Real-Time Maintenance Policy Optimization in Manufacturing Systems: An Energy Efficiency and Emission-Based Approach

Ágota Bányai and Tamás Bányai ()
Additional contact information
Ágota Bányai: Institute of Logistics, University of Miskolc, 3515 Miskolc, Hungary
Tamás Bányai: Institute of Logistics, University of Miskolc, 3515 Miskolc, Hungary

Sustainability, 2022, vol. 14, issue 17, 1-15

Abstract: Within the frame of the Fourth Industrial Revolution, the application of Internet of Things technologies makes it possible to convert conventional manufacturing systems into cyber-physical systems, where the used new technologies enable the improvement of maintenance and operation processes. The aim of this work is to develop and validate a new real-time maintenance policy model and optimization algorithm based on digital twin simulation. The maintenance policy model is based on the conventional failure and operation data from ERP (enterprise resource planning) and the real-time and forecasted failure and operation data from digital twin simulation. The described maintenance policy model and its optimization algorithm represent an innovative way to manage predictive, preventive, corrective, and opportunistic maintenance strategies. The novelty of the presented method is that the real-time data generated by the digital twin solution allow the definition of a more accurate maintenance strategy. The optimization algorithm is characterized by a standard evolutionary algorithm. The impact of maintenance policy optimization on the energy efficiency and emission was analyzed in the case of both conventional and cyber-physical manufacturing systems with and without digital-twin-based simulation. The results showed that the energy consumption and the greenhouse gas emission in the real-time maintenance policy optimization scenario decreased by 21%, depending on the electricity generation source.

Keywords: maintenance policy optimization; digital twin; optimization; manufacturing system; energy efficiency (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2071-1050/14/17/10725/pdf (application/pdf)
https://www.mdpi.com/2071-1050/14/17/10725/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:14:y:2022:i:17:p:10725-:d:900398

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().