A graph rewriting system for process platform planning

Authors:
Linda L. Zhang;Roger J. Jiao
Affiliations:
IESEG School of Management (LEM-CNRS), Catholic University of Lille, 3 rue de la Digue, 59000 Lille, France;The George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, 813 Ferst Drive, 30332-0405 Atlanta, GA, USA
Venue:
Decision Support Systems
Year:
2013

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Abstract

Facilitating production process planning for product families, process platform planning (P^3) has been well recognized as an effective means of achieving production efficiency. To support decision making in P^3 automation, this study adopts graph rewriting systems to 1) organize large volumes of product and process data and 2) model production process planning reasoning. The model developed represents the structural and behavioral aspects of process platforms as family graphs and related graph transformations, respectively. In view of its modeling advantage, the system is formally defined using PROGRES. It includes meta, generic, and instance models at three different levels of abstraction. Meta models are defined for family graphs to generalize the patterns common to planning production processes for different product families; generic models are defined to describe entities pertaining to production processes of specific product families; instance models represent production processes producing product variants in a family. The graph rewriting system-based P^3 model is applied to textile spindles' production process planning. The results obtained have demonstrated its potential and feasibility to support decision making in P^3 automation.