International Journal of Industrial Engineering & Production Research

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At the last decade of the 20^th century, Womack et. Al introduced Lean concept to the industrial world. Since 1990 up to now, existed studies mostly have focused on lean production in the step of manufacturing, but in this research leanness concept has developed in the plant life cycle. In this paper leanness concept will be described as elimination of wastes in the phases of investment, plant design & construction(hardware), organization & systems design (software) and these three steps will be added to, elimination of previously described  seven wastes in production step. For this purpose at first, the types of wastes in the above mentioned phases are defined by using Axiomatic Design methodology. After defining the types of wastes, a model for assessment of leanness is submitted. In this quantitative model, amount of leanness in each phase will be determined and combined to make a unique measure for total leanness. Dimensions of leanness are shown for quick understanding, by using a spider diagram. In the last section of the paper, the results of an example of the application of this model in fan industry are brought. This example shows the simplicity and powerfully of the model to determine the leanness in before production phases. © 2008 Authors all rights reserved.

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Nowadays total joint replacements are widely used in the world, so in average 800,000 joint surgeries are done yearly only in Europe and North America. However implant loosening is and remains as the major issue of all implant failures and therefore causes revision surgery procedures. Studies and experiments have identified poor fixation of implants most likely is the main cause of long term implant failure and in this case the cement-implant interface cavities are very effective due to resultant stress concentration . In this study the theory of this problem, continuum and mathematical equations for an inhomogeneous material by using Eshelby’s equivalent inclusion method with a spherical void as a special type of inhomogenities is addressed and a new yield criterion with respect to the void’s volume fraction is derived and changes in material elasticity tensor concerning Mori-Tanaka’s theorem also determined, then by using finite element method and remeshing technique a macro scale cement-implant interface cavity is modeled and concerning the loss of strength due to void existence and the interface stress concentration, the crack initiation and propagation phenomenon is numerically investigated with respect to different orthopedic cement material properties. The results show that crack propagates at the interface at constant stress and strain by elastoplastic material and it propagates in cement bulk by considering elastic material properties for cement that both could cause implant loosening even in very small void’s volume fractions in which there are no significant changes in cement yield stress and elasticity tensor according to analytical solution. But numerical simulation shows that when a homogenous cement structure is achieved via high vacuum mixing method, there is a uniform stress distribution in the cement structure and no stress concentration zone forms even at high stress levels and also there is no appropriate local site for crack initiation.

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  Selecting an effective project plan is a significant area in the project management. The present paper introduces a technique to identify the project plan efficient frontier for assessing the alternative project plans and selecting the best plan. The efficient frontier includes two criteria: the project cost and the project time. Besides, the paper presents a scheme to incorporate Directed Acyclic Graph (DAG) into the project risk analysis.

This scheme is used to estimate the expected impacts of the occurrence of the project risks on the project cost and the project time. Also, a theoretical model is defined to provide integration between project risk analysis and overall project planning using the breakdown structures. We believe that applying the proposed technique helps the company’s managers in most effective manner dealing with his complicated project plan assessment and selection problems. The application of the technique was implemented in the companies in construction industry in which represented a considerable cost and time improvements.

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The Materials Requirements Planning (MRP) method that is applied in production planning and management has some weaknesses. One of its weaknesses is that the time in MRP method is discrete, and is considered as time period. Hence we are not able to order our requirements at irregular time moments or periods. In this paper, a new form of MRP is introduced that is named Continuous Materials Requirements Planning (CMRP) approach. We discuss the disadvantages of Discrete MRP (DMRP) approach and analyze the conditions, applications and the manner of applying CMRP approach in our problems.

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  Omni directional mobile robots have been popularly employed in several applications especially in soccer player robots considered in Robocup competitions. However, Omni directional navigation system, Omni-vision system and solenoid kicking mechanism in such mobile robots have not ever been combined. This situation brings the idea of a robot with no head direction into existence, a comprehensive Omni directional mobile robot. Such a robot can respond more quickly and it would be capable for more sophisticated behaviors with multi-sensor data fusion algorithm for global localization base on the data fusion. This paper has tried to focus on the research improvements in the mechanical, electrical and software design of the robots of team ADRO Iran. The main improvements are the world model, the new strategy framework, mechanical structure, Omni-vision sensor for object detection, robot path planning, active ball handling mechanism and the new kicker design, , and other subjects related to mobile robot .

