Graduate Thesis Or Dissertation
 

Linking equations for the analysis of a serial automated workstation system

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  • In this research, an analytical model for analyzing a production line consisting of a series of automated workstations with infinite buffers is developed. Automated workstations are assumed to have deterministic processing times, and independent exponentially distributed operating time between failures and repair times. The analytical model starts with existing results from a Markov chain model of two automated workstations in series, where analytical expressions are developed for the average number of jobs in the second workstation and its queue. This research focuses on the development of a set of linking equations that can be used to analyze larger systems using a two workstation decomposition approach. These linking equations utilize probabilities computed in the two-workstation Markov chain model to compute workstation parameters for a single workstation such that the first two moments of the inter-departure process from the two-workstation system and the single workstation are the same. Simulations of a number of different 3-workstation and 10-workstation systems were carried out employing a range of workstation utilizations and processing time coefficients of variation. The results from these simulations were compared with those calculated with the analytical model and various two-parameter GI/G/1 approximations and linking equations present in the literature. The analytical model resulted in an average absolute percentage difference of less than 5% in the systems studied, and performed much better than general two parameter G/G/1 approximations. The analytical model was also robust in ranking the queues in the order of the average number of jobs present in the queues.
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file details NagarajanRaghavendran2004.pdf 2017-08-19 公开 下载