Simulation Optimization of Manufacturing Takt Time for a Leagile Supply Chain with a De-coupling Point
Published 2021-06-30
abstract views: 162 // FULL TEXT ARTICLE (PDF): 0
Keywords
- Simulation Optimization,
- WITNESS®,
- Lean Manufacturing,
- Leagile Supply Chain,
- Takt Time
- Decoupling point ...More
How to Cite
Copyright (c) 2023 International Journal of Industrial Engineering and Management
This work is licensed under a Creative Commons Attribution 4.0 International License.
Abstract
Achieving agility with leanness in supply chains is considered to be a challenge for industry and academia. In order to cope with dynamic demands at extreme downstream, buffer stocks at various points on the supply chain can be seen as a solution. Although it may improve the agility feature but extra inventories at warehouses affects the leanness of the supply chain adversely. The aim of the present paper is to address this issue by finding an optimum rate of production at the factory which is directly related to Takt time concept of lean manufacturing in order to fulfill the dynamic demand patterns at the downstream retailers end while minimizing intermediate stock inventories. The model is conceived as a leagile supply chain with a de-coupling point at the warehouse or distribution center between retailers and plant. A discrete event simulation model for the supply chain is developed in WITNESS® to experiment with various rates of production before finding the optimum value. The two performance measures representing fulfillment of product demands and inventory carrying costs are expressed in equivalent cost units for optimization. Two demand scenarios for a two product supply chain are simulated to identify the optimal rate of production while illustrating the solution methodology. The simulation optimization approach to address this problem of leagile supply chain is found to be effective and practical.
Article history: Received (October 24, 2020); Revised (April 1, 2021); Accepted (April 5, 2021); Published online (May 13, 2021)