فصلنامه مطالعات مدیریت صنعتی
پیاپی 20 (بهار 1390)

By studying the literature of lean production concepts and according to the attempts made by the organization to measure and implement the principles of lean production, it is decided to take the two measure streams, regarding to lean production into deep consideration. The outcome of these studies can be condensed into two majorachievements: 1) to draw the readers’ attentions to comprehensive definition of leanness 2) To present a framework that can first measure then provide approaches to solve the difficulties in an appropriate implementing in a suitable accordance with thecomprehensive definition of leanness. Having achieved a right understanding of leanness concepts, the existing models were studied to measure organizational leanness. Having considered the strengths and weaknesses, a model was represented which is a combination of fuzzy ANP and fuzzy DEMATEL approaches. Finally, by conductingan experimental study the application of this model has been demonstrated.

On the networks existing servers and customers, each node indicates a customer demand and demand rate is estimated for them. The edges of the network indicate connective ways among the nods which is usually shown with the distance of two nods orthe time of travelling. In the covering location problems, the objective is locating some of the servers on the network in a way that the customer's demand supported by the maximum covering of the servers and optimized objective criterion. In this researchthe location model with Probability Structure, which the probability of choosing servers by customer is estimated based on their distance, is developed. In the presented model, supposing there is a competitive market, lost demand is considered, too. Andaccording to the mentioned matter the objective of the model is to minimize the cost of losing demands or to maximize the earned profits of responding to the demands. Then, we propose a genetic algorithm (GA) to solve this model. In addition, we employ designof experiments and response surface methodology to both tune the GA parameters and to evaluate the performance of the proposed method in 45 test problems. The results of the performance analysis show that the efficiency of the proposed GA method is very well.

In This paper, application of MCDM techniques in evaluation and ranking of Temad Co. strategies has been considered. Statistical target group, as "expert group" has been chosen among company's managers to identify strategies and evaluate them. At the first phase, strategies have been deducted with SWOT technique and at the second phase,they have been ranked by ELECTR III technique. Criteria for evaluating strategies gathered among different resources and got summarized according to strategic expert's ideas. Weight of criteria has determined by RTC or PCT technique and thresholds have been dedicated by decision makers. To reduce uncertainty of decision making, ranking has been done in fuzzy situation. Furthermore, for assessing efficiency of results, sensitivity analysis has been implemented with two approaches. According to final results,evaluation and ranking of strategies can be done well by means of ELECTRE III technique.

Different inventory control systems try to determine how much and when to order at the least relevant cost while maintaining a desirable service level for customers. In this article, a continuous review stochastic inventory system, with three objectives, is optimized. In this model, contrary to the traditional inventory models, customer serviceis not considered a shortage cost in the objective function. But the frequency of stock out occasions and the number of items stocked out annually are to be minimized. For determining the Pareto optimal set, multi-objective evolutionary algorithms are used. First, NSGA-II, MOGA, VEGA, RWGA are developed. Then some improvements in NSGA-II mechanisms are made and R-NSGA-II is developed. Subsequently, these algorithms are examined for some criteria such as set coverage and spacing, and the best algorithms for each criteria are presented. The Result shows that R-NSGA-II has good scores formost criteria. Afterwards, Pareto optimal set is ranked using the method of global criteria.

managers in organizations. In this paper an innovative model for calculating amount of incentive payments to employee has been proposed. Considering the multi criteria nature of assessing organization’s employees, this research propose a methodology toface this problem using multiple criteria decision making technique. To evaluating the effectiveness of this model, the suggested model has been implemented for an electromotor manufacturing company and the results has been mentioned in article. Considering the high ability of TOPSIS technique in solving the large scale (large number of alternatives and criteria), this technique will be used for computations. The suggested model has been used for five production departments (163 persons) in mentioned company and amount of incentive payment for each one of employees has been calculated.

One of the main steps in production planning is the operation sequencing. The operation sequencing is assessed by a series of efficiency indexes such as jobs completion average time, jobs maximum tardiness and jobs average tardiness. In order to accomplish these efficiency indexes, some heuristic rules or algorithms like Shortest Order Time are offered so that each rule minimizes some indexes. For instance, Shortest Order Time (SOT)minimizes the jobs fulfillment average time index and jobs maximum tardiness index is minimized by the Earliest Delivery Date rule (EDD). The fuzzy analytic hierarchy process selects the best jobs sequence from the existing sequences by considering the concurrent effects of all efficiency indexes and scores comparison. In the present paper, the efficiency indexes in operation sequencing selection and a brief description of the fuzzy analytic hierarchy process method and its manipulation are introduced. Then by considering the effect of all the efficiency indexes, the best sequence in a single machine shop is found among the existing sequences.

One of the most common problems, encountered in the quality of product industrial units, includes low level & high distribution of production quality specifications. The complexity of methods causes the manager not to be able to make the right decision for solving this problem. The Six Sigma methodology is a powerful tool for adjustingthe parameters of production processes & its optimization in order to make them competitive products. To be able to guide the quality changes of goods in the desirable direction, first we must become familiar with these changes & then we must recognize the reasons of their presence. In this regard, barcode system which has highcapabilities in increasing the speed & precision of data transfer can help the organization to reach a desirable level of sigma. The present article has attempted to familiarize the readers with the definition of six sigma methodology & how to use the barcode system to improve the sigma level in a case study. The quality improvement of productswhich is a result of optimized management of sigma level has resulted in achieving desirable economical goals for the organization. These goals have been assessed in the conclusion section.

New Product Development (NPD) and its significance for companies, as a new approach, have some risks, but the identification of key factors of this approach can be helpful in decreasing risks in managers’ decision-making. So in this research, it is tried throughlibrary studies and consulting with professors, managers and experts in departments related to product development in SAIPA Automobile Group to identify the key factors and their indicators as much as possible. So through pre-test from 12 experts, 4 key factors of technology, marketing, commercializing, and product developmentteam management were determined and the importance of indicators were identified and 5 important indicators were chosen for each factor and 21 reliable questionnaires were gathered from 23 managers and experts in related departments (product development strategy, technical and providing-parts and marketing departments) throughAnalytical Hierarchical Process test approach. After compatibility ratio test, ideas were put together and the importance of factors and indicators was determined through pair comparison. Therefore respectively, marketing factor with index of Special profits in product, product development team with index of work incentives, in factor oftechnology consistent with new products and commercial key factor with flexibility and attention to customer needs are the most important factors in the NPD process. So, knowing and determining the priority of these factors in gathering and implementing product development strategy accelerate and facilitate the success procedure and decrease the decision-making risk.

Identification and determination of products and their quantities according to available resources are called Product Mix Problem in manufacturing plants. There are many methods for solving these problems. One of these methods is Theory of Constraints which is easy to use and understand. But unfortunately, it can’t solve multi bottleneck problems, so it doesn’t have sufficient efficiency when introduce new product. Consequently Revised Theory of constraints was proposed to solve these problems. This is one of the best methods that provide the same results as ILP in most of the cases. But in this algorithm all parameters are certainty. However, in the real-world, such parameters like capacity and demands are uncertainty. In this situation, fuzzy set theory can be used as an effective tool. So In this paper, an algorithm based on RTOC and fuzzy logic is proposed for solving Product Mix Problems with fuzzy capacity and fuzzy demand.This algorithm is more flexible and popularized than other methods which are used for solving fuzzy product mix problems.