Setup Optimization and Workload Balancing

Excerpt from Setup Optimization and Workload Balancing: For Mixed-Model Electronics Assembly Operations To cope with the rapid technological advances, product proliferation, shorter product lifecycles, and increasing competition, electronics companies are adopting flexible assembly strategies using multiple surface mount assembly modules to produce many different products in small batches. The component placement machines account for over half the investment in surface mount assembly lines, and also require considerable setup time (comparable to the actual processing time for small lot sizes) to changeover production from one product to another. This paper addresses a tactical planning problem for high mix, low volume electronics assembly facilities containing several placement machines (modules) operating in parallel. We propose an optimization model to decide which product families to assemble on each machine in order to minimize the total setup cost per demand period while ensuring that none of the machines is overloaded. Unlike strategic and operational models that emphasize either workload balancing or setup optimization, our tactical planning model simultaneously considers both these conflicting factors. To capture the impact of product grouping decisions on setup cost, we consider a partial set up policy that is both easy to implement in practice, and convenient to incorporate in the tactical planning model. The policy consists of reserving certain slots on each placement machine for permanent components, and loading the remaining components as needed to assemble each product. We formulate the tactical planning problem as an integer program, and show that even the special case of minimizing the setup cost on a single machine for a given assignment of products is NP-hard. For the general model, we develop an optimization-based method, combining column generation, heusristics, and lower bounding procedures, to approximately solve the problem and assess the quality of the solution. As part of our development, we describe solution methods for two practical subproblems - a single machine, product selection subproblem, and the setup optimization subproblem - that might apply directly to short-term production planning. Our computational experience with medium-sized test problems provides insights regarding the effective implementation of column generation strategies in this problem context, and identifies some opportunities for improvement. About the Publisher Forgotten Books publishes hundreds of thousands of rare and classic books. Find more at www.forgottenbooks.com This book is a reproduction of an important historical work. Forgotten Books uses state-of-the-art technology to digitally reconstruct the work, preserving the original format whilst repairing imperfections present in the aged copy. In rare cases, an imperfection in the original, such as a blemish or missing page, may be replicated in our edition. We do, however, repair the vast majority of imperfections successfully; any imperfections that remain are intentionally left to preserve the state of such historical works.