lecture 28
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© J. Christopher Beck 2005 1
Lecture 28: Supply Chain Scheduling 2
© J. Christopher Beck 2005 2
Outline Discrete Manufacturing vs
Continuous Manufacturing What Difference Does It Make?
A Typical Framework for Supply Chain Optimization Medium Term Planning Short Term Scheduling Information System Issues
© J. Christopher Beck 2005 3
Supply Chain Scheduling
© J. Christopher Beck 2005 4
Discrete vs. Continuous Manufacturing
Continuous (process) production Main inventory/products are finely
divisible Steel, shampoo, paper
Discrete production Main inventory/products are individually
countable Cars, computers, consumer electronics
Scheduling problems are different
© J. Christopher Beck 2005 5
Continuous:1. Main Processing
Raw materials aretransformed to intermediate products
Machines have high start-up/shutdown costs and
High changeover costs Often fixed batch sizes Usually run 24/7
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Continuous:2. Finishing
Products of mainprocesses are “specialized” Cut, bent, extruded, painted, printed, …
Often these are commodities Many clients Mix of make-to-stock, make-to-order
Due dates, sequence dependent changeovers, and inventory management are important
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Discrete:1. Primary Conversion
Like finishing in continuous Stamping, bending, cutting
Process is generally pretty simple
Output is often a part Car body part, computer case, …
Schedule is often integrated with downstream processes
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Discrete:2. Main Production
Many differentoperations of many tools 100 step process for semiconductors!
Machines are very expensive Often organized like a job shop Each order has its own route,
quantity, due date Sequence dependent changeovers
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Discrete:3. Assembly
Put together parts Machines are cheap but material
handling is important Assembly lines
cars or consumer electronics Due dates, changeovers,
sequencing, …
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Table 8.1
Segment Process Horizon Clock Speed
Differentiation
Continuous: Main
Planning Long-medium
Low Very low
Continuous: Finishing
Planning/scheduling
Medium-short
Medium/High
Medium/low
Discrete: Conversion
Planning/scheduling
Medium-short
Medium Very low
Discrete: Main
Planning/scheduling
Medium-short
Medium Medium/low
Discrete: Assembly
Scheduling Short High High
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Table 8.2Segment Optimization
ProblemSolution Technique
Continuous: Main Lot-sizing, cyclic scheduling
MIP
Continuous: Finishing
Single machine, parallel machine
Batch scheduling, inventory control, dispatch rules
Discrete: Conversion
Single machine, parallel machine
Batch scheduling, dispatch rules, CP
Discrete: Main Flow shop, job shop
IP, CP, shifting bottleneck, LS
Discrete: Assembly
Assembly line Grouping, spacing, sequencing techniques, CP, LS
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Supply Chain Decomposition
Medium-term plannin
g
Short-term
sched-uling
Stage 1 Stage 2 Stage 3 Stage 4
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Medium-term Aggregation
Time abstraction 1 unit = 1 day or 1 week
Product abstraction Work at product “family” level
e.g., Tuborg beer, not 6-pack, 12, 24, keg, …
Cost/job/capacity abstraction Average processing times Sequence dependencies ignored Factory treated as a single resource
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Medium-term Planning Results
Daily or weekly Demand for product families at each
facility Inventory levels Transportation requirements
No detailed scheduling has been done!
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Medium-term Constrains Short-term
Medium-term plannin
g
Short-term
sched-uling
Stage 1 Stage 2 Stage 3 Stage 4
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Medium-term Decouples Short-term
Medium-term plannin
g
Short-term
sched-uling
Stage 1 Stage 2 Stage 3 Stage 4
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Short-term Scheduling Uses More Precise Data
Time in minutes or seconds Horizon ≈ week, 2 weeks Jobs and resources are detailed Set-up time/cost are taken into
account Products not just product families
Demand for each product is represented
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Problem
Short term schedule solution may not exist! Why?
May require feedback of information to the medium-term and a resolve Carlsberg takes 10-12 hours for a
medium-term solve …
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Feedback Mechanism Needed
Medium-term plannin
g
Short-term
sched-uling
Stage 1 Stage 2 Stage 3 Stage 4
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Information Infrastructure Requirements
Medium-term plannin
g
Short-term
sched-uling
Stage 1 Stage 2 Stage 3 Stage 4