify value added and non-value added activities Eliminate non value added activities using Kaizen

(continuous incremental improvement)1. Develop future state value stream map

Takt Time

Available work time

per day

Takt Time = --------------------------------

Customer demand rate

per day

TPS Terminologies

Ways to Eliminate NVAs

Rearranging sequence Consolidating process steps Changing work methods Change type of equipment Redesigning forms and documents Improving operator training Eliminate unnecessary steps

Multiple explanations for Toyota’s success:Elimination of wasteUsing specific tools for productionDesign Rules

Lean – Tools and Techniques

1. Pull Systems2. Cellular Layout3. Uniform Plant Loading (Heijunka)4. Small lot sizes5. Minimized set-up times6. Kanban Systems7. Quality at source (Poka-Yoke)8. Flexible Resource9. Total Productive maintenance10. 5S

1. Traditional Production

1. Continuous Flow(One-piece flow)

1. Traditional vs. Lean Approach

1. Pull vs. Push (Traditional)

Pull Method: A method where customer demand activates the production of service or item. Work releases are authorised

Push Method: A push method where the production of the item begins in advance of customer needs. Work releases are scheduled

1. Pull Systems

Push vs. Pull

Show Video

VTS_02_1.VOB

2. Cellular Layouts

Cells group dissimilar machines to process parts with similar shapes or processing requirements

2. Cellular Layout

Process (Functional) LayoutProcess (Functional) Layout Group (Cellular) LayoutGroup (Cellular) Layout

Similar resources placed together

Resources to produce similar products placed together

MM M T

SG CG CG

T T T CG CG

T T T SG SG

M M D D D

A cluster or cell

3. Uniform Plant Loading (Heijunka)

Mixed model production

LEVELLED PRODUCTION

Levelled production means producing various models on the same production line to cater the customer demand. See the following diagram. The various products are shown in the form of different geometrical shapes. Assume they are different models of vehicles being produced on the same production line.

Production leveling is done by finding the ratio of demand of various models. Instead of producing batches of the same model, mix models are produced on the same production line according to the ratio of their demand in the market.

This is how customers do not have to wait for long and throughout the month all the customers are served equally well

Uniform Plant Loading (Maruti)

Tata Motors Plant

4. Small Lots

Use lot sizes as small as possible Advantages

Average level of inventory lessPass through the system fasterQuality problems are detected fastEasier to schedule

DisadvantageMultiple set ups

5. Minimized Set up Times

Small lot sizes to make mixed models Japanese workers: 800 T, time: 10 mins US workers time: 6 Hrs German workers time: 4 Hrs

Set Ups Internal (Done when m/c is stopped); disruptive External (Done when m/c is running)

Convert internal to external set ups Abolish the setup itself (uniform product design) Single Minute Exchange of Dies (SMED)

Internal and External set up

VTS_02_2.VOB

6. Kanban System

Kanban post

7. Quality at Source

Emphasis on eliminating defects at their origination points

Workers act as inspectors Jidoka (the authority of the workers to stop the line if quality problems

encountered)

Andons or call lights Each worker given access to andons to seek help.

Visual control of quality Poka-Yoke

Are either warnings that signal existence of a problem or controls that stop production until the problem is resolved

Minimize human errors http://facultyweb.berry.edu/jgrout/everyday.html

Errors in Service

Service Error

Server Errors Customer Errors

(67%) (33%)

Classifying Service Poka-Yokes

Server ErrorsTask:

Doing work incorrectly

Treatment:

Failure to listen to customer

Tangible:

Errors in physical elements of service (dirty waiting rooms, unclear bills)

Customer ErrorsPreparation:

Failure to bring necessary materials before the encounter

Encounter:Failure to follow system flow

Resolution:Failure to signal service failureFailure to execute post encounter actions

8. Flexible Resource

Multifunctional workers General purpose machines

9. Total Productive Maintenance (TPM) Eliminating causes of machine failure Maximizing effectiveness of machine throughout

its entire life Involving everyone in all departments and at all

levels TPM develops a maintenance system Central to TPM is the concept of Overall

Equipment Effectiveness (OEE)

Overall Equipment Effectiveness(OEE) OEE =

Availability Rate * Performance Rate * Quality Rate

OEE captures six big losses which result in reduced effectiveness of using an equipment

Availability: % of scheduled time that the operation is available to operate. Often referred to as Uptime.

