Mathematical model for maintenance planning of machine tools

Preventive maintenance planning of machine tools may be a complex task for tools with multiple components. For manufacturing processes with high setup and downtime costs, components replacement should be combined to avoid too many production stoppages and therefore reduce costs. The combination that minimizes costs should take into account the lifetime distribution and the age of each component at the replacement time. Replacing too soon may imply a high number of replacements for a given component, while replacing too late may imply a high number of failures that lead to shutdowns, increasing costs. In this paper, a tool is seen as a series system, which means that whenever a component fails, a corrective action is needed and at least the failed component has to be replaced. In the literature, some of the models and heuristics for maintenance planning of series systems consider that a minimal repair is made when a component fails, while other models propose static approaches, i.e., the same combination and the same interval is used over time regardless of the ages of the components involved. This paper aims to propose a dynamic approach and presents a mathematical model to determine both the next time to perform a preventive maintenance task and the components that should be replaced in order to minimize the total cost. The model also intends to determine the components to be replaced preventively when unexpected events occur (such as the failure of a tool component or the machine, the shortage of raw material, etc.) or during planned stoppages (such as the end of a production order, machine preventive maintenance task, etc.).We would like to thank the companies associated with the project and express our appreciation for the commitment of the employees involved.This work has been supported by Norte 010247 FEDER 017833 – TechParts I&D

Modelo metodológico para programación de tareas en sistemas de servicios: un enfoque de ingeniería de software

This paper presents an approach of software engineering to a research proposal to make an Expert System to scheduling on service systems using methodologies and processes of software development. We use the adaptive software development as methodology for the software architecture based on the description as a software metaprocess that characterizes the research process. We make UML’s diagrams (Unified Modeling Language) to provide a visual modeling that describes the research methodology in order to identify the actors, elements and interactions in the research process.Se presenta una estructura de Ingeniería de Software (IS) para un proyecto de investigación relacionada con la construcción de un prototipo de Sistema Experto (SE) para la programación de tareas en sistemas de servicios (PTSS), empleando metodologías y procesos del desarrollo de software. Se utiliza la metodología de desarrollo de software adaptable para el desarrollo de la arquitectura de software, partiendo de la descripción como un metaproceso de software que caracterizará el proceso de la investigación. Se emplean diagramas de UML (Unified Modeling Language) para proporcionar un modelado visual que describe la metodología del trabajo de investigación, que permite establecer los actores, elementos e interacciones en el proceso de investigación

PengaruhKompetensi dan Jumlah Kru Perawatan Terhadap Biaya Perawatan Kapal Penangkap Ikan dengan Pemodelan Dinamika Sistem

Pelaksanaan kegiatan perawatan, baik perawatan preventif maupun reaktif, tidak terlepas dari peran kru. Kompetensi dari seorang kru dapat diketahui dari pendidikan dan pelatihan yang pernah diterima, keahlian dan pengalaman. Metode dinamika sistem merupakan metode pemodelan yang menggunakan hubungan sebab-akibat dalam menyusun model suatu sistem yang kompleks. Penggunaan metode ini lebih ditekankan tentang bagaimana tingkah laku sistem. Kaitannya dengan crew skill dan jumlah crew terhadap perawatan pada kapal latih karena faktor human memiliki sifat yang dinamis, dengan pengertian kondisinya selalu berubah terhadap waktu. Tujuan dari penelitian ini adalah untuk memodelkan kompetensi dan jumlah kru perawatan terhadap terhadap biaya perawatan kapal penangkap ikan dengan menggunakan pendekatan dinamika system serta merekomendasikan pilihan antara kompetensi kru dan jumlah kru perawatan yang paling efektif untuk operasional kapal penangkap ikan sehingga menghasilkan biaya perawatan yang minimum. Metode yang digunakan dalam penelitian ini menggunakan pemodelan dinamika sistem. Hasil simulasi menunjukkan pada tingkat keandalan dipertahankan pada nilai minimum 0.6, biaya yang optimum untuk perawatan adalah meningkatkan nilai kompetensi kru hingga level 120% tanpa meningkatkan jumlah kru. Pada nilai minimum reliability 0.7 untuk mencapai total biaya minimum dengan meningkatkan kompetensi kru hingga level 130% dan jumlah kru hingga 2 orang. Selanjutnya untuk nilai minimum reliability 0.8 untuk mencapai total biaya minimum dengan meningkatkan kompetensi kru hingga level 130% dan meningkatkan jumlah kru hingga 2 orang. ============================================================================================================ Implementation of maintenance activities, both preventive and corrective maintenance, is inseparable from the role of the crew. Crew competence can be observed from the level of education and training, expertise and experience. This research utilized system dynamics modeling using causal relationships in developing the model of a complex system to understand the behavior of the system reliability when there is a change in either crew competence or crew size for fishing vessel. The objective of this study is to model the competence and crew size on the fishing vessel and observe its impact on maintenance cost by using system dynamics approach. By using such a model, we could recommend the most effective design of crew skills and crew size for the operation of fishing vessels which minimizes the maintenance cost. This research uses a system dynamics modeling to solve the problem. The simulation results show when the level of reliability is set to minimum value 0.6, the optimum cost for maintenance is obtained by increasing the level of crew skills to 120% without increasing crew size. When the minimum value of reliability is set to 0.7, the optimum cost for maintenance is obtained when we improve the competence of crew level to 130% with change crew size to 2 crews. And for the minimum level of reliability is set to 0.8, the optimum cost for maintenance is gained when we increasing crew skill level to 130% and increase the crew size up to 2 crews

