The improvement in manufacturing process is never ending effort, which is being derived by the culture of the organization. Therefore, an attitude of perfection, innovation and devotion is an essential part for the process improvement of an organization. Recently, innovations in the field of engineering help an entrepreneur sell the products through competitive environment. Moreover, the timely delivery of goods and cost effective product is the yardstick, which contributes to the performance index. These improvements resulted from continued performance enhancement efforts, helps in producing right quality in the right times which means providing stability to the organization performance. The role of lean thinking and supply chain characteristics is to create an effective marked on the organizational performance including bonding of all the participants where-so-ever possible. The purpose of this work is to examine the challenges, which integrate the Lean Principles to Supply Chain Characteristics for the real world situation to achieve better utilization of resources, timely delivery to the customer, and deletion of non-value added items including the control on all type of wastages as linked with supply chain systems.

The evaluation of the most appropriate flexibility in the manufacturing sector is one of the strategic issues that may affect the Flexibile Manufacturing System (FMS). In this paper, a Multiple Attribute Decision Making Method (MADM) methodology is structured to resolve this problem. The two decision making methods, which are Simple Additive Weighting (SAW) and Weighted Product Method (WPM), are integrated with Analytical hierarchy process (AHP) in order to get the best use of information available. The aim of using AHP is to give the weights of the attributes and these weights are used in SAW & WPM method for ranking of flexibility in FMS. Furthermore, the method uses fuzzy logic to change the qualitative attributes into the quantitative attributes. 15 factors are taken to evaluation of 15 flexibility. In this report, we concluded that Product Flexibility has the most impact in 15 flexibilities and Programme Flexibility has the least impact in these 15 flexibilities by this methodology.

Global supply chains have to manage production over the whole world. Therefore, production plants are needed to supply the demand of products and parts. Due to complication and uncertainty of production market, portfolio selection is one of the most challenging problems. Type-2(T2) fuzzy is a model, which provides the ability to handle the effect of uncertainty. Aiming at this problem, we propose a T2 supplier management system operation scheme, which not only employs fuzzy C-Means clustering algorithm by dynamically increasing cluster center, but also it achieves good classification performance. The key result is that fuzzy classification applications improve the planning and operating of supply and demand in a distributed production and global supply chain.

This paper presents an empirical investigation to measure the performance of a mining firm in province of Semnan, Iran based on fuzzy fuzzy Decision Making Trial and Evaluation Laboratory (DEMATEL) technique. The proposed study of this paper uses strength, weakness, opportunity and threat (SWOT) technique to analyze the firm and using DEMATEL rank various items based on their relative importance. Based on the results of our survey, cost reduction and increase investment in mining sector are the most important components of this survey. The study also compares the results with similar study, which has recently been accomplished and we believe the proposed model is capable of detecting possible threats and helping us provide possible actions.

The objective of this study is to measure the performance improvement of supply chain (SC) stages through implementing the national standardization system (NSS) in an innovative way. There are many studies on the positive effects of standardization system on supply chain performance (SCP), but very few studies have measured and prioritized the impact of this system on SCP. This paper introduces a new approach to the performance improvement of each stage of SC through implementing the NSS. First, we use fuzzy analytical hierarchical process method to measure the relative importance of each stage and determine the characteristics of SC. Then, the amount of SC stages improvement after implementing the NSS is determined. Finally, using a combination of results, the stages of SC are ranked according to the effectiveness of NSS implementation. In order to validate the proposed approach, the case analysis of Iran NSS is carried out on broiler SC. The stages of SC are ranked according to the performance improvement through implementing standardization system, subsequently. This approach can be generalized to other standardization systems and SCs.

There is an ongoing change on customers’ needs on selecting customers’ needs, which may influence requirements on designing products and services as well as export sale and company’s market shares in domestic and international market. In the present study, through descriptive approach with qualitative method and case study, we investigate important key factors influencing on new product development and products’ successive factors at overseas nutritional market. In addition by presenting a new model in accordance with the present condition of the organization we explore the closest product development model and affective factors influencing them. The study investigates 36 factors and extracts six important ones, which influence product development including intelligent information, process research and development, strategy introduced, participation strategy, market survey and differentiation strategy.

In this paper, we have modeled a decision making problem of a tea industry as a multi-objective optimization problem in interval environment. The goal of this problem is to maximize the overall profit as well as to minimize the total production cost subject to the given resource constraints depending on budget, storage space and allotted processing times in different machines. For this purpose, the problem has been formulated as a multi-objective integer linear programming problem with interval objectives. To solve the problem, we have proposed extended elitist non-dominated sorting genetic algorithm (ENSGA-II) for integer variables with interval fitness, crowded tournament selection, intermediate crossover, one neighborhood mutation and elitism. To develop this algorithm, we have proposed modified non-dominated sorting and crowding distance based on interval mathematics and interval order relations. Finally, to test the performance of the proposed algorithm, a numerical example has been solved.

The fatigue failure around rail-end-bolt holes is particularly dangerous since it leads to derailment of trains and consequently to inevitable accidents. It is well-known that the fatigue life of structural holed components, subjected to cyclic load, can be increased by generating compressive hoop stresses around the holes. These beneficial residual compressive stresses significantly reduce the maximum values of the operating tensile stresses arising at the critical points of the components and thus impede the formation of first mode cracks. A new approach to enhancement of fatigue life of rail-end-bolt holes has been developed. The approach involves sequential drilling and reaming through a new combined tool and then slide diamond burnishing by a new device. The technology implementation was carried out on machine tool. The process of creating residual stresses has been studied both experimentally and numerically. The experimental study was conducted by means of a modified split ring method. A reliable finite element modeling approach to the slide diamond burnishing process was developed. On this basis, the process was optimized by means of a genetic algorithm. As a result, the optimal combination of the governing process parameters is established, which ensures both maximum depth of the compressive zone and maximum absolute values of the residual stresses.

Ranking industry normally helps find hot sectors and attract potential investors to invest in appropriate plans. Ranking various industries is also a multiple criteria decision making problem. In this paper, we present an empirical investigation to rank different industries using the art of data envelopment analysis (DEA). The inputs of our proposed DEA model include capital, employment and importance coefficient and outputs are exports, ecological effects and added value. In addition, exports, value added and environmental investment are used as outputs of DEA method. Since the results of DEA may consider more than one efficient unit, so we implement Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) technique to rank efficient units. In our case study, there were 15 different sectors from various industries and the implementation of DEA technique recommends 8 efficient units. The implementation of TOPSIS among these efficient units has suggested that Chemical industry could be considered as the most attracting industry for investment.

Contractor selection plays essential role on development of business industries and any selection strategy is normally involved with various factors. This paper presents an empirical investigation to determine important factors influencing contractor selection to increase profitability. The proposed model of this paper is implemented for an Iranian constructor firm named Kayson Company located in city of Tehran, Iran. The study has been accomplished among top managers who worked for this firm. Using structural equation modeling, the study determines that five factors including performance, believes, flexibility, quality, price and services influence on profitability when a contractor is to be chosen.