Performance: Speed at which the work centre runs as a % of designed speed

Quality: Good units produced as a % of total units produced

Can be applied to any individual work centre or rolled up to department or plant levels

10. 5 Elements of 5S

1. Sort: Remove all unnecessary material and equipment

2. Straighten: Make it obvious where things belong

3. Shine: Clean everything, inside and out4. Standardize: Establish policies and

procedures to ensure 5S5. Sustain: Training, daily activitiesNote: Some add 6thS for “safety”

4S: Place for Cleaning Supplies

4S: Equipment Storage Area

4S: Peg Board for Tools

4S: Hazardous Waste

Measuring and Tracking 5S

Multiple explanations for Toyota’s success:Elimination of wasteUsing specific tools for production (SMED,

Poka Yoke)Design Rules

Spear and Bowen article

Toyota Production System (Design Rules)

Design Rules to design work processesActivityConnectionsPathways

Rule 1: Activity

All work shall be highly specified as toContentSequenceTimingOutcome

Specified Tasks

Rule 2: Connections

Every customer-supplier connection must be direct and there must be an unambiguous yes-or-no way to send requests and receive responses

Streamlined communication

Rule 3: Pathways

The pathway for every product and service must be simple and direct

Simple process architecture

Rule 4: Scientific Problem Solving

Any improvement must be made in accordance with the scientific method, under the guidance of a teacher, at the lowest possible level in the organization

Hypothesis-driven problem solving

Backslide

What usually happens

Backslide

“Actual”

If worked to the new standards

Innovate

Adapted from: Imai, “Kaizen”

Continuous Improvement

Conceptual A3 Proposal

Basic Structure and Flow of A3 Report

A3 Problem Solving: The Toyota Way

5 Whys Approach

A workstation starved for workWhy starved? A pump failed

Why pump failed? It ran out of

lubricant

Why it ran out of lubricant? A leaky

gasket not detected

Why leaky gasket not detected? Lack of training

Three Rules

What kinds of wastes are eliminated?

Questions

Do principles of lean production apply to knowledge work?

How can we extend the existing framework of lean production to a new context that differs substantially from that in which lean was observed?

Gortrac – Process Improvement2

Flexible Manufacturing Strategy

Quality Management and SPC

History of Quality Management

Rooted in Post-World war II Japan Japanese in an effort to build their nation adopted the US

manufacturing practices Embraced and suppported the work of two American

researchers: Joseph Juran (1904-2008) and W Edwards Deming (1900-1993)

Juran blamed the culture of the firm and management for poor quality

Deming developed SPC for industries Japanese industry leaders embraced the idea that efforts

to improve quality can actually reduce costs

History of Quality Management

By 1970s and 1980s, US market was invaded by Japanese electronic and automobile products

Toyota was already using advanced quality management system, and TPS became the international superstar of manufacturing practice In late 1980s, Motorola developed the Six Sigma (SS)

approach, others (GE, Seagate, AlliedSignal) adopted SS

TQM, another well-known method adopted by industry

Performance and Conformance

Successful quality management requires managers to understand what constitutes quality for the customer

Firms need to identifying the needs of the customers (internal or external) and provide a product or service that will satisfy or exceed their expectations

Performance and Conformance

Different kinds of quality Performance quality

Refers to the ability of the product to excel along one or more performance dimensions (“attributes”)

Conformance quality Because of inherent variability in production

processes, nothing is produced exactly according to specifications. The degree of match between specifications and the actual product or service is what we call as conformance quality

Quality Article

“Competing on eight dimensions of quality” (Harvard Business Review, Nov-Dec 1987) by David Garvin

Dimensions of Quality: Manufactured Products Performance – primary product characteristics Features – secondary characteristics Reliability – How often does the product fail?

Consistency of performance Conformance to standards – meeting design

specifications Durability – How long the product lasts; its life span

before replacement Serviceability – ease of repair, speed of repair Aesthetics – sensory characteristics (sound, feel, look) Perceived Quality – past performance, reputation,

recognition

Article – Key Points

Eight dimensions of quality Companies need not pursue all eight

dimensions If pursued, products become costly

Companies need to find what dimensions customers care for and work on those dimensions Proper market research is key

Some Quality Issues in Recent Times – Indian companies Safety features in Indian made passenger

vehiclesFive Indian made hatchbacks failed in New

Car Assessment Program (NCAP) Test Banning of Indian drugs in US for some Indian

pharmaceutical companies for poor manufacturing practicesRanbaxy, Wockhardt, RPG Life Sciences and

Quality Gurus

Walter Shewart W. Edward Deming Joseph Juran Armand V. Feigenbaum Philip Crosby Kaoru Ishikawa Taguchi

Key Contributors to Quality ManagementShewart Control Charts

Deming 14 points, special vs. common cause variation

Juran Quality is fitness-for-use

Feigenbaum Customer defines quality

Crosby Quality is free, zero defects

Ishikawa Cause-and-effect diagrams

Taguchi Taguchi loss function

Ohno and Shingo Continuous improvement

Modern Definition of Quality

Quality is inversely proportional to variability Reduction of variability is the fundamental idea in quality control.

