Abstract In today's competitive world, production and inventory control in small and medium enterprises (SME) is considered as an important issue by managers, because of the influence of factors such as fluctuations in demand and failure of machines. Network Failure Prone Manufacture Systems (NFPMs) are type of production systems that failure of machines is assumed for them. In this paper, a multi-product network failure manufacturing system with perishable items is studied. The production control policy is based on the hedging point policy that contains producing and maintaining of products in order to respond to demand and avoid shortages. In this system, demand is constant and shortages (backlog and lost sale) have been allowed. The main goal of this paper is to determine the optimal production rates that minimize expected value of total production, holding, shortage, and perishable costs. Because of uncertainly and complexity of these systems, simulation optimization has been done using ARENA software. Finally, numerical example will show the efficiency of the proposed approach.

Abstract In this paper the As-Is model of the organizational affairs process of the NIORDC (National Iranian Oil Refining and Distribution Company) was drawn by the use of BPMN modeling tool, and then its simulation model was modeled by using SIMPROCESS simulation software and relative parameters were defined. Necessary scheduling in defining simulation parameters were extracted and set according to available organizational documents and archives. Afterwards, justification and verification of simulation models were tested by using statistical tests. In the next stage, several reengineering scenarios were suggested and designed according to BPR rules, experts' viewpoints, brainstorming sessions, and the facts found during project implementation. These scenarios were modeled by using BPMN modeling tool, and then their simulation models were designed. Since these scenarios are about the future situation of the process, only some justification and verification steps of simulation models were considered. Finally, on the basis of defined indicators in the beginning of the project, values of them were calculated for each scenario and each one was analyzed on the basis of cost-benefit analysis. At last, these scenarios were ranked by using AHP method and their scores were counted in order to suggest to the management.