Noor, K; Siddiqui, M A and Syed, A I (2025) Optimization of specific energy consumption in cnc turning of a hardened alloy steel roll at low cutting speeds. Journal of Engineering, Design and Technology, 23(2), pp. 368-385. ISSN 1726-0531
Abstract
Purpose: This study was conducted to analyze the effects of machining parameters on the specific energy consumption in the computerized numerical control lathe turning operation of a hardened alloy steel roll at low cutting speeds. The aim was to minimize its consumption. Design/methodology/approach: The design matrix was based on three variable factors at three levels. Response surface methodology was used for the analysis of experimental results. Optimization was carried out by using the desirability function and genetic algorithm. A multiple regression model was used for relationship build-up. Findings: According to desirability function, genetic algorithm and multiple regression analysis, optimal machining parameters were cutting speed 40 m/min, feed 0.2 mm/rev and depth of cut 0.50 mm, which resulted in minimal specific energy consumption of 0.78, 0.772 and 0.78 kJ/mm3, respectively. Correlation analysis and multiple regression model found a quadratic relationship between specific energy consumption with power consumption and material removal rate. Originality/value: In the past, many researchers have developed mathematical models for specific energy consumption, but these models were developed at high cutting speed, and a majority of the models were based on the material removal rate as the independent variable. This research work developed a mathematical model based on the machining parameters as an independent variable at low cutting speeds, for a new type of large-sized hardened alloy steel roll. A multiple regression model was developed to build a quadratic relationship of specific energy consumption with power consumption and material removal rate. This work has a practical application in hot rolling industry.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | energy consumption; machining; process optimization |
| Index terms: | independent variable, correlation analysis, response surface methodology, multiple regression model, power consumption, energy consumption, mathematical model, genetic algorithm, consumption, multiple regression analysis, methodology |
| Subjects: | statistical analysis, mathematical modelling, energy systems, algorithms, research methods, consumer economics |
| Topics: | Digital Applications, Stakeholder Management, Research Practice, Sustainability |
| Descriptive scope: | 4 PCTA |
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