A Combined Process/Resource-oriented Approach to Shopfloor Simulation

Published

June 1, 2001

Author(s)

Hyunbo Cho, Albert W. Jones, P Y. Jang

Abstract

Manufacturing simulation tools are used frequently to analyze proposed planning, scheduling, and control decisions that attempt to optimize some performance measure(s) for the shop. These shops exhibit a dynamic and complicated evolution caused by the concurrent flows of disparate parts following nonlinear process plans, machine failures, priority jobs, and variability in processing and transportation times. Capturing that evolution faithfully often requires modifications to the tools, the models created using the tools, or both. These modifications to the models are often difficult to make and prohibit timely and effective decisions. This paper describes a new process and resource models-based intelligent simulator (PRISM), which simplifies those modifications. PRISM has four powerful capabilities. First, its process specification capability allows users to model nonlinear process plans that contain all the possible routings through the shop, decision-making rules associated with those routings, and precedence relationships among the processes in those routings. Second, a resource specification capability allows users to model properties of shopfloor resources and decision-making rules associated with those resources. Third, an automation capability that translates the process and resource models into a directed graph that the simulator engine uses directly. Fourth, a real-time analysis capability that simplifies integration of PRISM into many, existing, shopfloor control architectures.

Citation

International Journal of Computer Integrated Manufacturing

Pub Type

Journals

Download Paper

Local Download

Keywords

decision-making problem, directed graphs, nonlinear process plan, simulation

Citation

Cho, H. , Jones, A. and Jang, P. (2001), A Combined Process/Resource-oriented Approach to Shopfloor Simulation, International Journal of Computer Integrated Manufacturing, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=821610 (Accessed July 27, 2024)