International Journal of Industrial Engineering & Production Research

  Abstract : In this study, we prepared a LaNi_0.3Al_0.7O₃ perovskite catalyst using a sol-gel related method (with prop ionic acid as a solvent) for use in the methane dry reforming reaction to produce synthesis gas. We defined the catalyst structure on the basis of X-ray diffraction analysis and measurements of the specific surface area and particle size distribution. The mixed oxide structure was shaped into a cylindrical pellet before being measured for its mechanical strength. The shaped perovskite catalyst was then tested in the methane dry reforming reaction to produce synthesis gas at atmospheric pressure. The results are compared with the predictions of a mathematical model that is used to estimate the concentration profile within the pellet. The outlet concentration of the reactants and conversion products calculated by the mathematical model has been consistent with the results obtained by experiments conducted in a fixed bed reactor.

  The advent of e-commerce has prompted many manufacturers to redesign their traditional channel structure by engaging in direct sales. In this paper, we present a dual channel inventory model based on queuing theory in a manufacturer-retailer supply chain, consisting of a traditional retail channel and a direct channel which stocks are kept in both upper and lower echelon. The system receives stochastic demand from the both channel which each channel has an independent demand arrival rate. A lost-sales model which no backorder is allowed is supposed. The replenishment lead times are assumed independent exponential random variables for both warehouse and the retail store. Under the replenishment inventory policy, the inventory position is kept constant at a base-stock level. To analyze the chain performance, an objective function included holding and lost sales costs is defined. At the end, a proposed algorithm named, Best Neighborhood (BN) is used to find a good solution for inventory and the results are compared with Simulated Annealing (SA) solutions.

In previous studies, active suspension system in conventional powertrain systems was investigated. This paper presents the application of active suspension system in parallel hybrid electric vehicles as a novel idea. The main motivation for this study is investigation of the potential advantages of this application over the conventional one. For this purpose, a simultaneous simulation is developed that integrates the powertrain and active suspension systems in a unified media where the power and input data between two systems are exchanged. Using this concurrent simulation tool, the impact of the active suspension load on the internal combustion engine response is studied for both conventional and hybrid electric configurations. The simulation results presented in this study show that there are quite remarkable advantages for application of the active suspension in parallel hybrid electric vehicles in comparison with the conventional one.

  In order to have better insight of project characteristics, different kinds of fuzzy analysis for project networks have been recently proposed, most of which consider activities duration as the main and only source of imprecision and vagueness, but as it is usually experienced in real projects, the structure of the network is also subject to changes. In this paper we consider three types of imprecision namely activity duration, activity existence and precedence relation existence which make our general fuzzy project network. Subsequently, a corrected forward recursion is proposed for analysis of this network. Since the convexity and normalization of traditional fuzzy numbers are not satisfied, some corrected algebraic operations are also presented. Employing the proposed method for a real project reveals that our method results in more applicable and realistic times for activities and project makespan in comparison to

The present paper aims to investigate the effects of modularity and the layout of subsystems and parts of a complex system on its maintainability. For this purpose, four objective functions have been considered simultaneously: I) maximizing the level of accordance between system design and optimum modularity design,II) maximizing the level of accessibility and the maintenance space required,III) maximizing the providing of distance requirement and IV) minimizing the layout space. The first objective function has been put forward for the first time in the present paper and in it, the optimum system modularity design was determined using the Design Structure Matrix (DSM) technique.The second objective function is combined with the concept of Level of Repair Analysis (LoRA) and developed. Simultaneous optimization of the above-mentioned objective functions has not been considered in previous studies. The multi objective problem which has been put forward was applied on a laser range finder containing 17 subsystems and the modularity and optimum layout was determined using a multi objective particle swarm optimization (MOPSO) algorithm.

Pricing and advertising are two important marketing strategies in the supply chain management which lead to customer demand’s increase and therefore higher profit for members of supply chains. This paper considers advertising, and pricing decisions simultaneously for a three-level supply chain with one supplier, one manufacturer and one retailer. The amount of market demand is influenced by pricing and advertising. In this paper, three well-known approaches in the game theory including the Nash, Stackelberg and Cooperative games are exploited to study the effects of pricing and advertising decisions on the supply chain. Using these approaches, we identify optimal decisions in each case for the supplier, the manufacturer and the retailer. Also, we compare the outcomes decisions among the mentioned games. The results show that, the Cooperative and the Nash games have the highest and lowest advertising expenditure, respectively. The price level in the Nash game is more than the Stackelberg game for all three levels, and the retailer price in the Stackelberg and Cooperative games are equal. The system has the highest profit in the Cooperative game. Finally, the Nash bargaining model will be presented and explored to investigate the possibilities for profit sharing.

