Title | ||
---|---|---|
Simulation test bed for manufacturing analysis: benchmarking of a stochastic production planning model in a simulation testbed |
Abstract | ||
---|---|---|
A major problem in production planning is to determine when to release products into production to meet forecasted requirements. Recently, Riaño et al. (2002) proposed the Stochastic Production Planning (SPP) model for a multi-period, multi-product system, where the lead time to produce a product may be random. The model determines release times for the products that ensure the requirements in each time period are met with desired probabilities at a minimum cost. This paper describes how an advanced planning model like SPP can be integrated with discrete event simulation models to make the simulations more realistic and informative. This paper also compares the performance of the SPP model with the classical MRP (materials requirements planning) model, and with a stochastic variation of the MRP model in a simulation study. The costs associated with the production plans from SPP are about 10% less than the costs from the other two models. |
Year | DOI | Venue |
---|---|---|
2003 | 10.5555/1030818.1030975 | Winter Simulation Conference |
Keywords | Field | DocType |
stochastic production planning model,simulation study,advanced planning model,release time,simulation test bed,production planning,classical mrp,mrp model,discrete event simulation model,lead time,spp model,production plan | Material requirements planning,Systems engineering,Simulation,Computer science,Testbed,Lead time,Production planning,Benchmarking,Discrete event simulation | Conference |
ISBN | Citations | PageRank |
0-7803-8132-7 | 2 | 0.62 |
References | Authors | |
1 | 6 |
Name | Order | Citations | PageRank |
---|---|---|---|
German Riano | 1 | 8 | 1.76 |
Richard Serfozo | 2 | 2 | 0.62 |
Steven Hackman | 3 | 2 | 0.96 |
Szu Hui Ng | 4 | 223 | 21.88 |
Lai Peng Chan | 5 | 27 | 2.90 |
Peter Lendermann | 6 | 219 | 25.96 |