International Journal of Industrial Engineering & Production Research

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  In this paper, authors tackle three very important questions that need to be answered if a theory of design is to be constructed. The first is what designers do, Which we attempt to illustrate with the help of case studies and theories of design practice. The second question is what guides designers. Here, authors try to present some of the proposed normative positions about design, to show the similarities and differences between positions and a framework of how they can be categorized. The main (third) question is how the design thinking process can be represented drawing upon on a review of recent studies of design practice and designer's creativity.

  One approach to design thinking is to extract the features of the designers' strategic knowledge, for which comparative studies between expert designers and novices are useful. Also, controlled experimental studies may be adopted in order to understand the nature of the idea generation process.

Finally, the methods of research and representation of design thinking in order to gain a deeper understanding of the designers' creativity are proposed .

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When a specific building is examined and analysed for its architectural merits, it is the visible, superficial aspects, which are considered, for example: aesthetics, function, spatial relationships, and landscape. One of the most important invisible factors that should be considered in the design process is the safety of buildings against natural hazards, particularly against earthquakes. While the provision of earthquake resistance is accomplished through structural means, the architectural designs and decisions play a major role in determining the seismic performance of a building. In other words, the seismic design is a shared architectural and engineering responsibility, which stems from the physical relationship between architectural forms and structural systems. It is economic to incorporate earthquake resistance in the stage of design than to add it later in the structural calculation or strengthening after completion. In addition, a building with proper earthquake-proof design will be more effective against earthquakes than the one with complementary strengthening. This paper will demonstrate that evidence for this lies in many historical buildings, which have withstood earthquakes throughout the hundreds of years without having been reinforced with special material. The fact is that the master builder or Mimar (traditional architect) of historic buildings was simultaneously designing the architecture as well as choosing the suitable form, proportion, and material for the best structural performance.

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The present paper will investigate the specific elements of architectural design based on Islamic beliefs, by taking Iranian Architectural values and vernacular climate design methods into consideration. This research will assess the spirit of experimental elements, created by the inhabitants, according to recent scientific findings. The main concentration will be on the physical design of rural areas in hot, arid and sunny regions of Iran in order to have active and healthy environments and to emphasize on transferring all these sustainable values to the future.

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Mobile mechanical manipulators are one of the automation aspects which were revealed in last years of twentieth century. These machines assume the responsibility of human and gradually expand the domain of their activities in industry. This paper is a presentation of the Sweeper Robot designed in the Robotic Laboratory of Iran University of Science and Technology. The original design of this robot allowing to its gripper to constantly remain parallel to the ground is presented. The dynamic and kinematical models of the robot have been computed. A software was developed in MATLAB to validate the kinematical and dynamic models of the robot by comparison with the experimental results. Once the robot was built and its systematic odometric error estimated by experiment, a control scheme for linear motions was developed to deal with this error. The approach is based on the introduction of an initial rectifying offset motion before starting the linear motion. Eventually, classical line tracking and image processing algorithms were used to complete our robot and the efficiency of our design to achieve its mission in picking and placing different objects according to various algorithms.

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Hub covering location problem, Network design,   Single machine scheduling, Genetic algorithm,   Shuffled frog leaping algorithm

Hub location problems (HLP) are synthetic optimization problems that appears in telecommunication and transportation networks where nodes send and receive commodities (i.e., data transmissions, passengers transportation, express packages, postal deliveries, etc.) through special facilities or transshipment points called hubs. In this paper, we consider a central mine and a number of hubs (e.g., factories) connected to a number of nodes (e.g., shops or customers) in a network. First, the hub network is designed, then, a raw materials transportation from a central mine to the hubs (i.e., factories) is scheduled. In this case, we consider only one transportation system regarded as single machine scheduling. Furthermore, we use this hub network to solve the scheduling model. In this paper, we consider the capacitated single allocation hub covering location problem (CSAHCLP) and then present the mixed-integer programming (MIP) model. Due to the computational complexity of the resulted models, we also propose two improved meta-heuristic algorithms, namely a genetic algorithm and a shuffled frog leaping algorithm in order to find a near-optimal solution of the given problem. The performance of the solutions found by the foregoing proposed algorithms is compared with exact solutions of the mathematical programming model .

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  This paper demonstrates a preliminary investigation of geometry, function and its relation to DFX principles, namely DFM (Design for Manufacturing). This is the starting point for research on the development of an expert system that assesses design goals along DFX principles in a feature-based CAD environment. There is a need for a deeper level of understanding of the relationship between geometry and its effects on function, in order to correct and improve the product concept before large amounts of resources are invested in the product’s development.

