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ISEN 315 Spring 2011 Dr. Gary Gaukler. Dependent Demand. Effective use of dependent demand inventory models requires the following. Master production schedule Bill of material (BOM) Inventory availability Purchase orders outstanding Lead times.
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Dependent Demand Effective use of dependent demand inventory models requires the following • Master production schedule • Bill of material (BOM) • Inventory availability • Purchase orders outstanding • Lead times
Must have D and E completed here so production can begin on B Start production of D 1 week 2 weeks to produce D B 2 weeks E A 2 weeks 1 week E 1 week 2 weeks G C 3 weeks F 1 week D | | | | | | | | 1 2 3 4 5 6 7 8 Time in weeks Time-phased Product Structure
Lot Sizing For MRP Systems Assumptions: • Consider only one item • Demand known and deterministic • Finite horizon • No shortages • No capacity constraints
Lot Sizing For MRP Systems Problem formulation:
Lot Sizing: Silver-Meal Heuristic In any given period, produce to cover demand in a future period as long as the average cost per period is reduced by doing so Algorithm: • Start in period 1. Calculate C(t): average per-period cost if all units for next t periods produced in period 1. • Select lowest t such that C(t)<C(t+1): t* • Produce enough in period 1 to cover t* • Repeat, starting from period t*+1
Silver-Meal Example Assume net requirements are 18, 30, 42, 5, 20 Setup cost for production is $80 Holding cost $2 per unit per period
Production Schedule Changes • So far, the MRP examples we discussed were static • In reality, we need to update our production plans as time passes, thus MRP plans become dynamic • The widest-used technique involves “rolling horizons”:
Production Schedule Changes • Using rolling horizons can lead to fluctuations in the production schedule • As we include more and updated information (e.g., demand forecasts) in each period, our production schedule can change • This is called “system nervousness”
Production Schedule Changes • Results of fluctuations: • Planning for capacity utilization becomes difficult • Fluctuations become larger when we re-run MRP more often • But: re-running MRP is our only way of incorporating more information!
Just-in-time and Lean Production • Goal of Lean production: • Supply the customer with their exact wants when the customer wants it without waste • Method: JIT • JIT is a philosophy of continuous and forced problem solving • JIT: continual improvement, pull system
Waste Reduction • Waste is anything that does not add value from the customer point of view • Storage, inspection, delay, waiting in queues, and defective products do not add value and are 100% waste
Waste Reduction • Faster delivery, reduced work-in-process, and faster throughput all reduce waste • Reduced waste reduces room for errors emphasizing quality • Reduced inventory releases assets for other, productive purposes
Variability Reduction • JIT systems require managers to reduce variability • Variability is any deviation from the optimum process • Less variability = less waste • Inventory hides variability
Process downtime Scrap Setup time Quality problems Late deliveries Reduce Variability Inventory level
Reduce Variability Inventory level Process downtime Scrap Setup time Quality problems Late deliveries
Enabling JIT: Pull System • A pull system uses signals to request production and delivery from upstream stations • Upstream stations only produce when signaled • System is used within the immediate production process and with suppliers
200 – 100 – Q1 When average order size = 200 average inventory is 100 Inventory Q2 When average order size = 100 average inventory is 50 Time Reduce Lot Sizes
Reduce Setup Costs • High setup costs encourage large lot sizes • Reducing setup costs reduces lot size and reduces average inventory • Setup time can be reduced through preparation prior to shutdown and changeover
Implications for Manufacturing Reduced space and inventory • With reduced space, inventory must be in very small lots • Units are always moving because there is no storage