MANAGING PRODUCTION ACROSS THE SUPPLY CHAIN

&LOGISTICS NUMERICAL

THE BIG PICTURE

MASTER SCHEDULING Controls the timing and quantity of production for

products or product families Primary interface point for actual customer orders Coordinates forecasted demand and actual orders

with production activity Serves as tool for agreement between marketing

and operations (but at a different level than S&OP) Feeds data to more detailed material planning Indicates the quantity and timing (i.e., delivery

times) for a product or group of products

MASTER SCHEDULING CRITERIA

The Master Production Schedule must:

Satisfy the needs of sales/marketing

Be feasible for operations

Match with supply chain capability

DETAILED MPS FOR A PRODUCT

On-hand inventory at end of October = 100

Month November DecemberWeek 45 46 47 48 49 50 51 52Forecast Demand 150 150 150 150 125 125 125 125Orders Booked 170 165 140 120 85 45 20 0Master Schedule 300 0 300 0 250 0 250 0

Calculate the projected on hand inventory

PROJECTED ON-HAND INVENTORY

On-hand inventory at end of October = 100

Month November DecemberWeek 45 46 47 48 49 50 51 52Forecast Demand 150 150 150 150 125 125 125 125Orders Booked 170 165 140 120 85 45 20 0Projected On-Hand

Inventory 230 65 215 65 190 65 190 65Master Schedule 300 0 300 0 250 0 250 0

e.g., Projected on-hand inventory for week 47: = 65 + 300 – 150 = 215

PLANNING HORIZONHow far an MPS looks into the future

depends on Variability in demand and market

conditions Variability in supplier deliveries and

lead times Length of the production process.

MRP & JOB SEQUENCING

We’ve scheduled 500 chairs to be ready five weeks from now . . .

. . . Now what?

Back supports (3)

Side rails (2)

Front legs (2)

Cross bars (2)

Seat

MATERIAL NEEDED FOR A CHAIR

CHAIR STRUCTURE TREE(“BILL OF MATERIALS” OR BOM)

Chair

LegAssembly

Seat Back Assembly

Legs (2) Crossbar

Siderails (2)

Crossbar

BackSupports

(3)

ChairAssembly

(1 week)

Week 5Week 4

If final assembly takes one week, then we must startthe assembly at the beginningof Week 4 . . .

LEAD-TIME I

ChairAssembly

BackAssembly

LegAssembly

(1 week)

(1 week)

(1 week)

Seats (2 weeks)

Week 5Week 4Week 3Week 2Whichmeans thatthe majorsubassembliesand seats must bedone by thebeginningof Week 4 ...

LEAD-TIME II

ChairAssembly

BackAssembly

LegAssembly

(1 week)

(1 week)

(1 week)

Back Support (2 weeks)

Legs (2 weeks)

Side Rails (2 weeks)

Cross Bar (2 weeks)

Cross Bar (2 weeks)

Seats (2 weeks)

Week 5Week 4Week 3Week 2Week 1

LEAD-TIME III

LEAD-TIME KEY POINTS To have finished chairs at the

beginning of Week 5 with no work in progress, we must begin production and order materials in Week 1.

“Exploding” the bill of materials tells us when to order things.

Not much we can do to adjust output of chairs for the next 4 weeks

MATERIAL REQUIREMENTS PLANNING (MRP)

Requires:1. Bill-of-Materials (BOM)2. Inventory record3. Master schedule

to determine what should be ordered when, and how much to order.

OTHER CONSIDERATIONS I

Planned Orders

Feedback Feedback

Production Suppliers

MRP

OTHER CONSIDERATIONS II

When do we update the system? Capacity requirements planning using

MRP output MRP ‘nervousness’

Increasing order chaos, the lower in the BOM structure of materials

Lot sizing issues

JOB SEQUENCING Rules:

FCFS — first come, first served EDD — earliest due date Critical ratio — work time remaining

divided by days left before due date Performance measure:

Average lateness — sum of days late for each job divided by total number of jobs

EXAMPLE DATA

Job Estimated Time

Days Until Due

Critical Ratio

Weldco 8 32 0.250

MetroArt 10 20 0.500

MMCC 9 9 1.000

Jones 6 15 0.400

EXAMPLE FCFS

Job Estimated Time

Days Until Due

Start End Days Late

Weldco 8 32 0 8 0

MetroArt 10 20 8 18 0

MMCC 9 9 18 27 18

Jones 6 15 27 33 18

Average lateness = 36/4 = 9 days

EXAMPLE EARLIEST DUE DATE

Job Estimated Time

Days Until Due

Start End Days Late

MMCC 9 9 0 9 0

Jones 6 15 9 15 0

MetroArt 10 20 15 25 5

Weldco 8 32 25 33 1

Average lateness = 6/4 = 1.5 days

EXAMPLE CRITICAL RATIO(LARGEST RATIO FIRST)

Job Estimated Time

Days Until Due

Start End Days Late

MMCC 9 9 0 9 0

MetroArt 10 20 9 19 0

Jones 6 15 19 25 10

Weldco 8 32 25 33 1

Average lateness = 11/4 = 2.75 days

DISTRIBUTION REQUIREMENTS PLANNING (DRP)

Anticipates downstream demand Uses this information, not

predetermined reorder points or periodic reviews, to determine when to order

Computer-based software systems needed to deal with the added complexity

DRP BENEFITS

Helps improve customer service

Provides a better and faster understanding of the impact of shortages and/or promotions

Helps reduce costs Inventory Freight Production

Provides integration between the stages in the supply chain

LOGISTICS NUMERICALS

SCORING MODELS

Scoring models emphasize the factors that are important for locations, but which cannot easily be costed or quantified.

