safety,risk and reliability
Seyedeh Sara Khorashadizadeh; Jalal Haghighat Monfared; Mohammadali Afshar Kazemi; Shahram Yazdani
Abstract
The aim of this study was to propose a comprehensive risk classification for pharmaceutical industries. Bailey’s classical strategy method was used to develop the classification. Systematic review of literature was used for identification of articles related to supply chain risk management in pharmaceutical ...
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The aim of this study was to propose a comprehensive risk classification for pharmaceutical industries. Bailey’s classical strategy method was used to develop the classification. Systematic review of literature was used for identification of articles related to supply chain risk management in pharmaceutical industries. 77 articles were selected for final review. The selected articles examined in three stages of extracting and classifying the main risk groups of the supply chain (the first dimension of the conceptual framework of classification), extracting and classifying criteria for safety and security of supply chain (the second dimension of the conceptual framework of classification) and applying the two-dimensional framework of classification to identify and classify risk factors of the supply chain. Eventually 372 risk factors were identified and classified by applying the classifying frameworks to literature of pharmaceutical supply chain risk management. The proposed classification can be used as a reference classification in studies related to supply chain risks.
safety,risk and reliability
Amir Yousefli; reza Norouzi; Amir Hosein Hamzeiyan
Abstract
Reliability Redundancy Allocation (RRA) is one of the most important problems facing the managers to improve the systems performance. In the most RRA models, presented in the literature components’ reliability used to be assumed as an exact value in (0,1) interval, while various factors might affect ...
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Reliability Redundancy Allocation (RRA) is one of the most important problems facing the managers to improve the systems performance. In the most RRA models, presented in the literature components’ reliability used to be assumed as an exact value in (0,1) interval, while various factors might affect components’ reliability and change it over time. Therefore, components reliability values should be considered as uncertain parameters. In this paper, by developing a discrete - continuous inference system, an optimization - oriented decision support system is proposed considering the components’ reliability as stochastic variables. Proposed DSS uses stochastic if - then rules to infer optimum or near optimum values for the decision variables as well as the objective function. Finally, In order to evaluate the efficiency of the proposed system, several examples are provided. Comparison of the inferred results with the optimal values shows the very good performance of the developed stochastic decision support system.