This paper is a preliminary investigation into geometry and function involving DFM as part of an early stage of research into geometric effects on function and DFX through the use of CAD/CAE/CAM.In this paper, a concept is chosen to develop a parametric solid model that will be used to investigate a set of defined function attributes using model variants, which are evaluated in terms of the defined function attributes and DFM. The investigation found that for the functions defined, geometric parameters had less of an effect than expected. This is mainly due to the fact that the defined function attributes under investigation were associated with material properties. This paper demonstrates a preliminary investigation at the early stage of research to develop a more detailed relationship structure between geometry and functional attributes and their relationship with DFX. The end goal is to develop an integrated methodology involving geometry, function and DFX principles through the use of CAD/CAE/CAM .

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The Network Design Problem (NDP) is one of the important problems in combinatorial optimization. Among the network design problems, the Multicommodity Capacitated Network Design (MCND) problem has numerous applications in transportation, logistics, telecommunication, and production systems. The MCND problems with splittable flow variables are NP-hard, which means they require exponential time to be solved in optimality. With binary flow variables or unsplittable MCND, the complexity of the problem is increased significantly. With growing complexity and scale of real world capacitated network design applications, metaheuristics must be developed to solve these problems. This paper presents a simulated annealing approach with innovative representation and neighborhood structure for unsplittable MCND problem. The parameters of the proposed algorithms are tuned using Design of Experiments (DOE) method and the Design-Expert statistical software. The performance of the proposed algorithm is evaluated by solving instances with different dimensions from OR-Library. The results of the proposed algorithm are compared with the solutions of CPLEX solver.  The results show that the proposed SA can find near optimal solution in much less time than exact algorithm.

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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.

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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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Response surface methodology is a common tool in optimizing processes. It mainly concerns situations when there is only one response of interest. However, many designed experiments often involve simultaneous optimization of several quality characteristics. This is called a Multiresponse Surface Optimization problem. A common approach in dealing with these problems is to apply desirability function approach combined with an optimization algorithm to determine the best settings of control variables. As the response surfaces are often nonlinear and complex a number of meta-heuristic search techniques have been widely for optimizing the objective function. Amongst these techniques genetic algorithm, simulated annealing, tabu search and hybridization of them have drawn a great deal of attention so far. This study presents the use of harmony search algorithm for Multiresponse surface optimization. It is one of the recently developed meta heuristic algorithms that has been successfully applied to several engineering problems. This music inspired heuristic is conceptualized from the musical process of searching for a perfect state of harmony. The performance of the algorithm is evaluated by an example from the literature. Results indicate the efficiency and outperformance of the method in comparison with some previously used methods.

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control of production processes in an industrial environment needs the correct setting of input factors, so that output products with desirable characteristics will be resulted at minimum cost. Moreover, such systems havetomeetset of qualitycharacteristicstosatisfycustomer requirements.Identifyingthemosteffectivefactorsindesignoftheprocesswhichsupportcontinuousandcontinualimprovement isrecentlydiscussedfromdifferentviewpoints.Inthisstudy, we examined the quality engineering problems in which several characteristics and factors are to be analyzed through a simultaneous equations system. Besides, the several probabilistic covariates can be included to the proposed model. The main purpose of this model is to identify interrelations among exogenous and endogenous variables, which give important insight for systematic improvements of quality. At the end, the proposed approach is described analytically by a numerical example.

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The main advantage of heuristic or metaheuristic algorithms compared to exact optimization methods is their ability in handling large-scale instances within a reasonable time, albeit at the expense of losing a guarantee for achieving the optimal solution. Therefore, metaheuristic techniques are appropriate choices for solving NP-hard problems to near optimality. Since the parameters of heuristic and metaheuristic algorithms have a great influence on their effectiveness and efficiency, parameter tuning and calibration has gained importance. In this paper a new approach for robust parameter tuning of heuristics and metaheuristics is proposed, which is based on a combination of Design of Experiments (DOE), Signal to Noise (S/N) ratio, Shannon entropy, and VIKOR methods, which not only considers the solution quality or the number of fitness function evaluations, but also aims to minimize the running time. In order to evaluate the performance of the suggested approach, a computational analysis has been performed on the Simulated Annealing (SA) and Genetic Algorithms (GA) methods, which have been successfully applied in solving respectively the n-queens and the Uncapacitated Single Allocation Hub Location combinatorial problems. Extensive experimental results showed that by using the presented approach the average number of iterations and the average running time of the SA were respectively improved 12 and 10.2 times compared to the un-tuned SA. Also, the quality of certain solutions was improved in the tuned GA, while the average running time was 2.5 times faster compared to the un-tuned GA.

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This paper mainly focuses the study and analysis of the existing contributions related to the Biodiesel production. It, firstly, discuss the key issues related contributions which include chemical process, reactor designing, plantation, blending and applications. Next, it summarizes the analysis of the other prominent contributions related to process model, design, production, cost, optimization, feasibility, safety, effects, challenges and future of the Biodiesel. It also presents the discussion on the open issues in Biodiesel. Secondly, an approach is suggested for the design of the Biodiesel manufacturing plant in view of cost and capacity. The suggested approach is based on the mathematical model. This paper provides the brief study of Biodiesel production and plant design and it can be helpful to the beginners in the domain of renewable energy research.

