International Journal of Industrial Engineering and Management

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Vol. 13 No. 2 (2022)
Original Research Article

A Developed Optimization Model for Mass Production Scheduling Considering the Role of Waste Materials

Paitoon Chetthamrongchai
Faculty of Business Administration, Kasetsart University, Thailand
Bio
Olga Gennadevna Stepanenko
Associate Professor, Irkutsk National Research Technical University, Irkutsk, Russian Federation
Bio
Natalya Ryafikovna Saenko
Moscow Polytechnic University, Moscow, Russian Federation
Bio
Sergey Yurevich Bakhvalov
Kazan Federal University
Bio
Gulnaz Aglyamova
Kazan Federal University, Naberezhnye Chelny, Russia
Bio
A. Heri Iswanto
University of Pembangunan Nasional Veteran Jakarta
Bio

Published 2022-06-30

abstract views: 42 // FULL TEXT ARTICLE (PDF): 0


Keywords

  • Optimization model,
  • Mass production,
  • Production waste,
  • Production schedule,
  • Innovative method

How to Cite

Chetthamrongchai, P., Stepanenko, O. G., Saenko, N. R., Bakhvalov, S. Y., Aglyamova, G., & Iswanto, A. H. (2022). A Developed Optimization Model for Mass Production Scheduling Considering the Role of Waste Materials. International Journal of Industrial Engineering and Management, 13(2), 135–144. https://doi.org/10.24867/IJIEM-2022-2-307

Abstract

Planning, scheduling and delivery of shipments in workshops and factories active in the field of custom manufacturing industries are two important arms in the decision-making process that are used to optimize or reduce the adverse effects of problems in production, so this is one of the important pillars within any company or manufacturing plant. The importance of this issue will become clear when this tool is used in the real world and the production platform to benefit the companies. In this research, we will investigate a medium-term period and a short-term schedule for the production of carton sheets in the printing and packaging industry, and provide a method for separating cutting and scheduling models, as well as an innovative method for the scheduling. The result of the research is the comparison of the proposed method with the common method used in the factory to measure the efficiency.

 

Article history: Received (January 1, 2022); Revised (May 18, 2022); Accepted (May 19, 2022); Published online (June 8, 2022)  

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