| Pub. Date | : Feb, 2023 |
|---|---|
| Product Name | : The IUP Journal of Marketing Management |
| Product Type | : Article |
| Product Code | : IJMM020223 |
| Author Name | : Pritam Chakraborty, Kingshuk Kundu and Sirsendu Mahata |
| Availability | : YES |
| Subject/Domain | : Marketing |
| Download Format | : PDF Format |
| No. of Pages | : 22 |
Grinding is a widely used process for semi-finishing and finishing of various mechanical components to provide the desired size and accuracy of the product. Grinding wheel is composed of abrasive particles held together firmly in a bond material. The abrasive particles remove material from the workpiece when the grinding wheel is rotated at a high speed with a particular infeed. As a result, extremely high temperature is generated, which produces numerous adverse effects in the grinding performance. To reduce such thermal problems, cutting fluid or coolant is used. In this paper, initially, Analytic Hierarchy Process (AHP) is used for optimization of the grinding performance while grinding under dry and wet environments using three different coolant concentrations (1:80, 1:50 and 1:20) at 30 m infeed. AHP results show that 1:20 coolant concentration provides the best environment for grinding among the four alternatives in this case. Experimental data are used for Artificial Neural Network (ANN) in MATLAB as input and target data to predict outputs of different coolant concentrations which are not performed experimentally. The output data so obtained are finally used for decision making using AHP, where 1:30 coolant concentration is found to be the optimal coolant concentration. It is also found that the directionality of order of the performance of the coolant with three different concentrations used in actual experiments has remained unchanged in AHP done with 11 alternatives.
Analytic Hierarchy Process (AHP) is a Multi-Criteria Decision-Making (MCDM) tool for the analysis of complex and difficult-to-judge decisions based on human intuition and mathematical calculation. The analysis is performed by making a structured
Grinding, Analytic Hierarchy Process (AHP), Artificial Neural Network (ANN), Optimization, Multicriteria decision making, Hybrid decision making, MATLAB