Switching- and hedging- point policy for preventive maintenance with degrading machines: application to a two-machine line

Maintenance and production are frequently managed as separate activities although they do interact. Disruptive events such as machine failures may find the company unready to repair the machine immediately leading to time waste. Preventive Maintenance may be carried out and maintenance time reduced to the effective task duration, in order to prevent time waste. Companies and researchers have been focusing on policies able to mitigate the impact of Preventive Maintenance on system availability, by exploiting the knowledge about degradation profiles in machines and the joint information from the machine state and the buffer level. In this work, the mathematical proof of the optimal threshold-based control policy for Preventive Maintenance with inventory cost, maintenance cost, backlog cost is provided. The control policy is defined in terms of buffer thresholds and dependency of the thresholds on the degradation condition. The optimal control policy is proved to include a combination of switching points and hedging points, where the first ones activate the Preventive Maintenance for a given condition and the latter ones control the production rate in order to minimize the surplus. An extensive experimental campaign analyzes the impact of system parameters such as the Maintenance duration on the cost function. The results show that there exists cases in which the optimal policy is dominated by the effect of the hedging points or the switching points, alternatively. Therefore, the proposed method is used to provide suggestions to the management for operative decisions, in order to choose the policy fitting best the system

On the design of a flow line with intermediate buffers and mixed corrective maintenance

We considered a mixed corrective maintenance policy for machines in a two-machine one-buffer flow line. The machines had stochastic processing times and suffered from unexpected failures. In the case of a failure, the machines were either minimally repaired or their failing components were replaced by spare parts. While the replacement strategy is rapid and the system can be considered new thereafter, spare parts provisioning and storage costs are very high. Thus, we additionally considered minimal repairs, which are less expensive and restore the system to a working condition at a minimum. We modeled the system as a continuous-time Markov chain. This approach was used to measure the performance of the flow line and the mixed corrective maintenance policy employed. To facilitate design decisions for the flow line, we considered both the cost of an interstage buffer and the maintenance costs for machines in line. We formulated an optimization problem based on a profit function that enables the simultaneous optimization of the buffer size and maintenance strategy. Our numerical analyses reveal useful insights into the performance and optimal design of the flow line depending on the utilized maintenance strategy

A study in joint maintenance scheduling and production planning

Master'sMASTER OF ENGINEERIN

Machine integrated health models for condition-based maintenance

Strojevi su podložni degradaciji zbog tehničkih kao i ne-tehničkih faktora koji im povećavaju mogućnost kvarova i pogoršavaju njihovo stanje zdravlja. Zbog toga raste zanimanje za nove metode procjenjivanja zdravstvenog stanja. Sada se inherentno zdravlje stroja procjenjuje praćenjem podataka koje pružaju senzori. Drugim riječima, razvoj inherentnog zdravlja ovisi jedino o razvoju tehničkih čimbenika te stoga ne daje sveobuhvatnu informaciju o stanju stroja. Ovaj rad uvodi koncepte "inherentnog zdravlja" i "integriranog zdravlja" kao i njihovu povezanost. Na osnovu procjene inherentnog zdravlja, integrirano zdravlje uzima u obzir ne-tehničke faktore koji se odnose na starost, radne uvjete i održavanje stroja. Učinkovitost održavanja se također razmatra integrirajući sekvencijalnu nesavršenu politiku održavanja u strategiju održavanja koja se zasniva na integriranim zdravstvenim uvjetima. Sveobuhvatnom procjenom i otkrivanjem u stvarnom vremenu stanja integriranog zdravlja, ovaj se model može koristiti kao podrška upravljanju zdravljem stroja i donošenju odluke o održavanju. U analizi pojedinih slučajeva, očekuje se da će se očite razlike između inherentnog zdravlja i integriranog zdravlja pojaviti u određenim uvjetima.Machines undergo degradation as a result of both technical factors and non-technical factors that increase the potential for failures and deteriorate their health condition, and there is growing interest in new methods for health condition assessment. Currently, the inherent health of a machine is evaluated by monitoring of the data acquired by sensors. In other words, the evolution of the inherent health depends only on the evolution of technical factors, and therefore does not comprehensively represent the overall condition of the machine. This study introduces the concepts of "inherent health" and "integrated health" as well as their relationship. On the basis of inherent health assessment, the integrated health considers the non-technical factors related to the age, working conditions, and maintenance of a machine. By integrating a sequential imperfect maintenance policy into the maintenance strategy based on the integrated health conditions, the maintenance effectiveness is also considered. Through comprehensive assessment and real-time detection of the integrated health condition, this model may be used to support machine health management and maintenance decision-making. In case studies, the obvious differences between inherent health and integrated health are expected to appear under certain circumstances

