MRP, MPS, Bill of Material, Numericals
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Transcript of MRP, MPS, Bill of Material, Numericals
![Page 1: MRP, MPS, Bill of Material, Numericals](https://reader036.fdocuments.in/reader036/viewer/2022082202/58e796ca1a28abc52e8b59ed/html5/thumbnails/1.jpg)
MANAGING PRODUCTION ACROSS THE SUPPLY CHAIN
&LOGISTICS NUMERICAL
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THE BIG PICTURE
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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
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MASTER SCHEDULING CRITERIA
The Master Production Schedule must:
Satisfy the needs of sales/marketing
Be feasible for operations
Match with supply chain capability
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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
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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
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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.
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MRP & JOB SEQUENCING
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We’ve scheduled 500 chairs to be ready five weeks from now . . .
. . . Now what?
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Back supports (3)
Side rails (2)
Front legs (2)
Cross bars (2)
Seat
MATERIAL NEEDED FOR A CHAIR
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CHAIR STRUCTURE TREE(“BILL OF MATERIALS” OR BOM)
Chair
LegAssembly
Seat Back Assembly
Legs (2) Crossbar
Siderails (2)
Crossbar
BackSupports
(3)
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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
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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
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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
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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
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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.
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OTHER CONSIDERATIONS I
Planned Orders
Feedback Feedback
Production Suppliers
MRP
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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
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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
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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
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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
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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
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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
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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
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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
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LOGISTICS NUMERICALS
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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
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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.
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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.
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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.
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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
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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.
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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.
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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.
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Based on these criteria, the three Alternative sites were scored between 0 and 100 points:
Scoring model Example (cont.)
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Weights of each factor have been assigned as follows:
Scoring model Example (cont.)
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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.
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NETWORK MODELS
Electronic maps of road networks allow another approach to location, which is based on actual road layouts.
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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.
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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?
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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
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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
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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
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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