Describing Variability

Measures of variability (or spread out)Range Variance and the standard deviationStem-and-leaf plotHistogramBox PlotCoefficient of variation

Quality Improvement

Quality improvement is the reduction of variability in processes and products

Describing Variability

Stem-and-leaf display (Graphical display about a data set) Shape Spread Central tendency

Box Plot (Graphical Display) Central tendency Spread or variability Departure from symmetry Identification of outliers

Histogram Same as above

Histogram

Coefficient of Variation

Coefficient of Variation, c = σ / µWhere σ = standard deviation

µ = mean

If c<0.75 , low variability If 0.75 <= c <=1.33, moderate variability If c >= 1.33, High variability

Approaches to Quality Assurance

Acceptance Sampling Process Control Continuous

Improvement

The least progressive

The mostprogressive

Inspection before/After production

Inspection and corrective actionduring production

Quality built inthe process

Acceptance Sampling and Process Control

TransformationInputs Output

Acceptance Sampling Process control

Acceptance Sampling

Inspection before and after production often involves acceptance samplingProcedures; monitoring during the production process is referred to as processcontrol

Acceptance Sampling

In acceptance sampling, managers take two key decisionsWhen in the process to conduct inspections

How rigorously to test Frequency of inspection How many products to test each time

When in the Process to Inspect?

Raw materials and purchased parts Finished products Before a costly operation or where

significant value is added to the product Before an irreversible process Before a covering process

How Much to Inspect and How Often? The amount of inspection can range from no inspection

whatsoever to inspection of each item. Low –cost, high volume items require less inspection High-cost, low volume items require intensive inspection Majority of the quality control applications lie somewhere

between the two

As a rule, operations with high proportion of human involvement necessitatemore inspection than mechanical operations

Costs of Quality

Prevention Costs (costs associated with tasks intended to prevent defects from occurring) Quality Planning (developing & implementing quality

management program) Process monitoring Training Purchasing better equipment that produces less variation Working with vendors to increase the quality of input materials Process redesign to reduce errors Quality data acquisition and analysis Quality improvement projects

Costs of Quality

Appraisal Costs (assessing the condition of materials and processes at various points in process) Inspection and testing of incoming materialsProduct inspection and test at various stagesMaintaining accuracy of test equipment

(calibration)Laboratory testing

Costs of quality estimated to be between 15%-20% of sales at most companies Crosby

Cost of Quality

Internal failure costs (defects discovered before shipment) Scrap Rework Process downtime Retest Failure analysis Disposition

External failure costs (defects discovered after shipment) Customer complaint Warranty charges Liability costs Returned product/material

External and internal failure costs together accounted for 50%-80% of COQ Juran

The Costs of Quality

Cost of Quality

Quality Cost Trend Prediction as a Function of Time

Cost of Quality

It is estimated that the cost to fix a problem at the customer end is about 5 times thecost to fix a problem at the design stage

Cost of Quality

Ce + Ci + Ca + Cp Cost of Quality= --------------------------------------

Cb + Ce + Ci + Ca + Cp

Ce = External failure cost

Ci = Internal failure cost

Ca = appraisal cost

Cp = prevention cost

Cb = measured base production cost ( no costs for quality)

Consequences of Poor Quality

Loss of business Liability Productivity Costs

Process Control

Starts with measuring an important variable. This can be aProduct attribute

Diameter of a metal component, weight of a bag of potato chip

Process Attribute Temperature in a restaurant’s oven, length of

waiting time in a ticket booth, pressure applied in a molding process

Statistical Process Control (SPC) A statistical process control involves testing a random

sample of output from a process to determine whether the process is producing items within a pre-selected range

SPC uses statistical tools to observe the performance of the production process in order to detect significant variations before they result in the production of a sub-standard article.

SPC is about monitoring consistency and repeatability of a process

Major Objectives of SPC

Quickly detect the occurrence of assignable causes of process so that investigation of the process and corrective action may be undertaken before non-conforming units are manufactured

Reducing variability in the process

Why Quality Problems?

