The Integration of Maintenance Decisions and Flow Shop Scheduling

In the conventional production and service scheduling problems, it is assumed that the machines can continuously process the jobs and the information is complete and certain. However, in practice the machines must stop for preventive or corrective maintenance, and the information available to the planners can be both incomplete and uncertain. In this dissertation, the integration of maintenance decisions and production scheduling is studied in a permutation flow shop setting. Several variations of the problem are modeled as (stochastic) mixed-integer programs. In these models, some technical nuances are considered that increase the practicality of the models: having various types of maintenance, combining maintenance activities, and the impact of maintenance on the processing times of the production jobs. The solution methodologies involve studying the solution space of the problems, genetic algorithms, stochastic optimization, multi-objective optimization, and extensive computational experiments. The application of the problems and managerial implications are demonstrated through a case study in the earthmoving operations in construction projects

Multi-objective optimization for time-based preventive maintenance within the transport network: a review

Preventive maintenance in transportation is essential not only to safeguard billions in business and infrastructure investment, but also to guarantee safety, reliability and efficacy within the network. Government, industry and society have been increasingly recognising the importance of keeping transport units condition well-preserved. The challenge, however, is to achieve optimal performance of the existing transport systems within acceptable costs, effective workforce use and minimum disruption. Those are generally conflicting objectives. Multi-objective optimisation approaches have served as powerful tools to assist stakeholders to properly deploy preventive maintenance in industry. In this study, we review the research conducted in the application of multi-objective optimisation for preventive maintenance in transport-related activities. We focus on time-based preventive maintenance for production, infrastructure, rail and energy providers. In our review, we are interested in aspects such as the types of problems addressed, the existing objectives, the approaches to solutions, and how the outcomes obtained support decision

Integration of production, maintenance and quality : Modelling and solution approaches

Dans cette thèse, nous analysons le problème de l'intégration de la planification de production et de la maintenance préventive, ainsi que l'élaboration du système de contrôle de la qualité. Premièrement, on considère un système de production composé d'une machine et de plusieurs produits dans un contexte incertain, dont les prix et le coût changent d'une période à l'autre. La machine se détériore avec le temps et sa probabilité de défaillance, ainsi que le risque de passage à un état hors contrôle augmentent. Le taux de défaillance dans un état dégradé est plus élevé et donc, des coûts liés à la qualité s’imposent. Lorsque la machine tombe en panne, une maintenance corrective ou une réparation minimale seront initiées pour la remettre en marche sans influer ses conditions ou le processus de détérioration. L'augmentation du nombre de défaillances de la machine se traduit par un temps d'arrêt supérieur et un taux de disponibilité inférieur. D'autre part, la réalisation des plans de production est fortement influencée par la disponibilité et la fiabilité de la machine. Les interactions entre la planification de la maintenance et celle de la production sont incorporées dans notre modèle mathématique. Dans la première étape, l'effet de maintenance sur la qualité est pris en compte. La maintenance préventive est considérée comme imparfaite. La condition de la machine est définie par l’âge actuel, et la machine dispose de plusieurs niveaux de maintenance avec des caractéristiques différentes (coûts, délais d'exécution et impacts sur les conditions du système). La détermination des niveaux de maintenance préventive optimaux conduit à un problème d’optimisation difficile. Un modèle de maximisation du profit est développé, dans lequel la vente des produits conformes et non conformes, les coûts de la production, les stocks tenus, la rupture de stock, la configuration de la machine, la maintenance préventive et corrective, le remplacement de la machine et le coût de la qualité sont considérés dans la fonction de l’objectif. De plus, un système composé de plusieurs machines est étudié. Dans cette extension, les nombres optimaux d’inspections est également considéré. La fonction de l’objectif consiste à minimiser le coût total qui est la somme des coûts liés à la maintenance, la production et la qualité. Ensuite, en tenant compte de la complexité des modèles préposés, nous développons des méthodes de résolution efficaces qui sont fondées sur la combinaison d'algorithmes génétiques avec des méthodes de recherches locales. On présente un algorithme mimétique qui emploi l’algorithme Nelder-Mead, avec un logiciel d'optimisation pour déterminer les valeurs exactes de plusieurs variables de décisions à chaque évaluation. La méthode de résolution proposée est comparée, en termes de temps d’exécution et de qualités des solutions, avec plusieurs méthodes Métaheuristiques. Mots-clés : Planification de la production, Maintenance préventive imparfaite, Inspection, Qualité, Modèles intégrés, MétaheuristiquesIn this thesis, we study the integrated planning of production, maintenance, and quality in multi-product, multi-period imperfect systems. First, we consider a production system composed of one machine and several products in a time-varying context. The machine deteriorates with time and so, the probability of machine failure, or the risk of a shift to an out-of-control state, increases. The defective rate in the shifted state is higher and so, quality related costs will be imposed. When the machine fails, a corrective maintenance or a minimal repair will be initiated to bring the machine in operation without influencing on its conditions or on the deterioration process. Increasing the expected number of machine failures results in a higher downtime and a lower availability rate. On the other hand, realization of the production plans is significantly influenced by the machine availability and reliability. The interactions between maintenance scheduling and production planning are incorporated in the mathematical model. In the first step, the impact of maintenance on the expected quality level is addressed. The maintenance is also imperfect and the machine conditions after maintenance can be anywhere between as-good-as-new and as-bad-as-old situations. Machine conditions are stated by its effective age, and the machine has several maintenance levels with different costs, execution times, and impacts on the system conditions. High level maintenances on the one hand have greater influences on the improvement of the system state and on the other hand, they occupy more the available production time. The optimal determination of such preventive maintenance levels to be performed at each maintenance intrusion is a challenging problem. A profit maximization model is developed, where the sale of conforming and non-conforming products, costs of production, inventory holding, backorder, setup, preventive and corrective maintenance, machine replacement, and the quality cost are addressed in the objective function. Then, a system with multiple machines is taken into account. In this extension, the number of quality inspections is involved in the joint model. The objective function minimizes the total cost which is the sum of maintenance, production and quality costs. In order to reduce the gap between the theory and the application of joint models, and taking into account the complexity of the integrated problems, we have developed an efficient solution method that is based on the combination of genetic algorithms with local search and problem specific methods. The proposed memetic algorithm employs Nelder-Mead algorithm along with an optimization package for exact determination of the values of several decision variables in each chromosome evolution. The method extracts not only the positive knowledge in good solutions, but also the negative knowledge in poor individuals to determine the algorithm transitions. The method is compared in terms of the solution time and quality to several heuristic methods. Keywords : Multi-period production planning, Imperfect preventive maintenance, Inspection, Quality, Integrated model, Metaheuristic

