Job shop scheduling problems are one of the challenging combinatorial problems that have drawn the attention of researchers for the last three decades. It is observed that genetic algorithm (GA) is gaining more importance over the past several years. An attempt has been made through GA to solve job shop scheduling problems with job-based, operation-based, and proposed methods of representation and schedule deduction with the make-span objective. Computational experiments of this attempt have yielded better solutions coupled with appreciable reduction in computer processing time. A set of selected benchmark problems have been used with the proposed heuristic for validation and the results show the better performance of the proposed method of representation of jobs and schedule deduction.
This paper mainly focusses on parametric optimization of squeeze cast AC2A Ni coatedSiCpcomposite through Taguchi technique. Composite samples have been cast through squeeze casting for each experimental trial based on L16 orthogonal array. From analysis of variance (ANOVA), it has been found that reinforcement percentage, squeeze pressure, and pressure duration were the casting parameters making significant improvement in the mechanical properties such as hardness and ultimate tensile strength. Reinforcement percentage and squeeze pressure have been identified as the most influencing parameters from the percentage contribution analysis. The optimum parametric setting has been determined through Taguchi technique. It has been confirmed that AC2A-Ni coatedSiCpcomposite obtained for the optimum parametric setting has exhibited better mechanical properties compared to the experimental trials.
In this study, the response surface methodology was used to optimize the process parameters of constant speed horizontal spindle surface grinding. The experiments were conducted based on the design expert software. The surface roughness characteristics were investigated in AISI 1080 steel plates using A60V5V grinding wheels. The optimum parameters for minimum surface roughness were found using Design Expert software. The parameters for a particular surface roughness value can also be determined using the results of this experiment. This results shows that feed has a greater effect on surface roughness and feed has medium effect on surface roughness. While dressing depth of cut has a very minimal effect on surface roughness.
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