SWOT Analysis using of Modified Fuzzy QFD – A Case Study for Strategy Formulation in Petrokaran Film Factory

AbstractStrategy is a comprehensive program that determines main approaches of the organization and suggests proper ways for allocating resources in order to help the organization to achieve its long term objectives. Environment change, competitiveness and attitude of customers have convinced managers to have a strategic program. In strategic programming SWOT analysis is a useful method that can be used for analyzing strengths and weaknesses within the organization and opportunities and threats from outside of the organization. Although this method is very practical there are some problems in using it. For example there is no tool to determine the importance of factors and this is mostly done by personal preferences. In this paper weight of strengths, weaknesses, opportunities and threats are calculated by Fuzzy Quality Function Deployment and proper strategies for the organization are achieved by HOQ (House of Quality). Hence the customer requirements are important for the strategic planners in this approach the relations between the customer requirements and relations at the top of HOQ are numerically calculated and have impact on internal and external factors of the organization. Because of uncertainty in the decision making factors the calculations are done in a fuzzy environment. At the end this approach is applied in Petrokaran factory as a numerical case study

Vendor Selection: An Enhanced Hybrid Fuzzy MCDM Model

The objective of this article is to develop an empirically based framework for formulating and selecting a vendor in supply chain. This study applies the fuzzy set theory to evaluate the vendor selection decision. Applying Analytic Hierarchy Process (AHP) in obtaining criteria weights and applied Technique for Order Performance by Similarity to Idea Solution (TOPSIS) for obtaining final ranking of vendors. The usefulness of this model is explained through an empirical study for vendor selection

Board Intellectual Capital, Board Effectiveness and Corporate Performance: Goodness of the Data

Many factors influence corporate performance and among them, intellectual capital (IC) and corporate governance are the most important determinants. Based on the literature, the direct effect of IC and corporate governance mechanisms on corporate performance have been measured in the past several years. Nevertheless, to empirically test indirect effect of board IC and board effectiveness on corporate performance remains scant. In addition, most of the research in these areas have been conducted in developed countries. It is found that not much research has been carried out in the emerging markets of Middle-East like Iran. The purpose of this paper is to present goodness of data processes in relation to study board IC, board effectiveness and corporate performance of listed companies in Iran. The goodness of data involves screening and purifying of raw data in accordance with the assumptions of multivariate analysis. Data screening is the process of checking data for errors and correcting them before performing data analysis. The study employed census method where all listed companies in Tehran Stock Exchange (TSE) were investigated. Data were obtained through the questionnaire survey on 292 board members in TSE. Raw data were keyed into Statistical Package for Social Science (SPSS) version 22. A descriptive statistic, treatment of missing data, univariate assessment and removing of outliers, normality and multicollinearity tests were conducted. The results from data cleaning revealed a significance and the suitability of the data for multivariate analysis

Providing a Lean Supply Chain Model for Iran's Defense Industries Using Interpretative Structural Modeling Approach

The production of defense products is indispensable because of the role it plays in deterring and promoting the national security of the country, and, on the other hand, the economic conditions prevailing in the country have made production of defense products at the lowest cost an obligatory requirement. The lean supply chain of defense industries by focusing on waste removal and reducing costs, is an answer for producing lower-cost defense products. The purpose of this research is to identify the most important practices of the defense industries lean supply chain, and then, using exploratory and confirmatory factor analysis, the categorization and verification of the practices based on Structural Equation Modeling (SEM), and then, using the Interpretive Structural Modeling (ISM) model, presents a model that shows the relationships between these practices. The power of driving and dependence of practices are also analyzed using the MICMAC technique. The results of the research show that out of a total of 84 practices introduced in the previous research for the lean supply chain, 94 practices are effective in the lean supply chain of defense industries. It consists of 8 categories and includes: Workshop level management, Quality management, just in time, Repairs and Maintenance management, Human resource management, Suppliers relationships, new products design and Customer relationship. Customer’s relationship as the most basic and most driving practice and supplier relationship is the most dependent practice of the defense industries lean supply chain

Cloud Theory Based Simulated Annealing alghorithm for a Closed-Loop Supply Chain Network Design: Spanning Tree Solution Representation

Over the past decade, due to environmental laws and the competitive environment, development of an effective tactical plan for efficient and integrated supply chain and considering the responsibility of organizations to collect defective goods seems impossible. In this paper a mixed-integer linear programming is considered to mathematically model the essentially five stages along our supply chain network: suppliers, manufacturers, DCs, customers, and Dismantlers.Delivers raw materials from suppliers to factories and then through distribution centers, delivering the final product to customers. On the other hand, it simultaneously collects recycled goods from customers and enters the cycle of safe reconstruction or destruction.The aim of this model is minimizing the costs of establishing facilities at potential points as well as the optimal flow of materials in the network layers. Since the problem is NP-hard, to solve it, the cloud theory based simulated annealing algorithm has been used. We also used the tree-covering method to show the answer, which uses fewer arrays than other methods in the literature. To analyze the accuracy and speed of the proposed algorithm, we compared its performance with the genetic and simulated annealing algorithm. The results show that the cost function in the cloud-based refrigeration simulation algorithm provides more accurate answers than both algorithms studied in the literature. The results show that the cost function in the cloud-based simulated annealing algorithm provides more accurate answers than both algorithms studied in the literature. Also, in terms of convergence rate criterion, the proposed method has better position than the genetic algorithm, but it is not significantly different from simulated annealing algorithm

Resilient Supply Chain Model in Iran Pharmaceutical Industries

Within two recent decades, the complexity of business environment, dynamics, uncertainty and higher environmental fluctuations, concepts such as globalization and increasing competition made many changes in the equations ruling on the industries supply chain. In such conditions, the businesses must make themselves ready for encountering the continuous flow of challenges such as economic crises, sanctions, exchange rate and prices fluctuations, limitations of manufacturing system or natural disasters. “Resiliency” is one of strategies for dealing with such challenges. The present study aims to review the systematic studies based on the strategic position of pharmaceutical industry as a part of society’s health system and present here the resilient supply chain model. For this purpose, in addition to contemplating in the literature review, interview to the experts and using Delphi method, the resilient elements and indices of supply chain were identified and extracted, and a questionnaire was designed and provided to the population of pharmaceutical industry. The results were analyzed using structural Equations modeling technique and Lisrel software, and the proposed model of research was accepted upon explaining the associations between factors. This model studied the relationship between elements such as drivers, vulnerabilities, capabilities and empowerments of supply chain and their effect on each other. Summary of study indicates that the managers of pharmaceutical industries through making or using the capabilities and strengthening the empowerments can reduce the factors that make the companies susceptible for the disruption, and achieve the required resiliency to deal with them

Sustainable coal supply chain management using exergy analysis and genetic algorithm

Environmental threats of coal usage in the electricity production combined with the consumption of renewable and non-renewable resources had led to worldwide energy challenges. The cost of coal mining and economical and environmentally sustainable usage of mined coal could be optimized by efficient management of coal supply chain. This paper provides a mathematical model for improving coal supply chain sustainability including the cost of exergy destruction (entropy). In the proposed method, exergy analysis is used to formulate the model considering not only economic costs but also destructed exergy cost, while genetic algorithm is applied to efficiently solve the proposed model. In order to validate the proposed methodology, some numerical examples of coal supply chains are presented and discussed to show the usability of the proposed exergetic coal supply chain model and claim its benefits over the existing models. According to the results, the proposed method provides 17.6% saving in the consumed exergy by accepting 2.7% more economic costs. The presented model can be used to improve the sustainability of coal supply chain for either designing new projects or upgrading existing processes