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Operations Management - II Manimay Ghosh, Ph.D.
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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
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,
coins
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
A
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
R
TimeL
QInventory on hand
Demand Rate
Avg. Inventory (Q/2)
Reorder Pt.
Order PlacedOrder Receipt
L = Lead TimeR = Reorder Point
Time
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.
Q2H D
QS=
Q Model
Q opt=
2DS
H
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
weeks
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
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
© 2004 by Prentice Hall, Inc., Upper Saddle River, N.J. 07458 12-72
Probabilistic Models - When to Order?
Reorder Point
(ROP)
X
Safety Stock (SS)
Time
Inve
nto
ry L
eve
l
Lead Time
SSROP
Service Level P(Stockout)
Place order
Receive order
Fre
qu
en
cy
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
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
year)
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
Case
Zhou Bicycle Company
Fixed Time Period Model
Material Requirements Planning (MRP)
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
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
X:
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
L4L
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
161.5
137.8
190.3
128.8
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
firm
“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
Ad
just
mas
ter
sch
edu
leA
dju
st m
aste
r sc
hed
ule
An Overview of MRP II
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
2583
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.
Steps in Aggregate Planning
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)
Steps in Aggregate Planning
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
Strategies for Meeting Demand
Proactive strategies Influencing Demand
Offer discounts and promotions
Increase advertising in slack periods
Counter seasonal products Lawnmowers (summer) and snow-blowers (winter)
Strategies for Meeting Demand
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 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
Scheduling
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
Classroom Schedule Chart
Gantt Progress ChartGantt Progress Chart
Plymouth
Ford
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
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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
A 6 8
B 2 6
C 8 18
D 3 15
E 9 23
FCFS Job Seq(1)
Proc Time (days)
(2)
Flow Time (days)
(3)
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
(3-4)
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
18 1
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
(3-4)
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)
A 5 2
B 3 6
C 8 4
D 10 7
E 7 12
Johnson’s Rule
A
B A
B C A
B E D C A
1.
2.
3.
4.
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 – 3 work centres
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 centres
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.
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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 A
Job B
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
Case
Old Oregon Wood Store
Video
Scheduling – United Airlines
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
5%
Moving and WaitingTime in factory
Time on m/c
30% 70%
Cutting Loading, positioning,gauging
95%
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
pay
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
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
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
Toyota Production System
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
T T T
MM M T
M
SG CG CG
SG
D D D
D
T T T CG CG
T T T SG SG
M M D D D
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)
Video
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
OEE
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
OEE
Can be applied to any individual work centre or rolled up to department or plant levels
OEE
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
Toyota Production System
Multiple explanations for Toyota’s success:Elimination of wasteUsing specific tools for production (SMED,
Poka Yoke)Design Rules
TPS
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
Time
Imp
rove
me
nt
Backslide
Backslide
“Actual”
If worked to the new standards
Innovate
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?
Video
Gortrac – Process Improvement2
Video
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
many
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
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
line
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
Process Capability
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
Video
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)
02468
101214161820
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Wro
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Room not pr
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Room not cleane
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Pareto Chart (Restaurant)Pareto Chart
01020304050
Slow S
ervic
e
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Table
s
Discour
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Smok
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Cold
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Defect Name
De
fec
ts
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)
Time
Cost
Scope
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
Level
1
2
3
4
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
Time
Vertical Axis: Always Activities or Jobs
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)
Planning and Scheduling(PERT & CPM)
PERT
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
Cost3
4
0 1.00
25
50
100
1
5
2
6
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
556
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
17
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
OEE
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
OEE
Can be applied to any individual work centre or rolled up to department or plant levels
OEE
OEE Diagram
OEE
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
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%
OEE
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
OEE
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%
OEE
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%
