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Cycle Time Reduction in CNC Turning Process Using Six Sigma Methodology – A Manufacturing Case Study

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Innovations in Mechanical Engineering (icieng 2021)

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Abstract

Six-Sigma, a data-driven methodology, employed to improve the process in terms of Defect reduction or process optimization. In this paper, an experimental study is presented optimizing the cutting parameters while machining of shoulder bolt in a Computer Numerical Control (CNC) turning machine to reduce the cycle time. This study identifies, the effects of cutting speed, feed rate and dwell time on Thread rolling diameter (TRD) in CNC turning machine that was experimentally investigated. The experimentation plan is designed using six sigma D-M-A-I-C methodology, and the subsequent statistical analysis has been done using Minitab-16 software. Shainin based variable search tool has been used to investigate the design parameters that contribute to the reduction of the cycle time and factorial plots are employed to determine the contribution of important parameters. Later, the optimal values for the best cutting conditions are proposed for industrial production using the formulated mathematical model. Finally, this paper documents the analysis and tasks performed that reduced cycle time which resulted in increased productivity and also in annual savings.

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Acknowledgement

The project is funded by MHRD Government of India as research seed money scheme National Institute of Technology Warangal, India with Order No NITW/DIR/2018/478/1138 and FCT – Fundação para a Ciência e Tecnologia who financially supported this work within the R&D Units Project Scope: UIDP/04077/2020 and UIDB/04077/2020.

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Manoj, K., Kar, B., Agrawal, R., Manupati, V.K., Machado, J. (2022). Cycle Time Reduction in CNC Turning Process Using Six Sigma Methodology – A Manufacturing Case Study. In: Machado, J., Soares, F., Trojanowska, J., Ottaviano, E. (eds) Innovations in Mechanical Engineering. icieng 2021. Lecture Notes in Mechanical Engineering. Springer, Cham. https://doi.org/10.1007/978-3-030-79165-0_13

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  • DOI: https://doi.org/10.1007/978-3-030-79165-0_13

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