A simulation-based backward planning approach for order-release
Proceedings of the 29th conference on Winter simulation
Creating a flexible, simulation-based finite scheduling tool
Proceedings of the 29th conference on Winter simulation
Application of discrete event in production scheduling
Proceedings of the 30th conference on Winter simulation
Application of real-time simulation to assign due dates on logistic-manufacturing networks
Proceedings of the 30th conference on Winter simulation
An expert systems approach to simulating the human decision maker
Proceedings of the 30th conference on Winter simulation
Interating simulation based scheduling with MES in a semi-conductor fab
Proceedings of the 30th conference on Winter simulation
Validation and verification of simulation models
Proceedings of the 31st conference on Winter simulation: Simulation---a bridge to the future - Volume 1
Simulation modeling and optimization using ProModel
Proceedings of the 31st conference on Winter simulation: Simulation---a bridge to the future - Volume 1
Supply chain planning: the role of simulation in advanced planning and scheduling
Proceedings of the 34th conference on Winter simulation: exploring new frontiers
Proceedings of the 38th conference on Winter simulation
Optimization of production plan through simulation techniques
WSEAS Transactions on Information Science and Applications
A methodological approach to develop an integrated simulation system in manufacturing processes
ICOSSSE'07 Proceedings of the 6th WSEAS international conference on System science and simulation in engineering
| Hi-index | 0.00 |
This article illustrates the integration of discrete event simulation into the capacity planning process of a tier two automobile supplier. In this application, the capacity planning process is able to generate a feasible schedule for the 30% of the product line which generates 80% of the business. The schedule is "feasible" based on the ability to produce sufficient inventory to cover customer demand. The capacity planning process was unable to develop a schedule for the production of the remaining 70% of the product line or take into account shortages in customer supplied materials used in the production process. Simulation is used to validate the capacity planning process as well as generate a feasible schedule for the remaining products during the planning period as well as: evaluating the plan for customer supplied materials; identifying potential areas for improvement in the production process and determining material storage requirements for the facilities planner.