A GRASP for scheduling printed wiring board assembly

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Abstract
The assembly of printed wiring boards (PWBs) typically involves the coordination of thousands of components and hundreds of part numbers in a job shop environment with up to 50 different processes and workstations. In this paper we present a greedy randomized adaptive search procedureor GRASP, for solving the daily scheduling problem that is found in such environments. The advantages of the proposed methodology are its ability to respond quickly to changing organizational goals, revised customer requests, and a multitude of shop-floor contingencies. A flexible lot-sizing heuristic with user overrides allows the scheduling algorithm to alter the production strategy in the face of random disturbances, such as machine failures, component stockouts, and demand perturbations. The algorithms, embedded in a decision support system, have been implemented at Texas Instruments' (TI) Austin facility. This facility assembles boards for internal use and for a growing number of external customers. Before implementation it was necessary to convince management that the new approach would significantly outperform the scheduling methods that were currently in use. We were able to do this by running a series of experiments using real data that compared TI's rule set for scheduling starts and WIP with our methodology. The results indicated that over 10% increase in net revenues could be achieved with the GRASP and that comparable improvements in cycle time, flowline balance, and throughput could also be realized. Operational experience over the last two years has borne this out.