A review of maintenance service for leasing equipment

Recent business trend focuses more on efficiency. One of the chosen ways is leased the capital equipment from other parties. The leasing option encourages both the lessee and lessor to discuss any consequences include responsibility for managing the equipment performance, rectifying failure during operation, maintenance option provided during leasing period, as well as the accompanying cost. The review and maping of publications are conducted based on the order in which the reference appears in the publication, in order to follow the development of thinking on the research topic of leasing, yet to identify the more recent development during the last decade. Several potential research ideas could be generated from the maping toward the fast and flexibel busines

Joint Determination of Preventive Maintenance and Buffer Stock for a Production Unit under Lease

Purpose: The purpose of this work is to develop a mathematical model for simultaneously determining the optimal period of preventive maintenance actions and the optimal size of buffer stock for a production unit that is owned by a lessor and leased to a lessee under a lease contract. Design/methodology/approach: A mathematical model is formulated and a numerical procedure is developed for finding the optimal period of preventive maintenance actions and the optimal size of buffer stock to minimize the total expected costs considering both a lessor and a lessee over a lease period. Findings: The proposed model gives better solutions than those where the maintenance cost to the lessor and the production inventory cost to the lessee are minimized separately. Originality/value: The joint determination of preventive maintenance and safety stock is a topic that has been extensively studied for decades. The majority of the models reported in the literature implicitly assume that the firm owns the production unit and maintenance actions are done in-house. However, equipment acquisition through leasing is a common practice nowadays. Normally, under a lease contract, the lessor who owns the equipment is responsible for maintenance services. This may lead to a conflict between the lessor and the lessee concerning the optimal choice of maintenance actions. To solve this conflict, we propose a joint determination of preventive maintenance and safety stock model for a production unit under a lease. The objective of our model is to simultaneously determine the optimal period of preventive maintenance actions that the lessor needs to perform and the optimal size of buffer stock the lessee needs to produce so that the total combined expected costs to both parties over the lease period are minimizedPeer Reviewe

Pengembangan Model Kebijakan Maintenance dengan Mempertimbangkan Perpanjangan Periode Lease

Harga beli dan biaya perawatan peralatan semakin mahal, sehingga perusahaan mempertimbangkan untuk lease peralatan daripada membelinya. Perpanjangan periode lease akan memberikan keuntungan lebih banyak, baik bagi pihak lessor (yang menyewakan) maupun pihak lessee (penyewa). Pada penelitian sebelumnya, perpanjangan periode lease ditawarkan pada awal kontrak. Bagi pihak lessee, model ini memiliki resiko dalam pembiayaan seperti ketidakpastian performansi peralatan dan tanggung jawab lessor. Oleh karena itu, penelitian ini mencoba untuk memodelkan kebijakan maintenance yang optimal dengan mempertimbangkan perpanjangan periode lease (extended lease) yang ditawarkan pada akhir masa kontrak. Tujuannya untuk menghilangkan resiko yang ada pada penelitian sebelumnya. Minimal repair dilakukan untuk memperbaiki peralatan gagal agar kembali ke kondisi operasional, sedangkan imperfect preventive maintenance untuk meningkatkan kondisi operasional peralatan ketika mencapai batas kontrol optimal agar terhindar dari kegagalan. Model matematika dibangun untuk menentukan batas kontrol, jumlah dan degree preventive maintenance, serta jumlah periode extended lease optimal. Pada bagian akhir, percobaan numerik diberikan untuk menunjukkan pengaruh panjang extended lease dan kebijakan maintenance dalam memaksimalkan keuntungan lessor. ================================================================= The purchase price and maintenance cost of the equipment are more expensive, thus the company considers to lease the equipment instead of purchase it. The lease period extension will provide more benefits for both the lessor (owner) and the lessee (user). In a previous research, the lease period extension was offered in the beginning of the contract. For the lessee, this model had some risks in finance, such as uncertainty of the equipment performance and lessor responsibility. Therefore, this research attemps to modelling the optimal maintenance policy by considering lease period extension (extended lease) that is offered in the ending of the contract. It aims to eliminate some risks in the previous research. Minimal repair is performed to rectify a failed equipment back to its operasional state, while imperfect preventive maintenance is conducted to improve the operasional state of the equipment when reaches a controlled limit to avoid failures. The mathematical model is constructed to determine the optimal controlled limit, number and degree of preventif maintenance, and number of extended lease period. Finally, numerical examples are given to illustrate the influences of the optimal length of the extend ed lease and the maintenance policy to maximize profit of the lessor