Machine integrated health models for condition-based maintenance

Strojevi su podložni degradaciji zbog tehničkih kao i ne-tehničkih faktora koji im povećavaju mogućnost kvarova i pogoršavaju njihovo stanje zdravlja. Zbog toga raste zanimanje za nove metode procjenjivanja zdravstvenog stanja. Sada se inherentno zdravlje stroja procjenjuje praćenjem podataka koje pružaju senzori. Drugim riječima, razvoj inherentnog zdravlja ovisi jedino o razvoju tehničkih čimbenika te stoga ne daje sveobuhvatnu informaciju o stanju stroja. Ovaj rad uvodi koncepte "inherentnog zdravlja" i "integriranog zdravlja" kao i njihovu povezanost. Na osnovu procjene inherentnog zdravlja, integrirano zdravlje uzima u obzir ne-tehničke faktore koji se odnose na starost, radne uvjete i održavanje stroja. Učinkovitost održavanja se također razmatra integrirajući sekvencijalnu nesavršenu politiku održavanja u strategiju održavanja koja se zasniva na integriranim zdravstvenim uvjetima. Sveobuhvatnom procjenom i otkrivanjem u stvarnom vremenu stanja integriranog zdravlja, ovaj se model može koristiti kao podrška upravljanju zdravljem stroja i donošenju odluke o održavanju. U analizi pojedinih slučajeva, očekuje se da će se očite razlike između inherentnog zdravlja i integriranog zdravlja pojaviti u određenim uvjetima.Machines undergo degradation as a result of both technical factors and non-technical factors that increase the potential for failures and deteriorate their health condition, and there is growing interest in new methods for health condition assessment. Currently, the inherent health of a machine is evaluated by monitoring of the data acquired by sensors. In other words, the evolution of the inherent health depends only on the evolution of technical factors, and therefore does not comprehensively represent the overall condition of the machine. This study introduces the concepts of "inherent health" and "integrated health" as well as their relationship. On the basis of inherent health assessment, the integrated health considers the non-technical factors related to the age, working conditions, and maintenance of a machine. By integrating a sequential imperfect maintenance policy into the maintenance strategy based on the integrated health conditions, the maintenance effectiveness is also considered. Through comprehensive assessment and real-time detection of the integrated health condition, this model may be used to support machine health management and maintenance decision-making. In case studies, the obvious differences between inherent health and integrated health are expected to appear under certain circumstances

Modelo de apoio à decisão para a manutenção condicionada de equipamentos produtivos

