Journal Of Industrial Engineering International
Volume:5 Issue: 1, Jan 2009

The paper presents a multi-factor decision-making approach for prioritizing failure modes as an alternative to traditional approach of failure mode and effect analysis (FMEA). The approach is based on the ‘technique for order preference by similarity to ideal solution’ (TOPSIS). The priority ranking is formulated on the basis of six parameters (failure occurrence, non-detection, maintainability, spare parts, economic safety and eco-nomic cost). The Shannon`s entropy concept has been used for assigning objective weights to maintenance pa-rameters. The application of the approach has been reported with an actual case from a paper industry to illus-trate the use of the proposed methodology.

In a robust parameter design (RPD) problem, the experimenter is interested to determine the values of con-trol factors such that responses will be robust or insensitive to variability of the noise factors. Response sur-face methodology (RSM) is one of the effective methods that can be employed for this purpose. Since quality of products or processes is usually evaluated through several quality characteristics or responses, more atten-tion should be paid to multi-response parameter design to improve quality of several responses simultane-ously. There are many optimization methods in multi-objective decision-making (MODM) area which could be used for this purpose. In this article, some of these optimization techniques are reviewed and a criterion is considered to determine the optimum control setting factors for multi-response RPD problems. A sensitivity analysis is performed to investigate the effect of different scenarios on the solution.

This paper discusses the simulation study carried out for proposing one-piece lean line layout with features of Lean Manufacturing. The lean initiatives that can be addressed are, introducing Kanban replenishment sys-tem, better work-in-process, changing the layout, visual management techniques, standardized work for the re-duction of cycle time, number of workers, number of setups. To improve the layout in a pump manufacturing industry, VISIO 2007 and Pro Model-Process Simula tor Software are used. Pro Model simulation modeling software is a powerful yet easy-to-use simulation tools for modeling all types of systems and processes. Pro Model software is designed to model manufacturing systems ranging from small job shops and machining cells to large mass production, flexible manufacturing systems, and supply chain systems. The study has dis-cussed the lacuna in the existing flow line and has suggested a new one-piece lean line design using the simu-lation software. The validation is carried out by creating the wooden prototypes representing the cells and in-volving the workers to do the assembly of the pump. Standard time study charts are used to calculate the cycle time and change over time.

A tandem AGV configuration connects all cells of a manufacturing area by means of non-overlapping, sin-gle-vehicle closed loops. Each loop has at least one additional P/D station, provided as an interface between adjacent loops. This study describes the development of three tabu search algorithms for the design of tandem AGV systems. The first algorithm was developed based on the basic definition of a tandem network. The sec-ond and third algorithms, consider no preset number of loops and try to evenly distribute workload among loops by using workload balance as their objective functions. They generate different design scenarios for the tandem network, which can be evaluated and selected using a multi-attribute objective function. The first al-gorithm and the partitioning algorithm presented by Bozer and Srinivasan are compared for randomly gener-ated problems. Results show that for large-scale problems, the partitioning algorithm often leads to infeasible configurations with crossed loops in spite of its shorter running time. However, the newly developed algo-rithm avoids infeasible configurations and often yields better objective function values.

In this paper, an exact geometric algorithm is presented for solving two-job sequencing and scheduling problems in flexible flow shop and job shop environments while the resources are (un)available in some time periods and processors (un)availability is the same in all work centers. This study seems utterly new and it is applicable to any performance measure based on the completion time. The investigated models are very close to the actual scheduling problems, because they envisage the flexible job shop environments, heads, set-up times, arbitrary number of unavailability periods on all resources, arbitrary number of work-centers, any kind of cross-ability, any kind of resume-ability and several types of performance measures. The proposed model is presented to solve two-job problems because it is a graphical approach. However, it is concluded that the idea can be extended to n-dimensional problems as well.

This paper presents an analytic procedure for the value added to different production levels with different policy options. The approach is stochastic and thus provides a framework for informed decision-making on productivity growth under uncertainty conditions. The model was applied to data collected from a firm and re-sults recommend that the firm should redevelop if in diversification and systematisation growth stage and right size if in the bureaucratic growth stage.

The aim of this study is to propose a new mixed integer linear programming (MILP) model to find the minimum required number of yard cranes, Rubber tyred gantry cranes (RTGCs), for completion the total amount of works at the end of planning horizon. In other word, we find the optimal number of yard cranes in a container terminal which completes the total amount of works. The paper supports the proposed method using a numerical example.

Extensive research has been devoted to economic production quantity (EPQ) problem. However, little atten-tion has been paid to problems where depreciation cost and process quality cost must be considered, simulta-neously. In this paper, we consider the economic production quantity model of minimizing the annual total cost subject to depreciation cost and process quality cost, where depreciation cost and process quality cost are assumed to be continuous functions of holding time and of production run length, respectively. Local search meta-heuristics: iterated local search (ILS) and simulated annealing (SA) are proposed to solve proposed model. Finally, the meta-heuristics are computationally compared by using some numerical examples and re-sults are analyzed.