Variation due to two reasons

Common Cause or random variation

Assignable or Special cause or controllable variation

Statistical Process Control Tools (SPC) Variation in output is due to:

Common causes (also known as natural variation) Inherent variation present in every process Causes may difficult to distinguish or wholly

unidentifiable Resulting degree of variation is minor

Assignable causes (known as special variation) Variations due to specific causes

A process subject to assignable variation is out of control

Statistical Process Control Tools (SPC) Control (or in control or stable)

A process that exhibits only common cause variation is said to be in control or stable

A process is said to be out of control when it exhibits assignable variationExamples: less experienced worker has

replaced an experienced worker, machine malfunctioning, change of machine settings

Common Cause & Assignable Causes ( A Game)

Writing “R” with right hand (one line) Writing “R” with left hand (one line)

Common Cause and Assignable Cause Variation

Natural and Assignable Variation

Process Control: Three Types of Process Outputs

Relationship Between Population and Sampling Distribution

Control Charts

A control chart is a time ordered plot of sample statistics Sometimes called “the voice of the process” Graphical display of a quality characteristics (for example, level of

beer in each bottle in a bottling plant) Distinguish between random and non-random variability Chart contains a center line and two limits

Upper control limit Lower control limit

If the process is in control, all sample points will fall between them As long as points fall within control limits – the process is in

statistical control However, any point outside limits – investigate the assignable

causes

Control Charts

If all the points plot inside the limits, but behave in a nonrandom manner – indication that process is out of control and needs investigation

A Control Chart

In Statistical Control

A process that is operating with only chance cause of variation present is said to be in statistical control

If the process is in control, all the plotted points should have an essentially random pattern

Reasons for Popularity of Control Charts

Proven technique for improving productivity

Effective in defect prevention Prevents unnecessary process adjustment Provides diagnostic information Provides information about process

capability

Statistical Process Control Tools

Control Charts for variables (Characteristics that are expressed on a numerical scale: density, weight, diameter, resistance, length, time, volume) X-bar Chart and R-Chart

X-bar chart for process average R-chart for process variability

Control Charts for attributes (characteristic that can’t be measured on a numerical scale: smell of cologne acceptable or not acceptable, color of a fabric acceptable or not) p-chart and c-chart

p-charts for percent defective in a sample c-charts for counts (e.g. # of defects)

SPC Tools

Control Charts for variables (X-chart, R-Chart)

Variables data are measured on continuous scale

Length Width Weight Voltage Viscosity Amount of time needed to complete a task

Mean Control Chart (x-bar chart) A mean control chart or x-bar chart can be

computed in one of the two ways. Choice depends on what information is

available If process standard (σ) is known from past

experience or historical data

Mean Control Chart (x-bar chart)

Mean Control Chart (x-bar chart) If the process standard deviation is not known, a

second approach is to use the sample range as a measure of process variability. The appropriate formulas for control limits are

R-Chart Control Limits

D3, D4 = constants that provide 3 standard deviations (3D3, D4 = constants that provide 3 standard deviations (3σσ) limits ) limits for a given sample sizefor a given sample size

X-bar Chart Limits

A2 = constant to provide three sigma limits for the sample meanA2 = constant to provide three sigma limits for the sample mean

Steps in developing X-bar and R-chart Collect data on the variable measured (time, weight,

diameter). Collect at least 20-25 samples randomly. Sample size should be of 4 to 5 units.

Compute range for each sample, and average R-bar Calculate the UCL and LCL Plot the sample ranges. If all are in control process, Calculate UCL and LCL for x-bar chart Plot the sample means. If all are in control, process is in

statistical control.

Control Limits are Based on Sampling Distribution

Zones for Identification of Nonrandom Pattern

Control Chart Patterns

Pattern Recognition in Control Charts Recognizing non-random patterns on the control

chartOne point plots outside 3σ limitsTwo or three consecutive points plot beyond

2σ limitsFour out of 5 consecutive points plot at a

distance of 1σ or beyond from the centre lineEight consecutive points on one side of centre

p-chart

Control charts for attributes p-chart measures % defective items or proportion defective

items in a sample

Total # defects from all samples p-bar = ----------------------------------------

# samples × Sample size Appropriate when data consists of two categories of items

Good or bad, pass or fail Examples: # bad light bulbs and good light bulbs in a given

lot # of bad glass bottles and good glass bottles

P-chart Limits

c-chart

Appropriate when number of defects are counted because not possible to compute proportion defective

Examples Number of accidents per day Number of crimes committed in a month Blemishes on a desk Complaints in a day Typo errors in a chapter of the text book # customer invoice errors

C-chart Limits

C-bar = average no. of defects per unit = Total number of defects No of samples

Process Capability

Specifications: A range of values imposed by designers of the product or service based on customer requirements

Control limits and based on production process, and they reflect process variability

Process variability: Natural or inherent variability in a process due to randomness

Process capability: The inherent variability of process output relative to the variation allowed by the design specifications

Measures of Process Capability

Measures of Process Capability Process Capability Ratio Process Capability Index

Process Capability Ratio

Cp = (Upper Spec – Lower Spec) / 6σ

If Cp < 1, process range > tolerance range Process not capable of producing within design

specifications If Cp = 1, Tolerance range and process range are same If Cp > 1, Tolerance range > process range

