Study On Reliability Management Of Repairable Supply Network System

As the supply chain system spans more and more countries and its structure becomes more and more complex, plenty of unreliabilities appear, for example, the complexity of a high degree, increasing channel uncertainties, the inherent imbalances between supply and demand, and the increasing number of natural disasters and man terrorist attacks. Uncertainties result in the supply chain more vulnerable to various disruptions. In the process of supply chain management ,if the supply chain reliability declined, the supply chain would operate inefficiently, run costly, and even go to breakdown. Therefore, the unreliability factor identification, reliability evaluation and reliability optimization of the supply network system are of great significance.Firstly, from the perspective of supply chain, the study identifies reliability influencing factors that may affect the reliability of supply network system from seven dimensions, such as operation, finance, flexibility etc, based on supply chain operation reference model(SCOR) and literature analysis. And then the study measures the reliability of supplier, which prepare for the reliability evaluation and optimization of supply network system. Secondly, given the reliability of suppliers, a method of evaluating the reliability of hot standby repairable supply network system and parallel repairable supply network system is given, based on the theory of Markov model. With a case study, this method is analyzed and proved. Furthermore, according to the case study, we offer measures to improve the reliability of supply network system. Finally, after the definition of periodic repair strategy, the object that periodic repair strategy would be applied to, and the analysis of relation between Periodic repair strategy and the reliability of supply chain, the study developed a reliability optimization model of supply network system based on the theory of periodic repair, in order to improve and control the reliability of supply network system. The approach of optimizing reliability is obtained.