International Journal of Industrial Engineering & Production Research

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In this paper we focus on a continuously deteriorating two units series equipment which its failure can not be measured by cost criterion. For these types of systems avoiding failure during the actual operation of the system is extremely important. In this paper we determine inspection periods and maintenance policy in such a way that failure probability is limited to a pre-specified value and then optimum policy and inspection period are obtained to minimize long-run cost per time unit. The inspection periods and maintenance policy are found in two phases. Failure probability is limited to a pre-specified value In the first phase, and in the second phase optimum maintenance thresholds and inspection periods are obtained in such a way that minimize long-run expected.

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  The unprecedented growth of competition in the banking technology has raised the importance of retaining current customers and acquires new customers so that is important analyzing Customer behavior, which is base on bank databases. Analyzing bank databases for analyzing customer behavior is difficult since bank databases are multi-dimensional, comprised of monthly account records and daily transaction records. Few works have focused on analyzing of bank databases from the viewpoint of customer behavioral analyze. This study presents a new two-stage frame-work of customer behavior analysis that integrated a K-means algorithm and Apriori association rule inducer. The K-means algorithm was used to identify groups of customers based on recency, frequency, monetary behavioral scoring predicators it also divides customers into three major profitable groups of customers. Apriori association rule inducer was used to characterize the groups of customers by creating customer profiles. Identifying customers by a customer behavior analysis model is helpful characteristics of customer and facilitates marketing strategy development .

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There has been a recent development and explosion of interest among academicians across a wide range of disciplines in the use of virtual Class room. Utilization of the virtual class room as a laboratory experimentation for teaching and learning has increased significantly in recent years as development tools for web based applications have become easier to use and computers have become more capable and less expensive. But, does the virtual class-room improve students learning? Herein we describe the results of two experiments conducted on sections of a Manufacturing and Operation Management course [MIME - 3240] at one of the Colleges of Technology in the Sultanate of Oman during fall semester. Two experiments were designed to determine if student learning of Manufacturing and Operation Management course was significantly affected by two treatments: 1) Virtual class room environment for the students of section S₂ and 2) Real Class-room environment for students of section S₁. The actual final scores of students of section S₁ and S₂ were compared in order to determine the effectiveness of virtual class room on student learning for the Manufacturing and Operation Management course.

In this study Web-based virtual Class room (WVC) is developed to communicate, to share and to disseminate knowledge from the teacher to student. Further, in this study web based tools are also used to create, store, and manage contents of class room instructions and course material .

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 Purpose-The purpose of this paper is to review a sample of the literature relating to Interpretive Structural Modelling (ISM) and its deployment for modelling purposes in the area of supply chain management (SCM).
Design/methodology/approach- The literature is examined from the three perspectives. First, concept of ISM and examines ISM as modelling technique. Second, use of ISM by the various researchers in their research for modelling. Third, use of ISM for modelling in the area of supply chain management. Findings- ISM is a systematic application of some elementary graph theory in such a way that theoretical, conceptual and computational advantage are exploited to explain the complex pattern of conceptual relations among the variables. From the literature review, we can conclude that many researchers have used ISM for modelling the variables of: reverse logistics, vendor managed inventory, IT enabled supply chain management etc.
Research limitation/implications-The scope of this literature review is by design limited to ISM and it does not cover in investigating other modelling techniques. Literature review investigates sample of important and influential work in the area of application of ISM in the research.
Originality/Value-This study reviews a sample of recent and classic literature in this field and in doing so this paper provides some comprehensive base and clear guidance to researchers in developing, defining and presenting their research agenda for applying ISM methodology in a systematic and convincing manner.
 Key words: Interpretive Structural Modelling, SCI, SMEs, SCM