A desirable situation Ideally Cp > 1.33

Process Capability

Cp does not take into account where the process mean is located relative to the specifications

Cp simply measures the spread of the specifications relative to the six sigma spread in the process

Process Capability Index

Generally, if Cp = Cpk, the process is centered at the midpoint of the specifications

When Cpk < Cp, the process is off center

Process Shifted Downward from Centre

Process Capability (Sequential Steps)

1. Calculate Cpk to check centrality

2. Calculate Cp to check whether the process variation are within design specifications

SBI, Fortune Towers, BBSR Process Standards

Process standards Encashment of cheque: 5 minutes (after reaching

counter) Receipt of cash: 3 minutes Issue of Demand Draft: 10 minutes Issue cheque book: max 7 days Opening of bank account: 10 minutes Issue of duplicate card/PIN – 7 working days Issue of welcome kit: 8 days

Problem Solving

1st order problem solvingPatch workingCommon in industries

Problems recur

2nd order problem solvingFixing the root causesRare in industries

SPC – Honda America

Deming Wheel(P-D-C-A)

Six Sigma(DMAIC Model)

Define - Define the project Measure – How the process is functioning

currently Analyze – What factors affect the process Improve – By redesigning the process Control – Develop mechanisms to make

sure that problem stays fixed over long run

Six Sigma MethodologyDefine

Measure

AnalyzeImprove

Control

Breakthrough vs. Continuous Improvement

7 – Basic SPC Tools Used in Process Improvement

Check Sheet Scatter diagram Histogram Pareto Chart Flow Chart Run chart Fish-bone diagram or Cause-and Effect

diagram

Example – Summarized Data(Airlines Performance)

Check SheetCauses January February March April

Lost Luggage / /// // ////

Departure Delay

// /// //// ////

Mechanical /// /// ////

Overbooked /// / //

Pareto Chart

Pareto (Continued)

Pareto Chart (Hotel)

101214161820

Wanted n

on-smoking

ng typ

e of bed

Room not pr

operly

equippe

Other, n

ot cod

Noisy lo

Room not cleane

Plumbing not w

orking

Didn't lik

e view

Pareto Chart (Restaurant)Pareto Chart

01020304050

Slow S

Discour

Dinner

Defect Name

Histogram

Run Chart

Scatter Diagram

Fishbone Diagram

Flow Chart

Productivity and Quality

Productivity can be improved by improving quality if the improved quality is the result of reducing the amount of rework or repair to the product or service. Improving productivity through improved

quality means that products and services must be right the first time without increasing the input part of the equation.

Productivity

Productivity is a measure of a company’s effectiveness in converting inputs into outputs

Productivity = Output / Input

Yield: A Measure of ProductivityProduct Yield is a measure of output as an indicator of productivity. It can be calculated for the entire production process

Manufacturing Cost per Good Product

Manufacturing Cost per Product

Yield: Production with n Stages

Quality-Productivity Ratio (QPR)

Summary

SERVQUAL MODEL or GAP Model

Model that has been extensively used to measure service quality (Parasuraman, Zeithaml, & Berry, 1985) Banks Insurance Education Information Technology

Model: The level of service quality experienced by the customer is critically determined by the gap between a customer’s expectation of service and the perception of service that is delivered.

SERVQUAL MODEL

Service quality is a complex topic as it needs 5 dimensions for its definition

Model proposes 5 broad dimensions Reliability Responsiveness Assurance Empathy Tangibles

Service Quality Dimensionsin US (Level of Importance) Zeithaml, Parasuraman and Berry asked 1,900

customers of 5 nationally known companies to allocate 100 points across the five service quality dimensions: Reliability: 32% Responsiveness: 22% Assurance: 19% Empathy: 16% Tangibles: 11%

SectorSector Most ImportantMost Important Least Least ImportantImportant

BankingBanking ReliabilityReliability,, ResponsivenessResponsiveness

TangiblesTangibles

InsuranceInsurance All treated equalAll treated equal

HotelHotel ReliabilityReliability, Tangibles, , Tangibles, ResponsivenessResponsiveness

RestaurantRestaurant All treated equalAll treated equal

HealthcareHealthcare Reliability,Reliability, ResponsivenessResponsiveness

TangiblesTangibles

EducationEducation Empathy, Tangibles, Empathy, Tangibles, ReliabilityReliability

Recent Research Findings on SERVQUAL in Indian Service Sector – A 2008 study

Service Quality Model

Service Quality

If actual performance < customer’s expectation: poor quality

If actual performance = customer’s expectation: satisfactory quality

If actual performance > customer’s expectation: high quality

Gap Analysis

Project Management

What is a Project?

