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© J. Christopher Beck 20081 Lecture 27: Supply Chain Scheduling 1.

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Presentation on theme: "© J. Christopher Beck 20081 Lecture 27: Supply Chain Scheduling 1."— Presentation transcript:

1 © J. Christopher Beck Lecture 27: Supply Chain Scheduling 1

2 © J. Christopher Beck Outline The Beer Chain Carlsberg Denmark Supply Chain Management Supply Chain Introduction Strategic, Tactical, Operational Planning vs. Scheduling Hierarchical Decomposition

3 © J. Christopher Beck Readings P Ch 8.6, 8.1, 8.2

4 © J. Christopher Beck Supply Chain Scheduling

5 © J. Christopher Beck Carlsberg Sells many different brands of beer Sells many different “formats” bottles, cans, kegs 6-pack, 12, 24

6 © J. Christopher Beck Carlsberg Supply Chain Brewery 1 4 production lines Brewery 2 2 production lines Stage 1 Distribution Centre Stage 2Stage 3 Warehouses

7 © J. Christopher Beck Stage 1 Scheduling 3 production steps on each line brewing (and fermentation) filtering filling – bottling/packaging All are resource constrained but filling is usually the bottleneck Filling operation has different costs and processing times

8 © J. Christopher Beck Stage 1 Scheduling All orders have fixed “lot size” Products are divided into A,B,C categories A – high runners (a lot of demand) C – specialty beers: more expensive, less demand Sequence dependent changeovers!

9 © J. Christopher Beck Stage 1 Transportation Either to DC or direct to a warehouse Different lot size constraints (truck capacity)

10 © J. Christopher Beck Carlsberg Supply Chain Brewery 1 4 production lines Brewery 2 2 production lines Stage 1 Distribution Centre Stage 2Stage 3 Warehouses

11 © J. Christopher Beck Stage 2 & 3 Optimization Placement of pallets at DC and warehouses Transportation to warehouses Transportation to customers vehicle routing

12 © J. Christopher Beck Scheduling Process Medium term: 12 weeks given demand and forecasts for products 3 MIP models solved sequentially Costs: production, storage (at brewery, DC, warehouse), transportation, tardiness, non-delivery penalty, and violation of safety stock Each MIP is composed of 5-10 sub- problems based on products

13 © J. Christopher Beck Safety Stock One goal is customer service Usually achieved by maintaining inventory at DC and warehouses Minimum inventory levels = safety stock A lot of safely stock  good customer service, but also high inventory costs! (and skunky beer)

14 © J. Christopher Beck Short Term Scheduling Based on medium term schedule, short term scheduling plans the actual production for one week More detailed model of resources (i.e., sequence dependent setup costs) Uses genetic algorithm or constraint programming Transportation scheduling

15 © J. Christopher Beck Overall Process Medium term plan is re-done every day using up-to-date information takes 10 to 12 hours Then short term scheduling is re-done

16 © J. Christopher Beck Comments This is not a single model Decompositions are crucial medium term/short term product-based transportation scheduling decoupled from production scheduling

17 © J. Christopher Beck Supply Chain Optimization Assume we are interested in minimizing the cost of the entire supply chain Individual participants will cooperate to minimize overall cost How many things are wrong with this assumption?

18 © J. Christopher Beck Levels & Horizons LevelHorizonTypes of Decisions Strategic1 – 5 yearsFacility location, new products Tactical2 – 6 monthsSourcing, distribution, orders assigned to plants Operational7 to 21 daysProduction & transportation scheduling details

19 © J. Christopher Beck Planning vs. Scheduling PlanningScheduling HorizonMultiple stages, medium term One stage/facility, short term InformationAggregateDetailed ObjectiveMoneyTime (e.g,. tardiness, makespan)

20 © J. Christopher Beck Hierarchical Decomposition Planning solves higher level problems based on aggregate data The planning decisions are then used as constraints (e.g., due dates) for the scheduling May be multiple independent scheduling problems Planning decouples scheduling problems!


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