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Probabilistic Assessment of Industrial Synergistic Systems
Authors:Yung‐Chia Hsu  Serge Rohmer
Institution:1. National Chiao Tung University, Taipei, Taiwan;2. University of Technology of Troyes, Troyes, France
Abstract:A probability‐based method is presented for assessing the reliability of synergistic systems and their ability to cope with the uncertainties often associated with two of a company's main types of activities: those carried out by the manufacturing department, and those carried out by the storage department. This method is based on a model focusing on the dynamic simulation of synergistic flows in terms of the mass balance. It differs from previous material flow analysis tools, which do not take into account the temporary failures occurring at the companies involved and the resulting loss of production capacity. The failure events occurring at any of the companies in a synergistic system may result in various levels of synergy failure and a short supply of resources for other companies. We therefore propose to identify the main factors responsible for a lack of synergy. We developed a dynamic stock simulation model for assessing the reliability of synergistic systems as well as that of the individual companies of a system before and after a synergy is set up. We first confirm the validity of this model by comparing the results with those based on the binomial theorem in system reliability analysis, and we then apply the model to the case of an industrial system. We conclude that companies involved in a synergistic system will inevitably be exposed to a higher risk of resource shortage because of the unsteady synergistic and outsourcing flows on which they depend. More efficient stock management methods would prevent the occurrence of the risks often associated with synergistic flows.
Keywords:dynamic stock simulation  industrial ecology  material flow analysis (MFA)  risk assessment  synergy  system analysis
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