Complexity metrics for manufacturing control architectures based on software and information flow

  • Authors:

  • Areejit Phukan;Manoj Kalava;Vittal Prabhu

  • Affiliations:

  • Harold and Inge Marcus Department of Industrial and Manufacturing Engineering, The Pennsylvania State University, University Park, PA;Harold and Inge Marcus Department of Industrial and Manufacturing Engineering, The Pennsylvania State University, University Park, PA;Harold and Inge Marcus Department of Industrial and Manufacturing Engineering, The Pennsylvania State University, University Park, PA

  • Venue:
  • Computers and Industrial Engineering
  • Year:
  • 2005

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Abstract

A number of architectures can be used to integrate different components of a manufacturing enterprise such as machine tools, robots, and guided vehicles. The choice of architecture has a significant impact on system complexity, which in turn determines properties such as scalability, flexibility, fault-tolerance and modifiability. There is a need to develop metrics that quantify the complexity of a system that can serve as a means for comparing alternative architecture at the design stage. In this paper, we propose metrics used in software engineering to characterize the complexity of manufacturing systems. These metrics have been applied for measuring the complexity of two software systems: material delivery system and distributed scheduling.