Integrated non-cyclical preventive maintenance scheduling and production planning for multi-parallel component production systems with interdependencies-induced degradation

Integrating preventive maintenance (PM) scheduling and production planning efficiently remains challenging for researchers and practitioners alike, owing to complex component interdependencies. Existing studies often lack practicality due to oversimplified assumptions. In this paper, we propose a tw...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:International journal of advanced manufacturing technology 2024-02, Vol.130 (9-10), p.4723-4749
Hauptverfasser: Bahou, Ziyad, Lemnaouar, Mohamed Reda, Krimi, Issam
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:Integrating preventive maintenance (PM) scheduling and production planning efficiently remains challenging for researchers and practitioners alike, owing to complex component interdependencies. Existing studies often lack practicality due to oversimplified assumptions. In this paper, we propose a two-stage solution for the integrated PM scheduling and production planning problem within multi-parallel component manufacturing systems, accounting for diverse interdependencies. These interdependencies encompass stochastic, structural, economic, and resource-related interdependencies, all while accounting for the resultant degradation. The primary objective is jointly optimizing costs associated with holding, backorders, production, setup, and maintenance. Initially, we employ an Ordinary Differential System to compute a realistic production capacity. Additionally, we analyze the effects of interdependence-induced degradation on system availability and failures. Subsequently, we formulate the problem as an integer programming model to determine an optimal joint plan. The effectiveness of our approach is validated through numerical examples and sensitivity analysis, providing insightful guidance for efficient PM scheduling and production planning, particularly in large-scale production systems.
ISSN:0268-3768
1433-3015
DOI:10.1007/s00170-024-12975-4