Design of experiments and Monte Carlo simulation-based prediction model for productivity improvement in printing industry

Santosh B. Rane, Prathamesh R. Potdar and Nandkumar Mishra

International Journal of Productivity and Quality Management, 2022, vol. 35, issue 1, 78-116

Abstract: In today's cut-throat business competition, productivity improvement is essential for any organisation to reduce high production costs. The objective of this research is to improve the material productivity of the printing process by implementing Six Sigma methodology. In this study, define measure analysis improve and control (DMAIC) approach has been demonstrated with a combination of appropriate tools and techniques in Six Sigma methodology. A prediction model has been developed based on the design of experiment and Monte Carlo simulation (MCS). This study identified that start-up waste as a vital cause of less material productivity. This research concludes that every organisation should reinvestigate the process and explore the opportunity for productivity improvement by using the appropriate techniques. This case study has reduced print waste and electricity consumption annually by 89,064 kg and 648,000 kWh, respectively. This productivity improvement case creates an impact on the environment by reducing CO₂ emission and chemical waste.

Keywords: design of experiment; DOE; Six Sigma; DMAIC; cause and effect matrix; Monte Carlo simulation; prediction model; FMEA. (search for similar items in EconPapers)
Date: 2022
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