A project can be defined as a set of interrelated activities necessary to achieve established goals using a specified amount of time, budget, and resource

Primary Characteristics of a Project Unique (something that has not been done

before) A well-defined goal Composed of a set of interrelated activities A specified beginning and ending time Specified resource and personnel requirements A specified budget

PMBOK’s Definition

Project Management Body of Knowledge (PMBOK) guide by Project Management Institute (PMI), USA defines project as

“A temporary endeavor undertaken to create a unique product or service”.

1. What is Project Management? The planning, organising, monitoring and

controlling of all aspects of a project and the motivation of all involved to achieve the project objectives safely and within agreed time, cost and performance criteria. The project manager is the single point of responsibility for achieving this

Association of Project Management, UK

PMBOK Guide Definition of Project Management The application of knowledge, skills tools

and techniques to project activities in order to meet stakeholder’s need and expectations from a project

2. How Project is Different from General Operations Management? All work can be described as fitting two types

Projects Non- routine project such as mergers Routine such as building a house Limited time frame Narrow focus, specific objectives Less bureaucratic

Operations Ongoing work needed to ensure that an organization

continues to function effectively (usually repetitive)

Few Examples of Projects

Building a bridge or dam Constructing a house Writing a software for a client (say, ERP) Organizing an event

Sports, quiz competition Convocation ceremony Marriage

Making a commercial movie Hosting Olympic games

3. Why is it used?

Special needs that don’t lend themselves to functional management

Pressure for new products, new services

Project Life Cycle

4. What are the Key Metrics in Project Management (Iron Triangle)

Why Do Projects Fail?

Critical FactorsChange in initial project expectationsChange in the overall project importance to

the organizationChange in the need for the project by the

organizationChange in overall complexityChange in overall time to completion

Why Do Projects Fail?

Critical Factors Change in user needs Change in overall project resources Change in technical difficulties Change in funding source Change in regulatory problems Internal politics within the organization External politics to the organization Change in commitment by project champion

Source: Dilts and Pence, JOM, 24(4), 2006

How to Successfully FAIL in a Project Ignore the project environment (including

stakeholders) Push a new technology to market too quickly Don’t bother building a fall-back option When problems occur, shoot the one most

visible Let new ideas starve to death from inertia Don’t bother conducting feasibility studies

How to Successfully FAIL in a Project Never admit that a project is a failure Over manage project managers and their teams Never, never conduct post failure analysis Allow political expediency and infighting to dictate project

decisions Make sure that the project is run by a weak leader

Source: Pinto and Kharbanda, 1996

5. What are the Key Success Factors?

Top-down commitment A respected and capable project manager Skilled and appropriate team members Adequate funding Enough time to plan Careful tracking and control Good communications

The Project Manager

Bears the ultimate responsibility for the success or failure of the project. The person is responsible for the following Work achieved in desired sequence Managing a motivated work force Communicate effectively Ensure quality so that performance objectives are

realized Time (project is completed on time) Costs (project is completed within budget)

6. What are the Main Tools

Work breakdown structure Gantt Chart Network diagram Risk management analysis

Matrix Project Organization Structure

President

Research andDevelopment

Engineering Manufacturing Marketing

ManagerProject A

ManagerProject B

ManagerProject C

Structuring Projects Matrix: Advantages

Enhanced communications between functional areas

Duplication of resources is minimized

Functional “home” for team members

Policies of the parent organization are followed

Structuring Projects Matrix: Disadvantages

Too many bosses

Depends on project manager’s negotiating skills

Potential for sub-optimization

Project Management Process

Project Planning encompasses three major activities

A. Planning

B. Scheduling

C. Control

A. Project Planning

B. Project Scheduling

C. Project Control

Work Breakdown Structure

Work Breakdown Structure (Example)

Program

Project 1 Project 2

Task 1.1

Subtask 1.1.1

Work Package 1.1.1.1

Task 1.2

Subtask 1.1.2

Work Package 1.1.1.2

A work breakdown structure defines the hierarchy of project tasks, subtasks, and work packages

Planning and Scheduling (Gantt Chart)

Provides a visual display of project schedule, when activities are scheduled to start, when they will be finished, and where extra time is available and activities can be delayed. The project manager can use the chart to monitor the progress of the activities and see which ones are ahead of schedule and which one are behind schedule.

Gantt Chart

Activity 1Activity 2Activity 3Activity 4Activity 5Activity 6

Vertical Axis: Always Activities or Jobs

Horizontal Axis: Always TimeHorizontal Axis: Always Time

Horizontal bars used to denote length of time for each activity or job.Horizontal bars used to denote length of time for each activity or job.