Doctoral Thesis for PhD degree in Industrial and Systems EngineeringIntroduction: This thesis describes a methodology to combine Bayesian control chart and CBM (Condition-Based Maintenance) for developing a new integrated model. In maintenance management, it is a challenging task for decision-maker to conduct an appropriate and accurate decision. Proper and well-performed CBM models are beneficial for maintenance decision making. The integration of Bayesian control chart and CBM is considered as an intelligent model and a suitable strategy for forecasting items failures as well as allow providing an effectiveness maintenance cost. CBM models provides lower inventory costs for spare parts, reduces unplanned outage, and minimize the risk of catastrophic failure, avoiding high penalties associated with losses of production or delays, increasing availability. However, CBM models need new aspects and the integration of new type of information in maintenance modeling that can improve the results. Objective: The thesis aims to develop a new methodology based on Bayesian control chart for predicting failures of item incorporating simultaneously two types of data: key quality control measurement and equipment condition parameters. In other words, the project research questions are directed to give the lower maintenance costs for real process control. Method: The mathematical approach carried out in this study for developing an optimal Condition Based Maintenance policy included the Weibull analysis for verifying the Markov property, Delay time concept used for deterioration modeling and PSO and Monte Carlo simulation. These models are used for finding the upper control limit and the interval monitoring that minimizes the (maintenance) cost function. Result: The main contribution of this thesis is that the proposed model performs better than previous models in which the hypothesis of using simultaneously data about condition equipment parameters and quality control measurements improve the effectiveness of integrated model Bayesian control chart for Condition Based Maintenance.Introdução: Esta tese descreve uma metodologia para combinar Bayesian control chart e CBM (Condition- Based Maintenance) para desenvolver um novo modelo integrado. Na gestão da manutenção, é importante que o decisor possa tomar decisões apropriadas e corretas. Modelos CBM bem concebidos serão muito benéficos nas tomadas de decisão sobre manutenção. A integração dos gráficos de controlo Bayesian e CBM é considerada um modelo inteligente e uma estratégica adequada para prever as falhas de componentes bem como produzir um controlo de custos de manutenção. Os modelos CBM conseguem definir custos de inventário mais baixos para as partes de substituição, reduzem interrupções não planeadas e minimizam o risco de falhas catastróficas, evitando elevadas penalizações associadas a perdas de produção ou atrasos, aumentando a disponibilidade. Contudo, os modelos CBM precisam de alterações e a integração de novos tipos de informação na modelação de manutenção que permitam melhorar os resultados.Objetivos: Esta tese pretende desenvolver uma nova metodologia baseada Bayesian control chart para prever as falhas de partes, incorporando dois tipos de dados: medições-chave de controlo de qualidade e parâmetros de condição do equipamento. Por outras palavras, as questões de investigação são direcionadas para diminuir custos de manutenção no processo de controlo.Métodos: Os modelos matemáticos implementados neste estudo para desenvolver uma política ótima de CBM incluíram a análise de Weibull para verificação da propriedade de Markov, conceito de atraso de tempo para a modelação da deterioração, PSO e simulação de Monte Carlo. Estes modelos são usados para encontrar o limite superior de controlo e o intervalo de monotorização para minimizar a função de custos de manutenção.Resultados: A principal contribuição desta tese é que o modelo proposto melhora os resultados dos modelos anteriores, baseando-se na hipótese de que, usando simultaneamente dados dos parâmetros dos equipamentos e medições de controlo de qualidade. Assim obtém-se uma melhoria a eficácia do modelo integrado de Bayesian control chart para a manutenção condicionada

Conception conjointe des politiques de contrôle de production, de qualité et de maintenance des systèmes manufacturiers en dégradation