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Dynamic cellular manufacturing systems,   Mixed-integer non-linear programming,   Production planning, Manufacturing attributes

This paper presents a novel mixed-integer non-linear programming model for the design of a dynamic cellular manufacturing system (DCMS) based on production planning (PP) decisions and several manufacturing attributes. Such an integrated DCMS model with an extensive coverage of important design features has not been proposed yet and incorporates several manufacturing attributes including alternative process routings, operation sequence, processing time, production volume of parts, purchasing machine, duplicate machines, machine depot, machine capacity, lot splitting, material flow conservation equations, inflation coefficient, cell workload balancing, budget constraints for cell construction and machine procurement, varying number of formed cells, worker capacity, holding inventories and backorders, outsourcing part-operations, warehouse capacity, and cell reconfiguration. The objective of the integrated model is to minimize the total costs of cell construction, cell unemployment, machine overhead and machine processing, part-operations setup and production, outsourcing, backorders, inventory holding, material handling between system and warehouse, intra-cell and inter-cell movements, purchasing new machines, and machine relocation/installation/uninstallation. A comprehensive numerical example taken from the literature is solved by the Lingo software to illustrate the performance of the proposed model in handling the PP decisions and to investigate the incorporated manufacturing attributes in an integrated DCMS .

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 In this paper a single server queuing production system is considered which is subject to gradual deterioration. The system is discussed under two different deteriorating conditions. A planning horizon is considered and server which is a D/M/1 queuing system is gradually deteriorates through time periods. A maintenance policy is taken into account whereby the server is restored to its initial condition before some distinct periods. This system is modeled to obtain optimal values of arrival rates and also optimal maintenance policy which minimizes production, holding and maintenance costs and tries to satisfy demands through time periods. The model is also considered to control customers’ sojourn times. For each deteriorating condition a model is developed. Models are solved by GA based algorithms and results for a sample are represented .

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One of the most important issues in urban planning is developing sustainable public transportation. The basic condition for this purpose is analyzing current condition especially based on data. Data mining is a set of new techniques that are beyond statistical data analyzing. Clustering techniques is a subset of it that one of it’s techniques used for analyzing passengers’ trip. The result of this research shows relations and similarities in different segments that its usage is from strategic to tactical and operational areas. The approach in transportation is completely novel in the part of trip patterns and a novel process is proposed that can be implemented in highway analysis. Also this method can be applied in traffic and vehicle treats that need automatic number plate recognition (ANPR) for data gathering. A real case study has been studied here by developed process.

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The analytic center cutting plane method (ACCPM) is one of successful methods to solve nondifferentiable optimization problems. In this paper ACCPM is used for the first time in the vehicle routing problem with time windows (VRPTW) to accelerate lagrangian relaxation procedure for the problem. At first the basic cutting plane algorithm and its relationship with column generation method is clarified then the new method based on ACCPM is proposed as a stabilization technique of column generation (lagrangian relaxation). Both approaches are tested on a benchmark instance to demonstrate the advantages of proposed method in terms of computational time and lower bounds quality.

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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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In this paper we develop a new approach for land leveling in order to improve the topology of a large area for irrigation or civil projects. The objective in proposed model is to minimize the total volume of cutting so that technical requirements of land leveling such as suitable slope and standard ratio of cutting to filling and maximum penstock point’s height are considered. We develop a warped surface pattern and apply a linear programming model to determine the land optimal topology. Our approach is more practical to apply, in comparison with the existing “fit to plane” methods which apply bivariate regression statistical techniques because in these methods finding optimal solution, considering technical requirements, needs trial and error. Our proposed method does not need any trial and error, furthermore its results is global optimum. Also the warped surface pattern is adoptable to plane or curved patterns, and it is applicable for any land with any magnitude.