Gantt Chart

Prerequisites for Critical Path Methodology

A project must have:

well-defined jobs or tasks whose completion marks the end of the project;

independent jobs or tasks;

and tasks that follow a given sequence.

Types of Critical Path Methods

CPM with a Single Time Estimate Used when activity times are known with certainty Used to determine timing estimates for the project,

each activity in the project, and slack time for activities

CPM with Three Activity Time Estimates Used when activity times are uncertain Used to obtain the same information as the Single

Time Estimate model and probability information Time-Cost Models

Used when cost trade-off information is a major consideration in planning

Used to determine the least cost in reducing total project time

Steps in the CPM with Single Time

Estimate 1. Activity Identification 2. Activity Sequencing and Network

Construction 3. Determine the critical path

From the critical path all of the project and activity timing information can be obtained

Two Approaches to Develop Project Network

Activity-on-node (AON)Node to depict an activity

Activity on arrow (AOA)Arrow to depict an activity

Planning and Scheduling(PERT & CPM)

Probability of Completing a Project using Standard Normal Distribution

Time-Cost Trade-Offs Crashing

Crashing of Project

Risk Management

Risk MatrixEvent Probability Cost

1 0.85 $18

2 0.30 20

3 0.55 68

4 0.85 77

5 0.10 30

6 0.30 87

Risk Matrix

Probability of Occurring

0 1.00

Why do Projects Succeed

Strong project leadership Focus on meeting three constraints: scope, time, and budget Develop clear and measurable project goals Roles and responsibilities of each member should be clearly

defined The project execution strategy and implementation plan should

be well defined and clear to all stakeholders Project team members should have a sense of urgency about

the execution of the project All project deliverables and all project activities must be

visualized and communicated in detail to all team members and the stakeholders

Simulation

What is simulation?

It generally refers to using a computer program to perform experiments on a model of a real system In other words, it is a computer model that

imitates a real-life situation

It enables a decision maker to evaluate the behavior of a model under various conditions or scenarios

Monte Carlo Process

A technique for selecting numbers randomly from a probability distribution

Stated differently, it is a probabilistic simulation technique used when the process has a random component

The Process of Simulation

Probability Distribution of Demand for PCs

PCs demanded per week

Frequency of demand Probability of demand, P(x)

0 20 0.20

1 40 0.40

2 20 0.20

3 10 0.10

4 10 0.10

100 1.00

A Roulette Wheel for Demand

Numbered Roulette Wheel

Monte Carlo ProcessUse of Random Numbers (5 of 10)

Process of spinning a wheel can be replicated using random Process of spinning a wheel can be replicated using random numbers alone.numbers alone.

Transfer random numbers for each demand value from roulette Transfer random numbers for each demand value from roulette wheel to a table.wheel to a table.

Randomly Generated Demand for 15 weeks

Week r Demand, x Revenue

1 39 1 4,300

2 73 2 8,600

3 72 2 8,600

4 75 2 8,600

5 37 1 4,300

6 2 0 0

7 87 3 12,900

8 98 4 17,200

9 10 0 0

10 47 1 4,300

11 93 4 17,200

12 21 1 4,300

13 95 4 17,200

14 97 4 17,200

15 69 2 8,600

Σ=31 1,33,300

Estimated Average Weekly Demand Estimated average weekly demand =

31/15 = 2.05 PCs per week Estimated average revenue = 133,300 /15

= 8,866.67

Estimated average demand analytically From probability distribution, P(x):

E(x) = ΣP(xi)x

Where, Xi = demand value i

P(xi) = probability of demand

n = the number of different demand values

E(x) = 0.20*0+0.40*1+0.20*2+0.10*3+0.10*4 = 1.5 PCs per week

Problem

Machine shop breakdown

Cumulative Frequencies for BreakdownsNumber of breakdowns

Frequency Relative frequency

Cum Frequency

0 10 0.10 0.10

1 30 0.30 0.40

2 25 0.25 0.65

3 20 0.20 0.85

4 10 0.10 0.95

5 5 0.05 1.00

100 1.00

Assigning Random Numbers to Cumulative FrequenciesNumber of breakdowns

Frequency Probability Cum Prob. Corresponding Random Nos.

0 10 0.10 0.10 01 to 10

1 30 0.30 0.40 11 to 40

2 25 0.25 0.65 41-65

3 20 0.20 0.85 66-85

4 10 0.10 0.95 86-95

5 5 0.05 1.00 96 to 00

100 1.00

Summary of Results

Day RN Simulated Breakdowns

1 18 1

2 25 1

3 73 3

4 12 1

5 54 2

6 96 5

7 23 1

8 31 1

9 45 2

10 01 0

Advantages of simulation

Developing the model of a system often leads to a better understanding of the real system

Years of experience in the real system can be compressed into seconds or minutes

Does not disrupt ongoing activities of the real system

Can be applied to situations where standard mathematical analysis are difficult to apply

Advantages of Simulation

Recent advances in software make some simulation models very easy to develop

Allows questions of what-if?

