Abstract
Process family planning has been well recognized as an effective means of maintaining production efficiency by exploiting process reuse and near mass production efficiency underlying product families. To support process family planning automation, this study develops a PROGRES-based approach to modeling planning data, knowledge and reasoning. The PROGRES-based process family planning models are hierarchically organized. At the top level, a meta model is defined to conceptualize process family planning in general. Based on this meta model, generic models are defined for planning process families for specific product families (i.e., specific process family planning). Finally, instance models are obtained by instantiating the generic models, representing production processes for given product family members. The proposed approach is illustrated with planning processes for a textile spindle family.
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