RÉSUMÉ : La gestion de la production, le contrôle de la qualité et la planification de la maintenance sont les trois principales fonctions de la gestion des opérations dans les usines manufacturières. Dans la pratique, ces trois fonctions sont souvent gérées séparément, bien qu’elles soient, en réalité, étroitement inter-reliées. Plusieurs recherches ont été menées depuis des décennies afin de concevoir et d’optimiser conjointement les politiques de contrôle de la production, de la qualité et de la maintenance. Cette tendance est motivée par le fait que les politiques d’intégration des trois fonctions permettent d’améliorer la productivité et de réduire considérablement les coûts. Cependant, dans la quasi-totalité des modèles d’intégration dans la littérature, seulement deux fonctions sont intégrées à la fois. De plus, pour des raisons de simplification, ces modèles sont basés sur certaines hypothèses simplificatrices et irréalistes pour modéliser la dégradation de la qualité des produits et de la fiabilité des machines. Par exemple, ces modèles négligent souvent l’impact des opérations de production sur l’intensité de dégradation, mais aussi la corrélation entre les dégradations de la qualité et de la fiabilité. Par ailleurs, les politiques de contrôle de la qualité utilisées dans ces modèles sont soit les cartes de contrôle, soit le contrôle à 100%. Toutefois, l’intégration des plans d’échantillonnage, qui représentent une branche importante de Contrôle Statistique de la Qualité, avec les politiques de production et de maintenance n’a pas été étudiée encore dans la littérature. Ces plans sont largement utilisés dans l’industrie depuis longtemps afin d’éviter le coût excessif du contrôle à 100% et d’assurer en même un contrôle statistique de la qualité des produits livrés. Cette thèse s’intéresse au problème de conception conjointe des politiques de contrôle de la production, de la qualité et de la maintenance. L’objectif principal de la recherche est d’intégrer les plans d’échantillonnage avec les politiques de production et de maintenance des systèmes où la qualité et la fiabilité sont les deux sujettes à la dégradation. Nous proposons une approche pratique de modélisation et d’optimisation de ces politiques qui permet de prendre en considération la dynamique complexe de la dégradation telle que dans la réalité des systèmes manufacturiers. En outre, nous étudions les propriétés statistiques des plans d’échantillonnage afin de montrer comment des informations pertinentes fournies par ces plans peuvent être intégrées dans la planification des activités de maintenance préventive afin d’améliorer les performances globales des systèmes manufacturiers. Les contributions scientifiques réalisées dans le cadre de cette thèse sont présentées sous forme de quatre articles de revue. Le premier article introduit un modèle d’intégration du plan d’échantillonnage simple avec la commande de la production pour un système de fabrication par lots. Ce modèle vise essentiellement à étudier les interactions entre les paramètres du plan d’échantillonnage et les paramètres de gestion de la production tels que la taille du lot de production et le stock de sécurité. Ensuite, une extension de ce modèle est proposée dans le deuxième article afin de considérer l’aspect dynamique de la dégradation de la qualité et de la fiabilité en fonction des opérations de production et d’intégrer une politique de maintenance préventive. L’objectif est d’optimiser conjointement les paramètres de contrôle de la production, de la qualité et de la maintenance de façon à minimiser le coût total des opérations, tout en respectant une contrainte sur la qualité après-contrôle. De plus, cet article vise à montrer l’utilité des informations issues du plan d’échantillonnage simple pour la surveillance de la qualité de la production et pour l’organisation des actions de maintenance préventive. Une analyse comparative de l’utilisation de plan d’échantillonnage par rapport au contrôle à 100% est aussi fournie afin de quantifier les gains économiques qui en découleraient. Le troisième article propose une approche d’intégration du plan d’échantillonnage continu de type-1 (CSP-1) avec les politiques de production et de maintenance préventive pour les systèmes de production continue. L’objectif est d’étendre l’applicabilité du plan CSP-1 aux processus de production en dégradation, puisqu’il est actuellement applicable seulement aux processus stables. Un autre objectif de cet article est de quantifier les bénéfices de l’utilisation de CSP-1 par rapport au contrôle à 100%, et de montrer aussi comment le couplage de CSP-1 avec la maintenance préventive permet d’améliorer les performances des systèmes en dégradation. Finalement, le quatrième article introduit un modèle de contrôle conjoint de la production, de la qualité et de la maintenance d’une ligne de production dont les machines sont sujettes à la dégradation. En plus, les machines peuvent tomber en panne à cause des pièces non-conformes fabriquées dans les processus en amont. L’objectif est de montrer l’importance de la corrélation entre les dégradations de la qualité et de la fiabilité dans la modélisation de la dynamique des systèmes manufacturiers, et d’étudier l’effet de cette corrélation sur les paramètres optimaux du contrôle de la production, de la qualité et de la maintenance. Le second objectif de cet article est de montrer que les activités de maintenance et de contrôle de la qualité à un certain niveau de la ligne de production contribuent aussi à l’amélioration de la fiabilité des machines en aval.