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The assignment of workloads to production equipment is one category of planning decision for an electronics assembly factory. In practice, line balancing requires not only selecting machines with sufficient placement accuracy and feeder capacity, but also address- ing a host of other operational objectives and constraints. Motorola Labs led a multi-year effort to apply mathematical programming to balance a variety of production mix and vol- ume scenarios. By representing the optimization problem as a specially structured, mixed linear-integer program, we were able to incorporate a high degree of reality in the model, simultaneously optimizing fixed setups, handling custom parts, maximizing machine uptime, and mitigating secondary bottlenecks. This paper presents the story of how we developed and deployed a software solution that significantly improved assembly cycle times, setup changeovers, and overall factory productivity, saving the company tens of millions of dollars.

Developing and Deploying Electronics Assembly Line Optimization Tools: A Motorola Case Study