Journal of Quality Engineering and Management

Abstract One of the most important factors of effect on designing effective supply chain is reduction of economic costs. On the other hand, greenhouse gas emission and pollutants increase has driven managers of organizations and researchers to look for designing and setting up networks that are focused on optimization of environmental factors and reduction of pollutants in all sectors in addition to economic optimization. In addition to these two factors, product delivery time is one of factors of effect on supply chain. In this research an integrated direct and reverse logistic model is studied by considering three objective functions: minimizing environmental effects, economic costs and delivery time. In this research model, uncertainty is considered through solution robustness. Possible scenarios are defined and evaluated by common risk management tools. Then scenario-oriented robust model of the problem is presented by considering uncertain parameters. The model is completed by replacing occurrence rate of each scenario by outputs of risk assessment (normalized RPN) in the model. Then the model is turned in to a single-objective model by applying LP metric method, and solved with the GAMS software. Finally it can be said that an effective supply chain can be designed by combining risk assessment and robust optimization.     
 
 

Abstract Statistical quality control methods are the basis for measuring process performance and productivity. Control charts are one of the most widely used statistical control tools and play an important role in improving the quality of processes and products. The main purpose of their implementation is to identify the deviation (s) and take corrective measures to eliminate the root of the deviation. The technical applications of control charts are to determine the sample size, sampling frequency and control limits, which is called control chart design. In most nP chart design research, only one reason deviation is considered as the cause of the chart getting out of control, while several industry deviations can play a role. For this purpose, in this research, the design and statistical-economic development of nP control diagram, in order to reduce costs and average detection time and increase the power of the diagram by using gray values ​​and considering deviations for various reasons. In this regard, in order to achieve the optimal values ​​of these parameters, a multi-objective problem with three constraints has been defined, in which we have considered each possible combination of parameters as a decision unit. Then, using data envelopment analysis and ranking methods, the most efficient design for the decision maker is determined. In the continuation of the research, sensitivity analysis has been performed on some parameters of the model and the effect of these parameters on the optimal values ​​has been analyzed.