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Categorical Models for Process Planning

Published

Author(s)

Spencer J. Breiner, Eswaran Subrahmanian, Albert W. Jones

Abstract

Process plans provide a structure for 1) identifying the tasks involved in a given process, 2) the resources needed to accomplish them, and 3) a variety of relationships and constraints between these. This information guides important operational decisions across various organizational levels, from the factory floor to the global supply chain. Efficient use of this information requires a concrete analytical model that can be easily represented in digital form. In this paper we present a modeling framework for process plans based on a branch of mathematics called category theory (CT). Specifically, string diagrams provide an intuitive yet precise graphical syntax for describing symmetric monoidal categories (SMCs), mathematical structures which support serial and parallel composition. Ideal for process representation, these structures also support a powerful mathematical toolkit. Here we use these tools to analyze the relationship between different levels of abstraction in process planning hierarchy. We also model some spatiotemporal aspects of planning, dynamic decision-making inside the process hierarchy and the updating procedure in the event of errors or extensions in the production line.
Citation
Computers in Industry
Volume
v.112

Keywords

Process planning, multi-scale models, functional decomposition, applied category theory

Citation

Breiner, S. , Subrahmanian, E. and Jones, A. (2018), Categorical Models for Process Planning, Computers in Industry, [online], https://doi.org/10.1016/j.compind.2019.103124 (Accessed July 7, 2022)
Created November 19, 2018, Updated May 4, 2021