Maintenance Strategies Design and Assessment Using a Periodic Complexity Approach

People become more dependent on various devices, which do deteriorate over time and their operation becomes more complex. This leads to higher unexpected failure chance, which causes inconvenience, cost, time, and even lives. Therefore, an efficient maintenance strategy that reduces complexity should be established to ensure the system performs economically as designed without interruption. In the current research, a comprehensive novel approach is developed for designing and evaluating maintenance strategies that effectively reduce complexity in a cost efficient way with maximum availability and quality. A proper maintenance strategy application needs a rigorous failure definition. A new complexity based mathematical definition of failure is introduced that is able to model all failure types. A complexity-based metric, complication rate , is introduced to measure functionality degradation and gradual failure. Maintenance reduces the system complexity by system resetting via introducing periodicity. A metric for measuring the amount of periodicity introduced by maintenance strategy is developed. Developing efficient maintenance strategies that improve system performance criteria, requires developing the mathematical relationships between maintenance and quality, availability, and cost. The first relation relating the product quality to maintenance policy is developed using the virtual age concept. The aging intensity function is then deployed to develop the relation between maintenance and availability. The relation between maintenance and cost is formulated by investigating the maintenance effect on each cost element. The final step in maintenance policy design is finding the optimum periodicity level. Two approaches are investigated; weighted sum integrated with AHP and a comfort zones approach. Comfort zones is a new developed physical programming based optimization heuristic that captures designer preferences and limitations without substantial efforts in tweaking or calculating weights. A mining truck case study is presented to explain the application of the developed maintenance design approach and compare its results to the traditional reward renewal theory. It is shown that the developed approach is more capable of designing a maintenance policy that reduces complexity and simultaneously improves some other performance measures. This research explains that considering complexity reduction in maintenance policy design improves system functionality, and it can be achieved by simple industrially applicable approach

Optimisation de la planification intégrée de la maintenance préventive et de la production des systèmes multi-états

Cette thèse traite la problématique de la planification intégrée de la maintenance préventive et de la production des systèmes multi-états. Il s'agit d'un système de production modélisé comme étant un système multi-états avec un nombre fini de niveaux de capacité allant du fonctionnement parfait jusqu'à la défaillance totale. Il doit produire un ensemble de produits pour satisfaire une demande donnée durant l'horizon de planification. Les composantes du système multi-états sont assujetties à des remplacements préventifs et à une réparation minimale en cas de panne. Ce travail présente des modèles de planification permettant de générer simultanément le plan optimal de production au niveau tactique (problème de taille de lot capaci-taire) et les instants ou les intervalles d'intervention pour des actions de maintenance préventive. Les fonctions des objectifs de ces modèles minimisent la somme des coûts de la maintenance (préventive et corrective) et des coûts de production sujets à des contraintes de satisfaction de demande et de capacité. La méthodologie proposée développe des modèles mathématiques, des méthodes d'évaluation des temps de maintenance, des coûts de maintenance, les capacités relatives aux systèmes et des algorithmes de résolution pour obtenir des solutions optimales (recherche exhaustive) ou approximatives (algorithmes génétiques et recuit simulé). Cette méthodologie a été utilisée dans les trois contributions suivantes : 1. La première contribution propose un modèle de planification de la maintenance préventive périodique et de la production pour un système multi-états. Il s'agit de déterminer le plan de production optimal et les longueurs des intervalles de remplacement pour chaque composante du système. 2. La deuxième contribution traite du problème de la planification intégrée de la maintenance préventive acyclique et de la production dans le cas d'une seule machine. Le plan optimal détermine le plan de production et les instants d'intervention pour des activités de maintenance préventive. 3. La troisième contribution propose un modèle une planification simultanée de la maintenance préventive acyclique et de la production pour un système multi-états composé de plusieurs composantes. Les résultats obtenus dans cette thèse montrent l'impact économique réalisé par l'intégration de la planification de la maintenance préventive et de la production, ainsi que pour l'élimination de la contrainte de périodicité, surtout dans le cas d'une demande fluctuante. Les méthodes de résolution développées dans ces travaux permettent la résolution de problèmes de petite ou de grande taille