----------ABSTRACT : Production, quality and maintenance control are the three main functions of operations management in manufacturing plants. Traditionally, they have been treated by scientists and practitioners as separate problems even though they are strongly interrelated. In the past three decades, the integration of production, maintenance and quality control has attracted much attention in the literature. This trend is motivated by the fact that integrated control policies generally result in better manufacturing performance and significant cost savings. Nevertheless, most of the existing integrated models in the literature integrate only two functions at a time. Moreover, for simplicity, almost all of the integrated models are based on several simplifying assumptions that may make them unrealistic. For example, the complex dynamics of quality and reliability degradations such as the impact of operations speed on degradation intensity and the correlation between quality and reliability degradations have been always overlooked in the literature of integrated models. On the other hand, the quality control policies used in the existing integrated models are either 100% inspection of all parts produced or statistical process control tools such as the control charts. However, acceptance sampling which constitutes an important branch of the Statistical Quality Control has never been integrated with production and maintenance policies. Acceptance sampling plans and procedures have been widely used in industry for a long time to reduce the cost and time of quality inspection and to statistically control the outgoing quality. This research considers the problem of the joint design of production, quality and maintenance control policies of stochastic manufacturing systems. Specifically, the main objective of this thesis is to integrate sampling inspection techniques with production and maintenance control policies for systems subject to both quality and reliability degradations. We provide a practical modeling framework to adequately pattern the complex dynamics of degradation processes as in the real-life in order to develop new effective integrated control policies. Moreover, we investigate the intrinsic statistical properties of acceptance sampling plans in order to demonstrate how they can be coupled with condition-based maintenance to improve the overall performance of degrading manufacturing systems. This thesis is comprised of four journal articles. The first article investigates the joint production and quality control of a batch-processing production system which is unreliable and imperfect. A single acceptance sampling plan by attributes is used for quality control. The objective of this article is to introduce an integrated model for the joint optimization of the production lot size, the safety stock and the sampling plan parameters which minimize the total cost incurred. This aims to provide a better understanding of the interactions between the optimal production-inventory settings and the optimal sampling plan parameters. As an extension of this model, the second article considers that quality and reliability degradations are operation-dependent. Moreover, a preventive maintenance strategy is incorporated into the integrated control policy. Thus, the objective is to jointly optimize the production, quality and maintenance control parameters. This article investigates the statistical characteristics of the single sampling plan to show the relevance of quality information resulting from such a quality control to the maintenance decision-making. Also, a comparative study is conducted to quantify the economic savings that can be realized by using the sampling plans for degrading systems rather than 100% inspection. The third article addresses the joint economic design of production control, type-1 continuous sampling plan (CSP-1) and preventive maintenance of continuous-flow manufacturing systems. The objective is to show how integrated control policies can extend the application of continuous sampling plans to degrading production systems, as they are presently limited only to stable processes. In this article, three quality control policies are considered and compared: 100% inspection, the classical CSP-1 as in the standard procedures and a CSP-1 plan with a stopping rule that is coupled with condition-based maintenance. This aims to quantify the economic savings that can be achieved by using the CSP-1 compared to 100% inspection and to demonstrate how CSP-1 with an inspection stopping rule for degrading processes is more cost-effective than the classical CSP-1. Finally, the fourth article investigates the joint design of production, quality and maintenance control policies for manufacturing lines. We consider a small production line composed of two machines subject to quality and reliability degradations. The second machine is also subject to failures caused by defective products manufactured in upstream processes. The main objective of this article is to study the interactions between the optimal production, quality and maintenance control settings and the effect of failures correlation on those settings. Also, we show how maintenance and quality control activities in preceding stages can play an important role in the reliability improvement of the subsequent machines