The important factors in location decisions

Mostly use scoring model in facility / warehouse and transportation decisions

SCORING MODELS - FACTORS IN LOCATION DECISIONS In the region and country

● availability, skills and productivity of workforce● local and national government policies, regulations, grants

and attitudes● political stability● economic strength and trends● climate and attractiveness of locations● quality of life – including health, education, welfare and

culture● location of major suppliers and markets● infrastructure – particularly transport and communications● culture and attitudes of people.

SCORING MODELS - FACTORS IN LOCATION DECISIONS

In the city or area

● population and population trends● availability of sites and development issues● number, size and location of competitors● local regulations and restrictions on operations● community feelings● local services, including transport and utilities.

SCORING MODELS - FACTORS IN LOCATION DECISIONS

In the site

● amount and type of passing traffic● ease of access and parking● access to public transport● organizations working nearby● total costs of the site● potential for expansion or changes.

IMPORTANT FACTORS FOR SCORING MODELS

availability of a workforce with appropriate skills labor relations and community attitudes environment and quality of life for employees closeness of suppliers and services quality of infrastructure government policies toward industry.

When decision maker want the facility near to raw material

IMPORTANT FACTORS FOR SCORING MODELSConcerning with customers, decisions about location put

more weight on:

population density socio-economic characteristics of the nearby

population location of competitors and other services location of other attractions such as retail shops convenience for passing traffic and public transport ease of access and convenient parking visibility of site.

SCORING MODELS THE BASIS OF SCORING MODELS,Five steps:Step 1 decide the relevant factors in a decision

Step 2 give each factor a maximum possible score that shows its importance

(usually 0-100) and weight for each factor (0.00-1.00)

Step 3 consider each location in turn and give an actual score for each factor, up

to this maximum

Step 4 add the total weighted score (= Site Score x Factor Weight) for each

location and find the highest

Step 5 discuss the result and make a final decision.

SCORING MODEL EXAMPLE

Samson Ltd. is considering three alternative sites for its new facility.

After evaluating the firm’s needs, the Managers have narrowed the list of important Selection Criteria down into three major factors.

- Availability of skilled labor- Availability of Raw materials, and- Proximity to the firm’s markets.

Based on these criteria, the three Alternative sites were scored between 0 and 100 points:

Scoring model Example (cont.)

Weights of each factor have been assigned as follows:

Scoring model Example (cont.)

FACTOR FactorWeight

(Total=1)

Site A Site B Site C

Score Weighted Score

Score Weighted Score

Score Weighted Score

Skilled labor 0.5 70 35 70 35 50 25

Raw materials 0.3 60 18 40 12 90 27

Market Prox. 0.2 70 14 95 19 60 13

Total Weighted Score 67 66 64

Scoring model Example (cont.)Now we will multiply each score by its corresponding

factor weightWeighted scores are calculated as: (Site Score) x (Factor

Weight)

From these results, the largest total weight is for Site A. It appears to be the best location.

NETWORK MODELS

Electronic maps of road networks allow another approach to location, which is based on actual road layouts.

SINGLE MEDIAN PROBLEM

Finds the location of one facility on a network that minimize total cost is called the single median problem

The easiest way to find the single median

- Starts with a matrix of the shortest distances between towns.

- To find the shortest average distance, we have to combine these distances with the loads carried.

EXAMPLE

Ian Bruce delivers goods to eight towns, with locations and demands as shown in next slide. He wants to find the location for a logistics centre that minimizes the average delivery time to these towns. Where should he start looking?

HT

AL

FR

10

CP

BEDI15 GO

EN

15

25

20

10

10

1520

22

9 8

14

56

6

7

Distance between AL and CP

Facility CP

Demand at CP

Map of Ian Bruce’s problem

Single median problem – Example (cont.)

8

HT

AL

FR

10

CP

BEDI15 GO

EN

15

25

20

10

10

1520

22

9 8

14

56

6

7

Map of Ian Bruce’s problem

Single median problem – Example (cont.)

8

Ways from AL to ENRED= 15+9+7= 31

HT

AL

FR

10

CP

BEDI15 GO

EN

15

25

20

10

10

1520

22

9 8

14

56

6

7

Map of Ian Bruce’s problem

Single median problem – Example (cont.)

8

Ways from AL to ENRED= 15+9+7= 31 GREEN= 15+8+6+6= 35

HT

AL

FR

10

CP

BEDI15 GO

EN

15

25

20

10

10

1520

22

9 8

14

56

6

7

Map of Ian Bruce’s problem

Single median problem – Example (cont.)

8

Ways from AL to ENRED= 15+9+7= 31 (smallest)GREEN= 15+8+6+6= 35YELLOW= 22+6+6= 34