Utilizing Combinatorial Testing on Discrete Event Simulation Models for Sustainable Manufacturing
Paper in proceedings, 2010

This paper describes how combinatorial testing using covering arrays can be implemented to optimize discrete event simulation models of manufacturing systems for measures of sustainability Discrete event simulation models often have hundreds of parameters and many test values for each parameter Generally the interactions between the parameter-values are not well understood this can lead to sub-optimization of the system Most optimization engines and software for discrete event simulation packages use full factorial designs, which require many runs and hence a lot of computation time In this paper we introduce combinatorial testing using a test-suite generation tool called NIST-ACTS (National Institute of Standards and Technology - Advanced Combinatorial Test Suites) to dramatically decrease the number of runs required to detect the interactions and determine an optimal solution.

discrete event simulation

Combinatorial testing

environmental impact optimization

Author

Björn Johansson

Chalmers, Product and Production Development, Production Systems

Raghu Kacker

National Institute of Standards and Technology

Rüediger Kessel

National Institute of Standards and Technology

Charles McLean

National Institute of Standards and Technology

Ram Sriram

National Institute of Standards and Technology

ASME 2009 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC/CIE2009; San Diego, CA; United States; 30 August 2009 through 2 September 2009

PARTS A AND B 1095-1101

Subject Categories

Production Engineering, Human Work Science and Ergonomics

Other Environmental Engineering

DOI

10.1115/DETC2009-86522

ISBN

978-0-7918-4899-9

More information

Created

10/6/2017