Design of experiments and Monte Carlo simulation-based prediction model for productivity improvement in printing industry
by Santosh B. Rane; Prathamesh R. Potdar; Nandkumar Mishra
International Journal of Productivity and Quality Management (IJPQM), Vol. 35, No. 1, 2022

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.

Online publication date: Fri, 04-Feb-2022

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Productivity and Quality Management (IJPQM):
Login with your Inderscience username and password:

    Username:        Password:         

Forgotten your password?


Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com