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Network location models comprise one of the main categories of location models. These models have various applications in regional and urban planning as well as in transportation, distribution, and energy management. In a network location problem, nodes represent demand points and candidate locations to locate the facilities. If the links network is unchangeably determined, the problem will be an FLP (Facility Location Problem). However, if links can be added to the network at a reasonable cost, the problem will then be a combination of facility location and NDP (Network Design Problem) hence, called FLNDP (Facility Location Network Design Problem), a more general variant of FLP. In previous studies of this problem, capacity of facilities was considered to be a constraint while capacity of links was not considered at all. The proposed MIP model considers capacity of facilities and links as decision variables. This approach increases the utilization of facilities and links, and prevents the construction of links and location of facilities with low utilization. Furthermore, facility location cost (link construction cost) in the proposed model is supposed to be a function of the associated facility (link) capacity. Computational experiments as well as sensitivity analyses performed indicate the efficiency of the model.

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Monitoring the reliability of products in both the manufacturing and service processes is of main concern in today’s competitive market. To this end, statistical process control has been widely used to control the reliability-related quality variables. The so-far surveillance schemes have addressed processes with independent quality characteristics. In multistage processes, however, the cascade property must be effectively justified which entails establishing the relationship among quality variables with the purpose of optimal process monitoring. In some cases, measuring the values corresponding to specific covariates is not possible without great financial costs. Subsequently, the unmeasured covariates impose unobserved heterogeneity which decreases the detection power of a control scheme. The complicated picture arises when the presence of a censoring mechanism leads to inaccurate recording of the process response values. Hence, frailty and Cox proportional hazards models are employed and two regression-adjusted monitoring procedures are constructed to effectively account for both the observed and unobserved influential covariates in line with a censoring issue. The simulation-based study reveals that the proposed scheme based on the cumulative sum control chart outperforms its competing procedure with smaller out-of-control average run length values.

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Most of the researches in the domain of fuzzy number comparisons serve the fuzzy number ordering purpose. For making a comparison between two fuzzy numbers, beyond the determination of their order, it is needed to derive the magnitude of their order. In line with this idea, the concept of inequality is no longer crisp however it becomes fuzzy in the sense of representing partial belonging or degree of membership. In this paper we propose a method for capturing the membership degree of fuzzy inequalities through discretizing the μ-axis into equidistant intervals. It calculates m in the fuzzy inequalities ≤ m and ≥m among two normal fuzzy numbers. In this method, the two μ-axis based discretized fuzzy numbers are compared point by point and at each point the degree of preferences is identified. To show its validity, this method is examined against the essential properties of fuzzy number ordering methods in [Wang, X. and E.E. Kerre, Reasonable properties for the ordering of fuzzy quantities (I). Fuzzy Sets and Systems, 2001. 118(3): p. 375-385.] The result provides promising outcomes that may be useful in the domain fuzzy multi criteria or multi-attribute decision making analysis and also fuzzy mathematical programming with fuzzy inequality constraints.

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Disasters can cause many casualties and considerable destruction mainly because of ineffective preventive measures, incomplete preparedness, and weak relief logistics systems. After catastrophic events happen, quick and effective response is of great importance, so as to having an efficient logistic plan for distributing needed relief commodities efficiently and fairly among affected people. In this paper, we propose a fuzzy multi-objective, multi-modal, multi-commodity logistic model in emergency response to disaster occurrence, to assign limited resources equitably to the infected regions in a way to minimize transfer costs of commodities as well as distribution centers activation costs, and maximizing satisfied demand. In the proposed model, we have determined the optimal place of distribution centers among candidate points to receive people donations as well as sending and receiving different kinds of relief commodities. The amount of voluntary donations is not known precisely and is estimated with uncertainty, so we have used fuzzy parameters for them. The number of victims immediately after disaster is vague and is estimated indecisively though we have considered it as a fuzzy demand. A case study has been displayed to test the properties of the optimization problem that shows efficiency of this formulation in experiment.

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Abstract

            In this research, an integrated inventory model for non-instantaneous deteriorating items is analyzed when demand is sensitive to changes in price. The price used in this research is a time-dependent function of the initial selling price and the discount rate. To control the deterioration rate of items at the storage facility, investment in preservation technology is incorporated. To provide a general framework to the model, an arbitrary holding cost rate is used. Toward the end of the paper, a numerical case is given to approve the model and the impacts of the key parameters of the model are studied by sensitivity analysis to deduce managerial insights.