Post-Sale Cost Modeling and Optimization Linking Warranty and Preventive Maintenance

Ph.DDOCTOR OF PHILOSOPH

Safety and Reliability - Safe Societies in a Changing World

The contributions cover a wide range of methodologies and application areas for safety and reliability that contribute to safe societies in a changing world. These methodologies and applications include: - foundations of risk and reliability assessment and management - mathematical methods in reliability and safety - risk assessment - risk management - system reliability - uncertainty analysis - digitalization and big data - prognostics and system health management - occupational safety - accident and incident modeling - maintenance modeling and applications - simulation for safety and reliability analysis - dynamic risk and barrier management - organizational factors and safety culture - human factors and human reliability - resilience engineering - structural reliability - natural hazards - security - economic analysis in risk managemen

13th International Conference on Modeling, Optimization and Simulation - MOSIM 2020

Comité d’organisation: Université Internationale d’Agadir – Agadir (Maroc) Laboratoire Conception Fabrication Commande – Metz (France)Session RS-1 “Simulation et Optimisation” / “Simulation and Optimization” Session RS-2 “Planification des Besoins Matières Pilotée par la Demande” / ”Demand-Driven Material Requirements Planning” Session RS-3 “Ingénierie de Systèmes Basées sur les Modèles” / “Model-Based System Engineering” Session RS-4 “Recherche Opérationnelle en Gestion de Production” / "Operations Research in Production Management" Session RS-5 "Planification des Matières et des Ressources / Planification de la Production” / “Material and Resource Planning / Production Planning" Session RS-6 “Maintenance Industrielle” / “Industrial Maintenance” Session RS-7 "Etudes de Cas Industriels” / “Industrial Case Studies" Session RS-8 "Données de Masse / Analyse de Données” / “Big Data / Data Analytics" Session RS-9 "Gestion des Systèmes de Transport” / “Transportation System Management" Session RS-10 "Economie Circulaire / Développement Durable" / "Circular Economie / Sustainable Development" Session RS-11 "Conception et Gestion des Chaînes Logistiques” / “Supply Chain Design and Management" Session SP-1 “Intelligence Artificielle & Analyse de Données pour la Production 4.0” / “Artificial Intelligence & Data Analytics in Manufacturing 4.0” Session SP-2 “Gestion des Risques en Logistique” / “Risk Management in Logistics” Session SP-3 “Gestion des Risques et Evaluation de Performance” / “Risk Management and Performance Assessment” Session SP-4 "Indicateurs Clés de Performance 4.0 et Dynamique de Prise de Décision” / ”4.0 Key Performance Indicators and Decision-Making Dynamics" Session SP-5 "Logistique Maritime” / “Marine Logistics" Session SP-6 “Territoire et Logistique : Un Système Complexe” / “Territory and Logistics: A Complex System” Session SP-7 "Nouvelles Avancées et Applications de la Logique Floue en Production Durable et en Logistique” / “Recent Advances and Fuzzy-Logic Applications in Sustainable Manufacturing and Logistics" Session SP-8 “Gestion des Soins de Santé” / ”Health Care Management” Session SP-9 “Ingénierie Organisationnelle et Gestion de la Continuité de Service des Systèmes de Santé dans l’Ere de la Transformation Numérique de la Société” / “Organizational Engineering and Management of Business Continuity of Healthcare Systems in the Era of Numerical Society Transformation” Session SP-10 “Planification et Commande de la Production pour l’Industrie 4.0” / “Production Planning and Control for Industry 4.0” Session SP-11 “Optimisation des Systèmes de Production dans le Contexte 4.0 Utilisant l’Amélioration Continue” / “Production System Optimization in 4.0 Context Using Continuous Improvement” Session SP-12 “Défis pour la Conception des Systèmes de Production Cyber-Physiques” / “Challenges for the Design of Cyber Physical Production Systems” Session SP-13 “Production Avisée et Développement Durable” / “Smart Manufacturing and Sustainable Development” Session SP-14 “L’Humain dans l’Usine du Futur” / “Human in the Factory of the Future” Session SP-15 “Ordonnancement et Prévision de Chaînes Logistiques Résilientes” / “Scheduling and Forecasting for Resilient Supply Chains