Integrated Decision Model for Interrelated Sub-Problems of Part Design or Selection, Machine Loading and Machining Optimization

Abstract
In the work presented in this paper, we made an attempt to integrate the decisions for interrelated sub-problems of part design or selection, machine loading and machining optimization in a random flexible manufacturing system (FMS). The main purpose was to come up with an optimization model for achieving more generic and consistent decisions for the FMS and which can be practically implemented on the shop floor to help designers and other engineers in several ways, including, for instance, to optimize the designs of parts for specific FMS. In order to attain the generic decisions, an integer nonlinear programming (INLP) problem was formulated and solved to maximize the FMS throughput. Based on the results, the part design or selection, machine loading and machining optimization decisions can be simultaneously made. To get more insights of the results and also to check the validity of the model, a two-factor full factorial design was implemented for the sensitivity analysis, analysis of variance (ANOVA) and residual analysis. The computational analyses show that the tooling budget and available processing time were both statistically significant to throughput and confirmed that the model is valid with the data normally distributed.
Description
Keywords
Optimization, part design, part selection, machine loading, machining optimization, integer nonlinear programming, flexible manufacturing systems
Citation
Mgwatu, M.I., Opiyo, E.Z. and Victor, M.A.M., 2009, January. Integrated Decision Model for Interrelated Sub-Problems of Part Design or Selection, Machine Loading and Machining Optimization. In ASME 2009 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference (pp. 3-12). American Society of Mechanical Engineers.