Disadvantages of simulation

Although a great deal of time and effort may be spent to develop a model for simulation, there is no guarantee that the model will provide optimal solutions.

It merely indicates an approximate behavior for a given set of inputs Two reasons

By design there is inherent randomness in simulation Simulations are based on models and models are only approximations of

reality

Building complicated systems can be costly and time consuming Simulation may be less accurate than a mathematical analysis

because it is randomly based. If a given system can be represented by a mathematical model, it may be better to use simulation

Simulation Languages

Simscript III GPSS/H FLEXSIM EXTENDSIM SLAM II ARENA SIMUL8

Total Productive Maintenance

Effects of Poor Maintenance

Expensive and harmful Fixing major machines is costly Production is lost due to machine

breakdowns Breakdown reduces capacity May produce defective parts Workers are idle when machines break

Causes of Machine Failure

Irregular and inadequate preventive maintenance leads to deterioration of machines and ultimately their failure

Overusing at excessive speeds exceeding their specified limits reduces life of the m/c

Improper cleaning leads to accumulation of dirt, oil etc. on machine parts leads to corrosion and erosion

Causes of Machine Failure

Inadequate maintenance may lead to loosening of parts causing accidents

Incorrect machine set up or loading parts beyond capacity (i.e. taking excessive cuts) may lead to machine breakdown

Focus of Total Productive Maintenance (TPM) Eliminating causes of machine failure Maximizing effectiveness of machine

throughout its entire life Involves everyone in all departments and

at all levels TPM develops a maintenance system

9. Total Productive Maintenance (TPM) Is an alternative approach to equipment maintenance

that seeks to achieve zero breakdowns and zero defects. It is based on the premise that production operators

play a crucial role in maintenance Emphasizes proactive and preventive maintenance to

maximize the operational efficiency of the equipment Central to the TPM philosophy is the concept of Overall

Equipment Effectiveness (OEE) OEE measures performance of TPM

TPM seeks to maximize OEE

Overall Equipment Effectiveness(OEE) OEE =

Availability Rate * Performance Rate * Quality Rate

OEE captures six big losses which result in reduced effectiveness of using an equipment

Availability: % of scheduled time that the operation is available to operate. Often referred to as Uptime.

Performance: Speed at which the work centre runs as a % of designed speed

Quality: Good units produced as a % of total units produced

Can be applied to any individual work centre or rolled up to department or plant levels

OEE Diagram

Class Exercise

TPM Methodology

TPM aims to maximize the OEE in an organization through several methods. Some of the important elements of TPM include:

Establishing a thorough system of preventive maintenance for the equipment’s entire life span

Involvement of TPM by various departments

TPM Methodology

Involvement of every single employee from top management to workers on shop floor

Promoting preventive maintenance through a system of motivation management by creating autonomous small group activities for maintenance

TPM- Examples

Hindustan Lever implemented TPM in six factories and reported 30% improvement in product defect control and 20% gain in productivity

Hindalco reduced breakdown time from 1.12 hours/day to 0.15 hour/day

L&T improved OEE from 30% to 70% Marico improved OEE from 45% to 71%

Overall Equipment Effectiveness OEE = Availability × Performance × Quality

TEEP (Total Effective Equipment Performance)

= Loading × OEE

Loading = Scheduled Time / Calendar Time Work center runs 5 days/week, 24 hrs per day Loading = 5 days × 24 / 7days ×24 = 71.4%

Availability = Available Time / Scheduled Time Work center scheduled to run 8 hour shift (480 min) Work center experiences: 30 min scheduled break

and 60 minutes unscheduled break Availability = 390/450 = 87%

Performance = (Parts produced * Ideal Cycle time) / Available timeWork center is scheduled to run 8 hours with

a 30 min scheduled breakAvailable time = 450 – 60 (unscheduled

break) = 390 minutesStandard rate of production is 40 units/hour or

1.5 minutes per unit

The work center produces 242 units/shift This 242 units is total units , not good units Time to produce 242 units = 242×1.5 =

363 minutes Performance = 363/390 = 93%

Quality = Good Units/Units producedA work center produces 230 good units230 good units/242 units produced = 95%

OEE = Availability × Performance × Quality = 86.7%×93%×95% = 76.6%

TEEP = Loading × OEE= 71.4%×76.6 = 54.69%