Manufacturing Technology Today

M. Vijay Kumar ¹, A. N. N. Murthy ², K. Chandrashekhara ³

Affiliations
1 Dept. of Mech. Engg., JSS Academy of Technical Education, Bangalore, IN
2 JSS Academy of Technical Education, Bangalore, IN
3 Dept. of Mech. Engg., SJCE, Mysore, IN

Abstract

Though the designs of FMC strive to ensure the maximum flexibility in the system, in practice, after the implementation of such systems the operational executives often find it hard to accommodate frequent variations in the part designs of incoming jobs. The difficulty can vary well be overcome by scheduling the variety of incoming problem into the system efficiently. The scheduling of FMS with the aid of Genetic Algorithm and draft of code strings, which are used by this algorithm have been presented in this paper. Moreover, some results obtained by computer program based on this method also have been presented. In first case it has been assumed that the cell works in optimal mode. Every operation can be done on every machine and in the second case cell assorts in sequential mode. The first operation is executed on the first machine, the second operation on the second machine and so on. The only criterion of scheduling evaluation is the time of cell work. The time must be the shortest for definite number of jobs and machines.

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M. Vijay Kumar ¹, W. Yerriswamy ¹

Affiliations
1 JSS Academy of Technical Education, Bangalore, IN

Abstract

An important part of many quality improvement and quality development programs is an evaluation of the effect of process variables upon performance. The product quality is depending on number of independent factors. Their effects on dependent factors are evaluated through empirical investigation. In practice, a small number of controllable variables contribute to a vital share of the effect of the product quality. These variables do not necessarily produce a constant effect on the product. The question would therefore arise as to how efficiently and economically the contribution of each of these factors can be assessed individually and also collectively to produce the total effect on the product performance. An approach that fulfills these requirements is available in the statistically designed experiments. The statistically designed experiment permits simultaneous consideration of all the possible factors that are suspected to have a bearing on the problem under consideration. Even a limited number of experiments would enable experimenter to uncover the vital factors on which further trails would lead the researcher to track down their most desirable combination which will yield the expected results. Scanning a large number of variables is one of the objectives that a statistically designed experiment would fulfill in many problem situations. The purpose of this study is to develop a mathematical model to predict the task time taken by the operator to assemble the needle and thread by varying the working environmental conditions like temperature, light and noise. The adequacies of the model are then evaluated using MINITAB statistical software and analysis of variance (ANOVA) technique. The model developed is checked for its adequacy. Results of confirmation experiments showed that the model can predict the optimum task time with reasonable accuracy.

Keywords

Design of Experiment, ANOVA, Experiments, Treatment, Replication.

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