PRINTED-CIRCUIT BOARD FAMILY GROUPING AND COMPONENT ALLOCATION FOR A MULTIMACHINE, OPEN-SHOP ASSEMBLY CELL

This article considers a particular printed circuit board (PCB) assemb ly system employing surface mount technology. Multiple, identical auto matic placement machines, a variety of board types, and a large number of component types characterize the environment studied. The problem addressed is that of minimizing the makespan for assembling a batch of boards with a secondary objective of reducing the mean flow time. The approach adopted is that of grouping boards into production families, allocating component types to placement machines for each family, div iding of families into board groups with similar processing times, and the scheduling of groups. A complete setup is incurred only when chan ging over between board families. For the environment studied, precede nce constraints on the order of component placement do not exist, and placement times are independent of feeder location. Heuristic solution procedures are proposed to create board subfamilies (groups) for whic h the component mounting times are nearly identical within a subfamily . Assignment of the same component type to multiple machines is avoide d. The procedures use results from the theory of open-shop scheduling and parallel processor scheduling to sequence boards on machines. Note that we do not impose an open-shop environment but rather model the p roblem in the context of an open shop, because the order of component mountings is immaterial. Three procedures are proposed for allocating components to machines and subsequently scheduling boards on the machi nes. The first two procedures assign components to machines to balance total work load. For scheduling purposes, the first method groups boa rds into subfamilies to adhere to the assumptions of the open-shop mod el, and the second procedure assumes that each board is a subfamily an d these are scheduled in order of shortest total processing time. The third procedure starts by forming board subfamilies based on total com ponent similarity and then assigns components to validate the open-sho p model. We compare the performance of the three procedures using esti mated daily, two-day, and weekly production requirements by averaging quarterly production data for an actual cell consisting of five decoup led machines. (C) 1994 John Wiley & Sons, Inc.