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Abstract

Figure 5.1 illustrates the planning problems which are investigated in the developed group setup approaches. In this study, two different approaches are proposed for the job grouping problem. In the first approach, grouping is performed by use of well-known similarity measures and agglomerative linkage methods (see section 5.1). The second approach employs the so-called “inclusion measure” as a similarity coefficient, which is more appropriate for PCB assembly and generates setup families using a novel hierarchical clustering technique which is based on the inclusion tree representation scheme due to Raz and Yaung (1994). This approach is laid out in section 5.2. Because of the hierarchical nature of the presented grouping processes, initial grouping results are then improved using heuristic procedures which are described in section 5.3.

Keywords

Component Type Placement Location Inclusion Measure Nozzle Type Placement Machine 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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