Azim Houshyar

A systematic supplier selection procedure

Abstract One of the most important decisions that the procurement department of any manufacturing organization has to make is the selection of an appropriate supplier. This selection will commit the organization and its resources to an outsider for a long time to come, and any mistake in their selection could adversely affect the stability of the organization. As firms reduce their supply base and enter into long term commitments with suppliers, this decision becomes even more important. In this paper a systematic procedure for supplier selection is presented that influence all the relevant factors into the decision, and classifies them into critical factors, objective factors, and subjective factors. It offers a procedure that can be used to evaluate the suppliers performance.

Benchmarking the application of quality function deployment in rapid prototyping

Abstract The increased importance of rapid prototyping of manufactured goods in the global market environment has generated extensive interest in “doing enough of the right things” the first time. One very successful approach, called Quality Function Deployment (QFD), introduced by the Mitsubishi Corporation of Japan in 1972, is a structured process for taking the needs and desires of the customer and translating them into technical engineering requirements. Providing products and services that meet the quality expectation of the customer is a challenge facing every corporation. QFD provides a way to ensure customer needs and expectations are addressed from concept through delivery. QFD is an excellent means of communication between interdepartmental teams of product development staff, design engineers, manufacturing engineers, marketing personnel and the final user of the product.

Quality and optimum parameter selection in metal cutting

Abstract In many metal cutting operations, production parameters are treated as decision variables that can be determined based on some technological as well as optimization criteria. Parameters such as speed, feed rate, and depth of cut affect the quality of the product, its machining time, and overall machining costs. This paper deals with optimization of a single item in single-stage and multi-stage production systems, and determines the optimal cutting parameters under various evaluation criteria. In particular, the minimum machining time, minimum machining cost, and maximum profit rate criteria are discussed. Considering cutting speed as the only decision variable, we concluded that quality constrains the optimal cutting speed to a certain range in an attempt to produce higher-quality products in an optimum time. For multi-stage production, optimization techniques were used to determine the optimal speed for each production stage, and the optimal cycle time. To study the effect of introducing the element of quality into the determination of optimum cutting parameters, a comparison was also made with existing models.

Exact optimal solution for facility layout: deciding which pairs of locations should be adjacent

Abstract This paper describes the development of a mathematical model for determining optimum block layout systems utilizing 0–1 integer programming as the optimization component. The objective function is to maximize a weighted sum of adjacent departments. The selected weight is a measure of the flow of material between departments. Developing a set of constraints, and changing the objective function to minimization of adjacency of departments with no interaction, it is shown that the procedure is capable of determining the optimal location in small size problems. To apply it to larger size problems, additional constraints are developed that help reduce the number of iterations for the integer program to converge to an optimal solution.

Comparison of solution procedures to the facility location problem

Abstract This paper describes a mathematical model for determining optimum location for N facilities of the same size so as to maximize the sum of the material flow between the adjacent facilities. The model is based on a 0–1 integer program formulation of the problem which may produce an optimal, but infeasible solution, followed by a heuristic which begins with the 0–1 integer solution and generates a feasible solution. The procedure is capable of generating good solutions for medium-size problems. For location problems of size N = 4 to N = 16, the performance of the procedure in terms of the CPU time and the degree of closeness of the final solution to the optimal (yet infeasible) solution is measured and conclusions are drawn. The procedure is an addition to the existing pool of mathematical models for the facility layout problem.

A simulation model of the fuel handling system in a nuclear reactor

This article demonstrates the outcome of a study of the fuel handling system in the experimental breeder reactor (EBR-II). In this article, a mathematical model of the fuel handling system is described which predicts the systems performance under different fuel handling scenarios. In particular, the following two scenarios are studied: (a) a feasible fuel handling schedule to unload 330 blanket S/A in a period of 3 yr with minimal interruption to the normal operation of the reactor; and (b) a feasible fuel handling schedule to shut down and unload the reactor and the storage tank. In addition, the interactions between different sub-systems are highlighted and the results of different sensitivity analysis, performed to scrutinize the systems capability under different constraining procedures are reviewed.

Application of artificial neural networks in interactive simulation

Artificial Neural Networks (ANNs) show promising capabilities in interactive simulation. In this article, the literature on ANNs and their applications to simulation methodology is reviewed and several recommendations to their implementation are presented. Also, the creation of a manufacturing library consisting of basic ANN modules that can be used to represent complex manufacturing processes is discussed.

A practical reliability and maintainability data collection and processing software

To provide a means to insure effective implementation of reliability and maintainability (R&M) programs, using Visual Basic on Windows, a software program is developed that uses data on performance of the equipment and generates statistics on the reliability and maintainability of the machinery. The software is designed for the operators to enter the data, to be used by the design engineers and reliability engineers, to study the systems performance.

Determination of optimal intermediate storage capacity

Abstract A system of two machines running in batches and three storage used for storing raw materials, intermediate items, and finished products is considered. The system maintains enough WIP to assure no stockout will happen. Each machine has a finite production rate greater than or equal to the demand rate and thus operates with periodic start-ups and shut-downs. Using analytical results, total production cost as function of set-up costs, safety stocks, carrying costs and storage costs is presented. The problem reduces to a nonlinear, dynamic, constrained optimization one, for which a heuristic is developed that determines capacity of the buffers, the optimum safety stocks, cycle times for delivery of the raw material, and production runs such that overall costs are minimized.

Required steps for successful design and implementation of simulation

Abstract Use of simulation modeling as a tool to address manufacturing issues enables the modeler to measure the performance of the existing or proposed systems under different operating schemes. It can help management make basic evaluations of the different options. Therefore, simulation of the systems operation has rapidly become one of the most useful and common applications of computers. But, along with the prevailing use of simulation has come a great deal of misuse. Underlying all misuses is lack of knowledge. In this article the process of simulation modeling, data collection, common pitfalls in simulation modeling and its implementations, data analysis, output interpretation design of simulation experiments, and training requirements are described.