|
Description:
|
Within any manufacturing environment , the selection of the production or assembly machines is part of the day to day responsibilities of management . This is especially true when there are multiple types of machines that can be used to perform each assembly or manufacturing process . As a result , it is critical to find the optimal way to select machines when there are multiple related assembly machines available . The objective of this research is to develop and present a model that can provide guidance to management when making machine selection decisions of parallel , non -identical , related electronics assembly machines . A model driven Decision Support System (DSS ) is used to solve the problem with the emphasis in optimizing available resources , minimizing production disruption , thus minimizing cost . The variables that affect electronics product costs are considered in detail . The first part of the Decision Support System was developed using Microsoft Excel as an interactive tool . The second part was developed through mathematical modeling with AMPL9 mathematical programming language and the solver CPLEX90 as the optimization tools . The mathematical model minimizes total cost of all products using a similar logic as the shortest processing time (SPT ) scheduling rule . This model balances machine workload up to an allowed imbalance factor . The model also considers the impact on the product cost when expediting production . Different scenarios were studied during the sensitivity analysis , including varying the amount of assembled products , the quantity of machines at each assembly process , the imbalance factor , and the coefficient of variation (CV ) of the assembly processes . The results show that the higher the CV , the total cost of all products assembled increased due to the complexity of balancing machine workload for a large number of products . Also , when the number of machines increased , given a constant number of products , the total cost of all products assembled increased because it is more difficult to keep the machines balanced . Similar results were obtained when a tighter imbalance factor was used . |