Modified age-based replacement

The maintenance policy of age-based replacement (ABR) is widely specified in OEM instructions. The practical application of ABR raises concerns about ensuring consistent adherence to prescribed replacement schedules for extended periods. ABR lacks periodicity, resulting in scheduling asynchrony with designated time slots, while alternative policies such as block replacement (BR) provide periodicity at the expense of efficiency. Additionally, scepticism about ABR is based on its simplicity and restrictive assumptions, which include ideal replacements and the one-component system assumption. The task of estimating component lifetime distributions and defining critical parameters such as cost of failure, which is an average cost with varying downtime, presents significant challenges. We study “modified age-based replacement” (MABR) in response to the limitation of periodicity, so that preventive replacements exhibit quasi-periodic behaviour. We quantify the cost-inefficiency of MABR compared to ABR, thus informing the practical implications of introducing periodicity into the ABR policy and highlighting the need to incorporate real-world constraints, such as time slots for maintenance actions. The findings indicate that MABR and a special case are reasonably efficient provided the slot-interval is not too large. This is a useful insight for practical application of ABR type policies for scheduling preventive maintenance

Algorithmic Strategy for Simultaneous Optimization of Design and Maintenance of Multi-Component Industrial Systems

This article describes a new approach to simultaneous optimization of design and maintenance of large-scale multi-component industrial systems. This approach, in a form of an algorithm, aims to help designers in the search for solutions by characterizing the components and their architecture including maintenance issues. The aim is to improve the performance of the industrial systems by maximizing the Total Operational Reliability (TOR) at the lowest Life Cycle Cost (LCC). In the case of this research, the term "design" refers to the reliability properties of the components, possible redundancies, faulty component accessibility, and the ability to improve the component real-time monitoring architecture. The term “maintenance” refers to maintenance plan adapted to the opportunistic dynamic maintenance plan. Simultaneous optimization of design and maintenance is achieved by a two-level hybrid algorithm using evolutionary (genetic) algorithms. The first level identifies the optimal design solutions calculated relative to the TOR and the LCC. The second proposes a dynamic maintenance plan that maximizes the reliability of the system throughout its operating life

Contributions au développement de politiques de remplacement préventif pour des sytèmes multi-composants

Dans cette thèse, nous proposons de développer des politiques de remplacement préventif pour des systèmes multi-composants. Ces systèmes sont composés de plusieurs composants selon une configuration bien déterminée et dont l’état se dégrade d’une manière aléatoire. Les politiques de remplacement définissent les actions à entreprendre en fonction de l'état du système ou de ses composants et ont pour objectif de retarder l'apparition des pannes et de prolonger la durée de vie du système. Sur le plan théorique, la généralisation des modèles de remplacement des systèmes mono-composants à des systèmes multi-composants n'est pas évidente. La difficulté réside essentiellement dans l’existence d’interaction ou de dépendance entre les différents composants du système. Nous nous sommes concentrés dans cette thèse sur les dépendances stochastique et économique entre les composants. Pour la dépendance stochastique, la propagation de la panne a été modélisée par l’effet domino pour un système parallèle à deux composants. Nous avons proposé deux politiques de remplacement de type Age. Dans la première politique, nous avons supposé que la structure des coûts est constante alors que dans la deuxième politique cette hypothèse a été modifiée en prenant une structure de coûts variable. Nous avons aussi proposé dans le cadre de la dépendance stochastique un modèle de remplacement bi-objectif qui optimise à la fois le coût espéré du remplacement et la disponibilité du système. Pour la dépendance économique, nous avons proposé une politique de remplacement basée sur le comptage des pannes pour un système parallèle et nous l’avons intégrée dans un modèle d’allocation de la redondance d’un système série-parallèle. Le modèle mathématique a été résolu par une approche heuristique basée sur l’algorithme du recuit simulé.The aim of this thesis is to develop preventive replacement policies for multi-component systems. Systems are composed of several components connected under a known configuration and subject to random failures. Each replacement policy defines the actions to be taken according to the state of the system or its components and it is intended to delay the occurrence of failures and extend the lifetime of the system. From the theoretical point of view, the extension of replacement models from single-component systems to multi-component systems is not obvious. The difficulty is due primarily to the interaction or dependence between the different components of the system. In this thesis the focus has been put on the stochastic and economic dependencies between components. For stochastic dependence the propagation of the failure is modeled by the domino effect for a two-component parallel system, and two age replacement policies are investigated. In the first policy, we assumed that the cost structure is constant whereas in the second policy a variable cost structure is assumed. We proposed also a bi-objective replacement model that optimizes both expected replacement cost rate and system availability. For economic dependence, we proposed a failure counting replacement policy for a parallel system and we integrated it in a redundancy allocation model for a serie-parallel system. The mathematical model has been built taking account of this policy and Simulated Annealing algorithm has been used as resolution approach

Dynamic grouping maintenance with time limited opportunities

International audienceThis paper presents firstly a dynamic grouping maintenance strategy for multi-component systems with positive economic dependence, which implies that combining maintenance activities is cheaper than performing maintenance on components separately. Preventive maintenance durations and multiple occurrences of maintenance activities within scheduling horizon are considered. Moreover, in a dynamic context, maintenance opportunities, defined as inactivity periods of the systems at which several maintenance activities could be executed with reduced maintenance costs, may randomly occur with time. The second objective of the paper is to propose a new algorithm to optimally update online the grouped maintenance planning by taking into account the maintenance opportunities. A numerical example of a five components system is finally introduced to illustrate the proposed dynamic grouping maintenance strategy