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EMPIRICAL EVALUATION OF EXPONENTIAL AND INDEPENDENCE ASSUMPTIONS IN QUEUEING MODELS OF MANUFACTURING SYSTEMS
Author(s) -
Inman Robert R.
Publication year - 1999
Publication title -
production and operations management
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.279
H-Index - 110
eISSN - 1937-5956
pISSN - 1059-1478
DOI - 10.1111/j.1937-5956.1999.tb00316.x
Subject(s) - randomness , queueing theory , automotive industry , computer science , independence (probability theory) , exponential function , exponential distribution , layered queueing network , mathematical optimization , industrial engineering , operations research , mathematics , statistics , engineering , computer network , mathematical analysis , aerospace engineering
This paper presents actual data (processing times, interarrival times, cycles‐between‐failures, and time‐to‐repair) from two automotive body welding lines. The purpose is twofold. First, to help researchers focus their work on realistic problems, we exhibit the nature of randomness actually found in two industrial manufacturing systems and provide a data source for realistic probability distributions. Second, we assess the validity of two common assumptions regarding this randomness in automotive manufacturing. Many queueing network models assume that certain random variables are independent and exponentially distributed. Though often reasonable, the primary motivation for the independence and exponentiality assumptions is mathematical tractability.