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Managing income is a considerable dimension in supply chain management in current economic atmosphere. Real world situation makes it inevitable not to design or redesign supply chain. Redesign will take place as costs increase or new services for customers’ new demands should be provided. Pricing is an important fragment of Supply chain due to two reasons: first, represents revenue based each product and second, based on supply-demand relations enables Supply chain to provide demands by making suitable changes in facilities and their capacities. In this study, Benders decomposition approach used to solve multi-product, multi-echelon and multi-period supply chain network redesign including price-sensitive customers.

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Supply chain management is a set of used methods for the efficient integration of suppliers, manufacturers, warehouses, and sellers to response customer requirements to reduce system costs and to distribute products at the right place and right time. This study aims to identify and rank the supply chain damages using the analytic network process as a practical case in a fast moving consumer goods (FMCG-food industry) company. Firstly the supply chain damages are explored according to literature review. In the next step the most important damages are identified into four cluster of supply include
supply, production, distribution and support. Then, the weight of each identified damages based on its effects on other damages are calculated by using the analytic network process approach. According to results, the most important supply chain damages are logistics, distribution, competition and changing market tastes. The obtained results can provide practical discussion and solutions for similar companies to improve your market share and customer satisfaction.

 

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In current study, a particle swarm clustering method is suggested for clustering triangular fuzzy data. This clustering method can find fuzzy cluster centers in the proposed method, where fuzzy cluster centers contain more points from the corresponding cluster, the higher clustering accuracy. Also, triangular fuzzy numbers are utilized to demonstrate uncertain data. To compare triangular fuzzy numbers, a similarity criterion based on the intersection region of the fuzzy numbers is used.  The performance of the suggested clustering method has been experimented on both benchmark and artificial datasets. These datasets are used in the fuzzy form. The experiential results represent that the suggested clustering method with fuzzy cluster centers can cluster triangular fuzzy datasets like other standard uncertain data clustering methods. Experimental results demonstrate that, in almost all datasets, the proposed clustering method provides better results in accuracy when compared to Uncertain K-Means and Uncertain K-medoids algorithms.

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In a system, prediction of remaining useful lifetime (RUL) of servicing before reaching to a specified breakdown threshold is a very important practical issue, and research in this field is still regarded as an appreciated research gap. Operational environment of an equipment is not constant and changes regarding to stresses and shocks. These random environmental factors accelerate system deterioration by affecting on the level or rate of degradation path. The present study focuses on providing a practical operational guideline to estimate the RUL of a system with general degradation path after receiving a shock which only affects on the degradation level. Due to exact estimation of the shock arrival times and measuring the magnitudes of future shocks to investigate shock effects on RUL is almost impossible in the real world and laborious in practice, in this research a new procedure based on total defect size monitored in the constant inspection periods and Accelerated Factor (AF) is proposed to analyze RUL of the system. A Micro-Electro-Mechanical system (MEMS) is used as an example and the results show the applicability of the proposed approach.

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A coalition loyalty program (CLP) is a business strategy employed by for-profit companies to increase or retain their customers. One of the operational challenges of these programs is how to choose the mechanism of coordination between business partners. This paper examines the role of revenue sharing contracts in the loyalty points supply chain of a CLP with stochastic advertising-dependent demand where the program operator (called the host) sells loyalty points to the partners of the program. The purpose of the study is to examine the effect of this coordination mechanism on the decisions and profits of the members of the chain using the Stackelberg game method and determine whether the presence of revenue sharing contracts benefits the chain members when the advertising is done by the host and when the advertising cost is shared between the host and its partners. The results show that when the host gives bonus points to end customers (advertising), revenue sharing contracts become a powerful incentive for the profitability of the host and its partners. The findings provide new insights into the management of CLPs, which can benefit business decision-makers.