Industrial Management Perspective
Year:2019 | Volume:9 | Issue:33 |Papers Count:7

Nowadays the efficiency-o7666riented performance evaluation of complex systems be-comes increasingly important for investment and management decisions. This paper proposes a new formulation approach based on dynamic network DEA (DN– DEA) models for multi-period and multi-division (MPMD) systems to measure and decompose the overall efficiency. Although conventional DEA models provide magnificant modeling idea of efficiency measures in the multi-input and-output contexts, they do not account for the multi-division transformation process of decision-making units (DMUs) and present “ black-box” measures of their efficiency scores wich causes incorrect estimates of the efficiency points of the units by ignoring the information about the internal operations of the system. As an illustrative case study, the present research applies the proposed approach to evaluate the efficiencies of 13 universities of Iran over the three-year period and the rate of innovation has been measured according to each division, every period, as well as total innovation.

The increased competition in markets, make manufacturers find a better way to attract customers. It is critical to make customers sure about the quality and reliability of products. One way to ensure customers is providing warranty policies to reduce not only the risk of production failures, but also to understand customers’ wants and requirements. This research seeks to recognize the effects of decision making of customers on short-term and long-term results of warranty providers with agent based modeling. Cusomers of this market have different risk prefrences and make decision in two ways: logically and socially. The reults confirm that the type of customers and their decisions influence the number of customers who will to extend their contract and the profitability of warranty providers. Concering to all states, the fisrt warranty provider in short term and the second warranty provider in long term are more capable of keeping customers and make profit.

In this research a multi-objective job shop scheduling problem with an assembly stage and lot streaming is studied. Lot streaming (LS) technique is a process in which a job (lot) is splitted into smaller jobs (sub-lots) such that successive operations can be overlapped. The aim of this study is to schedule and sequence operations in order to meet constraints and minimize the makespan and total weighted earliness and tardiness penalties which, in turn, leads to decrease time and costs and achieve more effective management in industrial departments. First, a mixed integer linear programming model is presented. Since this problem is classified as NP-hard, a metaheuristic algorithm based on Harmony Search is proposed to solve the problem. In order to verify the effectiveness of the proposed algorithm, several performance measures are used. Computational results revealed that the proposed algorithm outperforms non-dominated sorting Genetic algorithm.

The current research intends to optimize green/functional quality decisions along with pricing and marketing decisions in a two-echelon supply chain. In this paper, coordination of a supply chain is analyzed under consumer environmental awareness (CEA) where demand is a function of: (1) price, (2) marketing/advertisements, (3) functional quality, (4) green quality. In the investigated supply chain, the retailer decides on price and advertisement decisions while the manufacturer decides on functional/green quality decisions. At first, the supply chain is modeled under decentralized decision making and at the second stage, decision variables are optimized under the centralized structure. Finally, a mathematical programming model is developed to coordinate decision variables and at the same time ensures participation of both supply chain members. Results show that the proposed mathematical model results in higher profit for the supply chain compared to the decentralized model and also achieves a Pareto improvement for supply chain members. In addition, compared to the decentralized model, under the proposed model, the green quality of products is decided in higher levels.

In modern business environments, a competitive Supply Chain Management is crucial to business continuity. In this context, Lean, Agile, Resilient and Green (LARG), are advocated as the fundamental paradigm for a competitive Supply Chain as a whole. Various paradigms have emerged in the supply chain from the beginning, from among which there are four paradigms lean, agile, resilient and green that are important in supply chain performance and competitiveness, which are referred to as the LARG supply chain. Each of these paradigms pursues a specific mission and purpose in the supply chain. The choice of best supplier in each supply chain is based on different decision-making criteria, but the weight of each criteria varies according to the supplier's priorities. The purpose of this research is to provide a hybrid model of multi-criteria decision for selecting suppliers in the LARG paradigms of tile and ceramic industry. In this research, in first, supplier selection indicators are identified and then weighted by the Best Worst Method. Subsequently, suppliers are ranked by piecewise linear value function and multi-criteria decision-making technique TODIM. This system can play an important role in improving supply chain performance in effective decision making by managers in the supplier selection process and provide results based to reality.

This research aimed to present a sustainable value chain model based on Porter's Framework Development and Balanced Scorecard. Since the localization of this developed model requires a deep examination of an industry or the needs of an enterprise, partnership company of Sayyahfar & Khandadash with the brand named PremiumBond, active in the aluminum composite panel industry, has been selected as a case study. The research strategy respect to the objectives and coverage of the mentioned steps is qualitative and in terms of purpose, developmental and applicative, and respect to variables, it's exploratory mixed and the results are presented using a review of library studies and an open interview with experts. Data analysis was done using Multi-Criteria Decision-Making techniques such as Best-Worst and Topsis method along with Excel 2013 software. Finally, based on the results, the suggested developed value chain model, the new value chain model for PremiumBond Company along with the contribution of each value domain and the developed value chain ecosystem profile, are presented.

Today's organizations are in a world that is sensitive to social and environmental issues, and it is necessary to give special attention to the health and well-being of employees, as well as environmental protection, in addition to customer satisfaction. The purpose of this study is to determine the weight of each of the HSE maturity indices for oil and gas industries. The statistical population of the study consisted of HSE experts and experts in Sarkhon and Qeshm Refinery Company. HSE maturity indicators have been identified through semi-structured interviews with the organization's experts and the experimental data of the research. To determine the importance of dimensions and indicators, a combination of fuzzy DEMATEL and fuzzy ANP techniques have been used. The results showed that the dimensions of strategy and line with score of 97, evaluation and risk management with a score of 85 and leadership, commitment and culture with the score of 80 first to third priorities, and in the results section, the safety dimensions with a score of 172, health with score 142 and environmentalists rated 137 with the first to third priority. Finally, the HSE maturity level of Sarkhon and Qeshm gas refining companies was measured using the weights earned in the research, with 80. 2% of the total points ranked 3rd (growth level).