Part-machine group formation with ordinal-ratio level data & production volume

Abstract

This work presents an algorithm for design of cellular manufacturing system. It considers ordinal level data and ratio level data. We consider sequence of operation for every component as ordinal level data. The ratio level data includes operation time per unit, production volume & machine capacity. Adapted design activity model & image representation in computer vision is used to model ordinal-ratio level data. Orthographic view part grouping is used for part family formation. Machines are allocated on basis of their net utilization for a part family. Performance of algorithm is comparable & of good quality with existing methods in its class. To validate the result, a two way ANOVA technique is used, and on simulated example the F-ratio is enumerated. It is observed that production volume has significant influence on cell configuration and cell performance. It is concluded that the change in production volume mixes may need reconfiguration & capacity scaling according to recommendation of algorithm & ANOVA analysis. To facilitate industrial application, it can be implemented by using free software, Scilab and/or commercial softwares.