By Zeynep Muge Avsar, W. Henk Zijm (auth.), Stanley B. Gershwin, Yves Dallery, Chrissoleon T. Papadopoulos, J. MacGregor Smith (eds.)
Analysis and Modeling of producing Systems is a suite of papers on a number of the most up-to-date learn and purposes of mathematical and computational strategies to production structures and provide chains. those papers care for basic questions (how to foretell manufacturing facility functionality: easy methods to function construction platforms) and explicitly deal with the stochastic nature of mess ups, operation instances, call for, and different very important events.
Analysis and Modeling of producing Systems can be of curiosity to readers with a robust historical past in operations examine, together with researchers and mathematically refined practitioners.
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Extra info for Analysis and Modeling of Manufacturing Systems
An alternative would be to use discreteevent simulation, but experiments indicate that the required computation time for simulation, even on a powerful computer, makes analysis of large numbers of SKUs infeasible. Approximate formulas are also justified simply because in many industrial applications, demand streams fluctuate significantly over time, 40 ANALYSIS & MODELING OF MANUFACTURING SYSTEMS and exact analytical performance estimates in the case of non-stationary demands are mostly intractable and unavailable in the inventory literature.
The rest of this section is devoted to the assessment of the proposed approximation. Performance measures typically considered for repairable item systems are the stockout probability, the fill rate and the expected shortage at the base. The fill rate is defined as the probability that any demand arriving at the base can be fulfilled immediately. To obtain these perfonnance measures, Capacitated Two-Echelon Inventory Models for Repairable Item Systems 13 the distribution of the random variable K] must be computed.
We have presented the analysis under the assumption that all nodes (in either the base repair shop or the central facility, or the transportation nodes) show exponential behavior. , each open BCMP network will do. In particular, this allows for general (non-exponential) transportation servers since in any BCMP network an ample server may have a general service time distribution without destroying the product form property. One other extension to be mentioned here is for multi-echelon systems. Aggregate models of such systems would include conditional probabilities, namely q's, to be defined for each echelon as a function of the state of the Capacitated Two-Echelon Inventory Models/or Repairable Item Systems 23 downstream echelons.
Analysis and Modeling of Manufacturing Systems by Zeynep Muge Avsar, W. Henk Zijm (auth.), Stanley B. Gershwin, Yves Dallery, Chrissoleon T. Papadopoulos, J. MacGregor Smith (eds.)