Job Adjustment Strategy for Predictive Maintenance in Semi-Fully Flexible Systems Based on Machine Health Status

Thirupathi Samala, Vijaya Kumar Manupati, Bethalam Brahma Sai Nikhilesh, Maria Leonilde Rocha Varela and Goran Putnik
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Thirupathi Samala: Department of Mechanical Engineering, NIT Warangal, Warangal 506004, India
Vijaya Kumar Manupati: Department of Mechanical Engineering, NIT Warangal, Warangal 506004, India
Bethalam Brahma Sai Nikhilesh: Department of Mechanical Engineering, NIT Warangal, Warangal 506004, India
Maria Leonilde Rocha Varela: Department of Production and Systems, School of Engineering, University of Minho, 4804-533 Guimarães, Portugal
Goran Putnik: Department of Production and Systems, School of Engineering, University of Minho, 4804-533 Guimarães, Portugal

Sustainability, 2021, vol. 13, issue 9, 1-20

Abstract: Complex systems consist of multiple machines that are designed with a certain extent of redundancy to control any unanticipated events. The productivity of complex systems is highly affected by unexpected simultaneous machine failures due to overrunning of machines, improper maintenance, and natural characteristics. We proposed realistic configurations with multiple machines having several flexibilities to handle the above issues. The objectives of the proposed model are to reduce simultaneous machine failures by slowing down the pace of degradation of machines, to improve the average occurrence of the first failure time of machines, and to decrease the loss of production. An approach has been developed using each machine’s degradation information to predict the machine’s residual life based on which the job adjustment strategy where machines with a lower health status will be given a high number of jobs to perform is proposed. This approach is validated by applying it in a fabric weaving industry as a real-world case study under different scenarios and the performance is compared with two other key benchmark strategies.

Keywords: semi-fully flexible systems; degradation modelling; residual life prediction; job adjustment strategy (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2021
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