Master Schedule Stability Under Conditions of Finite Capacity
A basic intro to this paper:
http://mit.edu/edmund_w/www/IJPR_stability_-Ver9.pdf
We are revising this paper for International Journal of Applied Management Science
It is a popular topic, however, it is limited to make-to-stock.
ABSTRACT
The Master production schedule (MPS) is the main tool to control product availability, which is the core element of improving customer service in the consumer goods industry. Calculation of the MPS becomes much more complex in a multi-product environment where forecast errors and capacity constraints can add a great deal of uncertainty to the planning process. This circumstance leads to a problematical issue known as MPS stability. In this article, we propose a new way to improve MPS stability under conditions of finite capacity. The approach has its genesis in a real world, make-to-stock situation that frequently occurs in the food industry and other related types of manufacturing. Using a comprehensive MPS model, we conduct a simulation study with experimental design to identify factors having a significant influence on MPS stability. Then we perform sensitivity analysis on select factors that hold the greatest promise for improvement by employing a simple predictive equation. Finally, we test a different way to plan safety stocks and report the results. In conclusion, we find that elimination of forecast bias and choice of safety stock method both are particularly important for improving MPS stability and ultimately customer service.
Keywords: master production schedule; stability; finite capacity; consumer goods industry; forecast bias; safety stock
An Update on Auto-ID Technology
An interesting area is using RFID tags as an ultra low cost sensor.
The Internet of Things
I am thinking about writing a book in this area, specializing in agriculture.
I can give an overview.
These are some links for ioT
The Master production schedule (MPS) is the main tool to control product availability, which is the core element of improving customer service in the consumer goods industry. Calculation of the MPS becomes much more complex in a multi-product environment where forecast errors and capacity constraints can add a great deal of uncertainty to the planning process. This circumstance leads to a problematical issue known as MPS stability. In this article, we propose a new way to improve MPS stability under conditions of finite capacity. The approach has its genesis in a real world, make-to-stock situation that frequently occurs in the food industry and other related types of manufacturing. Using a comprehensive MPS model, we conduct a simulation study with experimental design to identify factors having a significant influence on MPS stability. Then we perform sensitivity analysis on select factors that hold the greatest promise for improvement by employing a simple predictive equation. Finally, we test a different way to plan safety stocks and report the results. In conclusion, we find that elimination of forecast bias and choice of safety stock method both are particularly important for improving MPS stability and ultimately customer service.
Keywords: master production schedule; stability; finite capacity; consumer goods industry; forecast bias; safety stock
An Update on Auto-ID Technology
An interesting area is using RFID tags as an ultra low cost sensor.
The Internet of Things
I am thinking about writing a book in this area, specializing in agriculture.
I can give an overview.
These are some links for ioT
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