International Journal of Industrial Engineering & Production Research
Year:2012 | Volume:23 | Issue:3|Papers Count:8

Decision making about outsourcing or insourcing of manufacturing activities is a Multiple Criteria Decision Making (MCDM) problem, which requires considering many quantitative and qualitative factors as evaluative criteria simultaneously. Therefore, a suitable MCDM method could be useful in this area, take into account the interactions between quantitative and qualitative criteria. The analytic network process (ANP) is a relatively new MCDM method which can deal with different kinds of interactions systematically. Moreover, the Decision Making Trial and Evaluation Laboratory (DEMATEL) method is able to convert the cause and effect relations between of the criteria into a visual structural model as well as handling the inner dependences within a set of criteria. However both ANP method and DEMATEL techniques in their original forms are incapable to capture the uncertainty during value judgment elicitation. To overcome this problem, here, a new and effective model is proposed based on combining fuzzy ANP and fuzzy DEMATEL for decision making about outsourcing or insourcing of manufacturing activities in uncertain conditions. Data from a case study is used to illustrate the usefulness and applicability of the proposed method.

The purpose of this article is to present a system dynamics (SD) model for studying the interconnections among human being weight, eating habit, exercise, body fat, take-in medication, drugs-uses, and the health problems in general. Due to the fact that all of these factors have direct and indirect impacts on the expenses that insurance company have to pay this author is proposing a systems thinking approach for determining the interconnections among the factors and uses the concept of system dynamics to simulate and determine the behavior of the system. To do so, key points about systems thinking, related theories, and system dynamics are reviewed. A model presenting the interconnections between weight factor and health problems are developed and discussed. Expense rates are classified into operational expenses (OE), treatment expenses (TE), Medication expenses (ME), Hospitality expenses (HE), and Drug treatment expenses (DE). This article makes a significant contribution to the health study issues due to the fact that it shows how a factor such as weight can have impacts on hearth attack, blood pressure, and blood sugar, to mention a few, and how relate all these to the overall expenses that an insurance company have to pay at last.

Profile monitoring in statistical quality control has attracted attention of many researchers recently. A profile is a function between response variables and one or more independent variables. There have been only a limited number of researches on monitoring multivariate linear profiles. Indeed, monitoring correlated multivariate profiles is a new subject in the filled of statistical process control. In this paper, we investigate the effect of autocorrelations in monitoring multivariate linear profiles in phase II. The effect of three main models namely AR (1), MA (1), and ARMA (1, 1) on the methods of multivariate linear profile monitoring is evaluated and compared by using simulation study and average run length criteria. Results indicate that autocorrelation affects performance of the existing methods significantly.

The purpose of this paper is to review the literature relating to Interpretive Structural Modelling (ISM) and its deployment for modelling variables of supply chain management (SCM). The literature was 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. This literature review provides some comprehensive base and clear guidance to researchers in developing and presenting their research agenda for modeling the variables of SCM by using ISM for improving the performance of the supply chain.

This paper presents an overview of new approaches in rapid product development in production networks from design points of view. The manufacturing industries are changing their focus to global sourcing as a means to improve performance and enhance competitiveness. Some partnerships created with this strategy improve product development through collaborative design. With the advent of e-Commerce, a new set of collaborative applications integrated to the firms’ IT infrastructure allow a direct interaction between the firm and its suppliers, having an impact of negotiations. The globalization of the market necessitates the reduction of time-to-market, mainly due to shorter product life cycle. The computing and communication have become indispensable in every aspect of product development and design. The paper describes the network that directly links designer capabilities and with customers and manufacturing division. The networks focuses the three major forces that will affect the design community, namely, speed of decision, expansion of scope and degree of concurrency. Due to evolution of production networks, it has become possible to obtain the mass production within a key short time, using emerging technology that affect the speed and efficiency of product development using a pool of efficient designers and product managers.

The present research is conducted to show that organizations can use wiki to attract customers purchase intention inside the e-commerce context. Considering the relation between wiki and ecommerce for CRM, this research tries to explore the characteristics such as perceived risk, customer experience, knowledge sharing culture, trust and knowledge sharing in wiki tool impact on purchase intentions in the web site. By using multidimensional analysis, this study shows that choosing a suitable tool for hosting in the websites in order to gather essential knowledge from customers plays an important role in explaining certain customer online behavior. In particular, the researchers propose a model that explains wikis require a culture of collaboration and sharing in an online environment to achieve a win-win situation between customers and producers.

Control chart pattern (CCP) recognition techniques are widely used to identify the potential process problems. Recently, artificial neural network (ANN) –based techniques are popular for this problem. However, finding the suitable architecture of an ANN-based CCP recognizer and its training process are time consuming and the obtained results are not interpretable. To facilitate the research gap, this paper presents a simple statistical approach for detecting and identifying control chart patterns. In this method, by taking new observations on the quality characteristic under consideration, the Maximum Likelihood Estimator of pattern parameters is first obtained and then the Beliefs on each pattern is determined. Then using Bayes’ rule, Beliefs are updated recursively. Finally, when the amount of a derived statistic falls outside the calculated control interval a pattern recognition signal is issued. The advantage of this approach comparing with other existing CCP recognition methods is that it has no need for training. Simulation results show high accuracy and satisfactory speed of the proposed method.

In this paper, we consider scheduling of project networks under minimization of total weighted resource tardiness penalty costs. In this problem, we assume constrained resources are renewable and limited to very costly machines and tools which are also used in other projects and are not accessible in all periods of time of a project. In other words, there is a dictated ready date as well as a due date for each resource such that no resource can be available before its ready date but the resources are allowed to be used after their due dates by paying penalty costs depending on the resource type. We also assume, there is only one unit available of each resource type and no activity needs more than it for execution. The goal is to find a schedule with minimal total weighted resource tardiness penalty costs. For this purpose, we present a hybrid metaheuristic procedure based on the greedy randomized adaptive search algorithm and path-relinking algorithm. We develop reactive and non-reactive versions of the algorithm. Also, we use different bias probability functions to make our solution procedure more efficient. The computational experiments show the reactive version of the algorithm outperforms the non-reactive version. Moreover, the bias probability functions defined based on the duration and precedence relation characteristics give better results than other bias probability functions.