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Data envelopment analysis (DEA) and balanced scorecard (BSC) are two well-known approaches for measuring performance of decision making units (DMUs). BSC is especially applied with quality measures, whereas, when the quantity measures are used to evaluate, DEA is more appropriate. In the real-world, DMUs usually have complex structures such as network structures. One of the well-known network structures is two-stage processes with intermediate measures. In this structure, there are two stages and each stage uses inputs to produce outputs separately where the first stage outputs are inputs for the second stage. This paper deals with integrated DEA and game theory approaches for evaluating two-stage processes. In addition, it is an extension of DEA model based on BSC perspectives. BSC is used to categorize the efficiency measures under two-stage process. Furthermore, we propose a two-stage DEA model with considering leader-follower structure and including multiple sub stages in the follower stage. To determine importance of each category of measures in a competitive environment, cooperative and non-cooperative game approaches are used. A case study for measuring performance of power plants in Iran is presented to show the abilities of the proposed approach.

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In any supply chain, distribution planning of products is of great importance to managers. With effective and flexible distribution planning, mangers can increase the efficiency of time, place, and delivery utility of whole supply chain. In this paper, inventory routing problem (IRP) is applied to distribution planning of perishable products in a supply chain. The studied supply chain is composed of two levels a supplier and customers. Customers’ locations are geographically around the supplier location and their demands are uncertain and follow an independent probability distribution functions. The product has pre-determined fixed life and is to be distributed among customers via a fleet of homogenous vehicles. The supplier uses direct routes for delivering products to customers. The objective is to determine when to deliver to each customer, how much to deliver to them, and how to assign them to vehicle and routes. The mentioned problem is formulated and solved using a stochastic dynamic programming approach. Also, a numerical example is given to illustrate the applicability of proposed approach.

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Achieving optimal production cycle time for improving manufacturing processes is one of the common problems in production planning. During recent years, different approaches have been developed for solving this problem, but most of them assume that mean quality characteristic is constant over production run length and sets it on customer’s target value. However, the process mean may drift from an in-control to an out-of-control at a random point in time. This study aims to select the production cycle time and the initial setting of mean quality characteristic, so that the expected total cost, consisting of quality loss and maintenance costs as well as ordering and holding costs, already considered in the classic models is minimized. To investigate the effect of mean process setting, a computational analysis on a real world example is performed. Results show the superiority of the proposed approach compared to the classical economic production quantity model.

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The locomotive assignment and the freight train scheduling are important problems in railway transportation. Freight cars are coupled to form a freight rake. The freight rake becomes a train when a locomotive is coupled to it. The locomotive assignment problem assigns locomotives to a set of freight rakes in a way that, with minimum locomotive deadheading time, rake coupling delay and locomotive coupling delay all freight rakes are hauled to their destinations. Scheduling freight trains consists of sequencing and ordering freight trains during the non-usage time between passenger trains but with no interference and with minimum delay times. Solving these two problems simultaneously is of high importance and can be highly effective in decreasing costs for rail transportation. In this paper, we aim to minimize the operational costs for the locomotive assignment and the freight train scheduling by solving these two problems concurrently. To meet this objective, an efficient and effective algorithm based on the ant colony system is proposed. To evaluate the performance of the proposed solution method, twenty-five test problems, which are based on the conditions of Iran Railways, are solved and the computational results are reported.

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Managing income is a considerable dimension in supply chain management in current economic atmosphere. Real world situation makes it inevitable not to design or redesign supply chain. Redesign will take place as costs increase or new services for customers’ new demands should be provided. Pricing is an important fragment of Supply chain due to two reasons: first, represents revenue based each product and second, based on supply-demand relations enables Supply chain to provide demands by making suitable changes in facilities and their capacities. In this study, Benders decomposition approach used to solve multi-product, multi-echelon and multi-period supply chain network redesign including price-sensitive customers.

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Resource planning in large-scale construction projects has been a complicated management issue requiring mechanisms to facilitate decision making for managers. In the present study, a computer-aided simulation model is developed based on concurrent control of resources and revenue/expenditure. The proposed method responds to the demand of resource management and scheduling in shell material embankment activities regarding large-scale dam projects of Iran. The model develops a methodology for concurrent management of resources and revenue/expenditure estimation of dam's projects. This real-time control allows managers to simulate several scenarios and adopt the capability of complicated working policies. Results validation shows that the proposed model will assist project managers as a decision support tool in cost-efficient executive policymaking on resource configuration.