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The set covering problem (SCP) is a well-known combinatorial optimization problem. This paper investigates development of a local branching approach for the SCP. This solution strategy is exact in nature, though it is designed to improve the heuristic behavior of the mixed integer programming solver. The algorithm parameters are tuned by design of experiments approach. The proposed method is tested on the several standard instances. The results show that the algorithm outperforms the best heuristic approaches found in the literature.

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In this study, an optimization model is proposed to design a Global Supply Chain (GSC) for a medical device manufacturer under disruption in the presence of pre-existing competitors and price inelasticity of demand. Therefore, static competition between the distributors’ facilities to more efficiently gain a further share in market of Economic Cooperation Organization trade agreement (ECOTA) is considered. This competition condition is affected by disruption occurrence. The aim of the proposed model is to maximize the expected net after-tax profit of GSC under disruption and normal situation at the same time. To effectively deal with disruption, some practical strategies are adopted in the design of GSC network. The uncertainty of the business environment is modeled using the robust optimization technique based on the concept of uncertainty budget. To tackle the proposed Mixed-Integer Nonlinear Programming (MINLP) model, a hybrid Taguchi-based Memetic Algorithm (MA) with an adaptive population size is developed that incorporates a customized Adaptive Large Neighborhood Search (ALNS) as its local search heuristic. A fitness landscape analysis is used to improve the systematic procedure of neighborhood selection in the proposed ALNS. A numerical example and computational results illustrate the efficiency of the proposed model and algorithm in dealing with global disruptions under uncertainty and competition pressure.

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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.

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Flexible and dynamic supply chain network design problem has been studied by many researchers during past years. Since integration of short-term and long-term decisions in strategic planning leads to more reliable plans, in this paper a multi-objective model for a sustainable closed-loop supply chain network design problem is proposed. The planning horizon of this model contains multiple strategic periods so that the structure of supply chain can be changed dynamically during the planning horizon. Furthermore, in order to have an integrated design, several short-term decisions are considered besides strategic network design decision. One of these short-term decisions is determining selling price and buying price in the forward and reverse logistics of supply chain, respectively. Finally, an augmented e-constraint method is used to transform the problem to a single-objective model and an imperialist competitive algorithm is presented to solve large scale problems. The results’ analysis indicates the efficiency of the proposed model for the integrated and dynamic supply chain network design problem. 

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Recently, urbanization has been expanded rapidly in the world and a number of metropolitan areas have been appeared with a population of more than 10 million people. Because of dense population in metropolitan and consequently increasing the delivery of goods and services, there has been a lot of problems including traffic congestion, air pollution, accidents and high energy consumption. This made some complexities in distribution of urban goods; Therefore, it is essential to provide creative solutions to overcome these complexities. City logistics models can be effective in solving these complexities.

In this paper, concepts and definitions related to city logistics are explained to provide a mathematical model in order to design city logistics distribution network aim at minimizing response times. This objective is effective for goods and emergency services, especially in times of crisis and also for goods that are delivered as soon as possible. This is a three-level network and has been used in modeling of queuing theory. To validate the model, a numerical example has been established and results of the model have been explained using BARON solver in Gams software. Finally, conclusions and recommendations for future research are presented.

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A teaching-learning-based optimization (TLBO) algorithm is a new population-based algorithm applied in some applications in the literature successfully. Moreover, a genetic algorithm (GA) is a popular tool employed widely in many disciplines of engineering. In this paper, a hybrid GA-TLBO algorithm is proposed for the capacitated three-stage supply chain network design (SCND) problem. The SCND problem as a strategic level decision-making problem in supply chain management is an NP-hard class of computational complexity. To escape infeasible solutions emerged in the problem of interest due to realistic constraints, combination of a random key and priority-base encoding scheme is also used. To assess the quality of the proposed hybrid GA-TLBO algorithm, some numerical examples are conducted. Then, the results are compared with the GA, TLBO, differential evolution (DE) and branch-and -bound algorithms. Finally, the conclusion is provided.

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CCC-r control chart is a monitoring technique for high yield processes. It is based on the analysis of the number of inspected items until observing a specific number of defective items.  One of the assumptions in implementing CCC-r chart that has a significant effect on the design of the control chart is that the inspection is perfect. However, in reality, due to the multiple reasons, the inspection is exposed to errors. In this paper, we study the economic-statistical design of CCC-r charts when the inspection is imperfect. Minimization of the average cost per produced item is considered as the objective function. The economic objective function, modified consumer risk, and modified producer risk are simultaneously considered, and then the optimal value of r parameter is selected.