Dr. James R. Burns, Professor College of Business Administration Texas Tech University

1. Supply and Value Chain Support Through Scheduling and Simulation: Applications to the Semiconductor Industry Dr. James R. Burns, Professor College of Business Administration Texas Tech University Dr. Onur Ulgen, Professor Department of Industrial and Systems Engineering University of Michigan, Dearborn Dearborn, Michigan 48128

2. Introduction • Simulation Tools for Supply Chain Inventory Analysis are presented • Reductions in inventory result in • Reductions in cost • Reductions in cycle time • Improvements in quality • Improvements in workflow

3. Simulation Models • Through use of IT to produce enterprise-wide visibility, simulation models show • Significant reductions in uncertainty are possible • This leads to reductions in between supplier inventory • Which leads to reductions in cycle (lead) time • The models show reductions in information delays through IT investments lead to significantly improved performance

4. What are stocks and flows?? • A way to characterize systems as stocks and flows between stocks • Stocks are variables that accumulate the affects of other variables • Rates are variables the control the flows of material into and out of stocks • Auxiliaries are variables that modify information as it is passed from stocks to rates

5. Stock and Flow Notation--Quantities • STOCK • RATE • Auxiliary

6. Stock and Flow Notation--Quantities • Input/Parameter/Lookup • Have no edges directed toward them • Output • Have no edges directed away from them

7. Inputs and Outputs • Inputs • Parameters • Lookups • Inputs are controllable quantities • Parameters are environmentally defined quantities over which the identified manager cannot exercise any control • Lookups are TABLES used to modify information as it is passed along • Outputs • Have no edges directed away from them

8. Stock and Flow Notation--edges • Information • Flow

9. Basic Model Structure

10. A Two-player Supply Chain Model • First player (the supplier) provides product to the second player (the firm) • Second player provides information back to the first • Each player received orders from its “customer” and replenishes inventory according to its ordering policy

11. Inventory Ordering Policy • Assume continuous replenishment with constant demand, fixed order quantity • Using the Wilson EOQ model, the optimal order quantity can be calculated to be 2000 widgets • With annual demand of 6 million, 3000 orders go out every year • That is an order every 2.9 hours

12. We present first The Two-player Supply Chain Model… • Without information visibility • With discrete ordering policy of ordering 2000 widgets once every 2.9 hours

14. The second Two-Player Model Assumes ... • Instantaneous information about end-customer purchases all the way up and down the supply chain • orders cost virtually nothing, as opposed to $100 in the earlier model • an implied order goes out every time a purchase is seen at the customer end • Otherwise, the two models are identical, structurally

16. Comparing the two models • Instantaneous ordering model exhibits greater sales (less missed sales) • Instantaneous ordering models exhibits significantly lower total holding cost--$5,000,000 vs. $13,000,000. • Results here are approriate for a supplier making product that costs the firm $1000 each and for which there is annual demand of 6,000,000 units a year

17. Why the differences with respect to inventory? • In some cases, the discrete ordering policy “misses” its threshold and does not order more inventory • This results in missed sales (there are some time steps in which no ordering takes place at all) • Beginning at month four, every other time step is missed, roughly, so for the last eight months, onl half of the monthly demand of 500,000 units is met. • Instead of selling 6,000,000 units, only 4,000,000 were sold

18. Why the differences with respect to holding cost? • Overall, the inventory in the pipeline in the instantaneous ordering model is significantly less. • Discrete pipeline approach to upstream information dissemination results in larger inventories • Discrete pipeline scenario starts with much higher initial inventories--500,000 versus only 100 for the enterprise visibility approach. • The high initial inventories are needed to compensate for the missed sales and does so until about month four

19. Cycle times and Little’s Law • According to Little’s Law • Cycle time = inventory / throughput • Inventory was reduced by 58% • Cycle time would be similarly reduced

20. Reduced inventory leads to... • reduced cycle (lead) times • less rework and scrap due to smaller lot sizes

21. What about a large order quantity? • 500,000 once a month would do it • results are worse that orders of 2000 a month

26. A Three-Player Supply Chain • Each player is modeled as a first-order balancing loop structure • Customer orders run 30 per time steps, but this happens randomly in only halfof the time steps. • This model is looked at in both of two contexts--a delayed information approach and the enterprise-wide instantaneous information approach

27. First-order Balancing loop structure

34. The last figure • exhibits a rapid ascent to the desired inventory on the part of all three players, to the desired inventory, with no overshoot--very well behaved

35. These models were created using the VENSIM tool • www.vensim.com • a product of Ventana Systems, Inc.

36. Translation of these models to commercial simulations • These models can be setup to be driven by flight simulator front ends with sliders and dials, meters and such • Users would decide upon • Amount of work in process • Ordering policy • Ordering parameters (quantity, time between reviews, lead time, safety stock, etc.)

37. Summary • Continuous dynamic simulations explain much of the behavior we see in enterprise systems and supply chains • They can be useful tools for deciding • What effect IT will have on the supply chain • The actual structure of the simulation tools can be preprogrammed

38. Summary, Continued • The only thing the user has to do is use the simulation model to make decisions about • Ordering policy • Order quantities • Order frequency • Order lead time • Amount of work in process • Etc.

39. Questions from the AUDIENCE??? • Thank you for coming!!!