Efficiency and effectiveness of the organization is result ofmanagement performance and supply chain structure.Today, several factors in selection the supplier or the best combination of suppliers have been identified that this issue would increase the complexity of suplier selecting.This study investigates the application of Fuzzy Delphi in order to identify the important factors in selecting a supplier in the steel industry and then provide a comprehensive and holistic model of supplier selection to overcome the complexity.In this context, Interpretive Structural Modeling (ISM) unlike other methods, the holistic, dealing with supplier selection to prioritize components-surfacing and identifying key components, so industry leaders will provide comperhensive map to select the best combination based on their.The results of this study indicate that "technically possible", "financial health" and "geography situation" are the basic components to the selection of suppliers.

This paper addresses a production and outbound distribution scheduling problem in which a set of jobs have to be process on a single machine for delivery to customers or to other machines for further processing. We assume that there is a sufficient number of vehicles and the delivery costs is independent of batch size but it is dependent on each trip. In this paper, we present an Artificial Immune System (AIS) for this problem. The objective is to minimize the sum of the total weighted number of tardy jobs and the batch delivery costs. A batch setup time has to be added before processing the first job in each batch. Using computational test, we compare our method with an existing method for the mentioned problem in literature namely Simulated Annealing (SA). Computational tests show the significant improvement of AIS over the SA.

Due to the particular importance of projects in human life and in organizations, proper project management has been always regarded highly by researchers and practitioners. Recent advances in technology and fundamental changes in most scientific areas have affected projects and made their nature and environmental circumstances much more complex than in the past. Fortunately, in recent years, many scholars have recognized the importance of complexity in modern project management and tried to identify its various aspects. Furthermore, one of the main factors for a project’s success is the assignment of an appropriate project manager. Many studies have been done about project managers' competencies and the selection methods of a suitable project manager. In most of these researches, the amount and type of project complexity have been explained as influential factors for determining the competent project manager. However, a specific approach for project manager selection considering the complexity of projects is not provided yet. Hence, in this paper we try to design and implement a fuzzy group decision making approach to allocate the best project manager taking into account the project complexity. Also, owing to the importance of construction projects in the development of countries' basic infrastructures, we exclusively studied this kind of projects. Finally, it should be noted that from the viewpoint of complexity theory, system complexity can exist in two forms: static and dynamic. Therefore, considering the breadth of issues related to each of these two complexity areas, just the static complexity of construction projects has been studied here.

Empirical studies show that there is stronger dependency between large losses than large profit in financial market, which undermine the performance of using symmetric distribution for modeling these asymmetric. That is why the assuming normal joint distribution of returns is not suitable because of considering the linier dependence, and can be lead to inappropriate estimate of VaR. Copula theory is basic tool for multivariate modeling, which is defined by using marginal and dependencies between variables joint distribution function. In addition, Copulas are able to explain and describe of complex multiple dependencies structures such as non-linear dependence. Therefore, in this study, by combining symmetric and asymmetric GARCH model for modeling the marginal distribution of variables and Copula functions for modeling financial data and also use of DCC model to determine the dynamic correlation structure between assets, try to estimate the Value at Risk of investment portfolio consists of five active index In Tehran Stock Exchange. The results demonstrate excellence of GJR-GARCH(1,1) with the distribution of t-student for marginal distribution. t-Copula model, estimates the Value at Risk model less than the Gaussian Copula in all cases.

In the current study, a dual-channel supply chain is considered containing one manufacturer and two retailers. It is assumed that the manufacturer and retailers have the same decision powers. A game-theoretic approach is developed to analyze pricing decisions under the centralized and decentralized scenarios. First, the Nash model is established to obtain the equilibrium decisions in the decentralized case. Then, the centralized model is developed to maximize the total profit of the whole system. Finally, the equilibrium decisions are discussed and some managerial insights are revealed. 

This paper considers the advertising, pricing, and service decisions simultaneously to coordinate the supply chain with a manufacturer and a retailer. The amount of market demand is influenced by advertising, pricing and service decisions. In this paper, three well-known approaches to the game theory, including the Nash, the Stackelberg-retailer, and the cooperative game are exploited to study the effects of these policies on the supply chain. Using these approaches, we identify optimal strategies in each case for the manufacturer and the retailer. Then, we will compare the outcomes of each strategy thus developed. The results show that, compared with the Nash game, the Stackelberg-retailer game yields higher profits for the retailer, the manufacturer, and the whole system. The cooperative game yields the highest profits. Finally, the Nash bargaining model will be presented and explored to investigate the possibilities for profit sharing.

The area coverage of machines on the production line to address the scheduling and routing problem of autonomous guided vehicles (AGV) is an innovative way to improve productivity in manufacturing enterprises. This paper proposed a new model for the optimal area coverage of machines in the production line by applying a single AGV to minimize both the transfer costs and the number of breakpoints of AGV. One of the unique advantages of the area coverage employed in the present study is that it minimizes transfer costs and breakpoints, and makes it possible to provide service for several machines simultaneously since the underlying assumption was finding a path to ensure that every point in a given workspace is covered at least once. Since rail AGV is used in this study, AGV can only pass horizontal and vertical distances in the production line. The reversal of the AGV path in vertical and horizontal distances implies failure and breakpoint in the present paper. The simulation results confirm the feasibility of the proposed method.