Assessing the effect of proactive maintenance scheduling on maintenance costs and airline profitability: The case of Turkish Airlines Technic

This study mainly aims to examine the perception of Turkish Airlines Technic staff about the effect of proactive maintenance scheduling (PMS) on maintenance costs (MCs) and airline profitability(AP). Another purpose of the study is to reveal if perception of the staff changes according to demographic features and experience of the staff. As far as it is known, there is no direct study addressing the effects of PMS on MCs and airline profitability. The study is considered to be a first in this context. In the study, Turkish Airlines-THY was chosen as the company that was handled. The fact that the company has a separate special maintenance&repair group (Turkish Airlines Technic-THYT) was effective in the selection of this company. Some additional qualifications (very rooted, with corporate governance, Turkey's top largest&full service carrier, member of IATA and Star Alliance, and a listed company (in BIST) were also among other factors affecting the selection. Methodologically, it was used a quantitative survey with a sample of 133 THYT staff. Staff has been chosen among departments that takes place actively/directly in maintenance. Besides questions that aim to measure the perception of THYT staff on the effects of PMS to MCs and AP, some demographic and experience related questions were asked in order to find out if perception of the staff changes according to their qualifications. The data were collected by online survey method and analyzed with SPSS version 22. Necessary tests together with Chi-square and Fisher’s tests were carried out to analyze the results. It was concluded that there is a strong correlation between PMS and the MCs. The study proved that PMS has a great decreasing effect on MCs and a great increasing effect on AP. The study also revealed that THYT personnel is like-minded that PMS reduces MCs and increases AP as well

Assessing alignment of maintenance practices to total productive maintenance best practice: a case study within a South African conglomerate

A research report submitted in partial fulfilment of the requirements for the degree in Master of Science in Engineering to the Faculty of Engineering and the Built Environment, University of Witwatersrand, Johannesburg, 2017In today’s competitive world, a good maintenance approach is important for companies to remain competitive and control operational costs. There are various maintenance methods that can be applied in any organization, singly or combined, and such an approach must lead to increased availability, reliability and operability of equipment at an acceptable cost. World Class Manufacturing (WCM) has become a buzz phrase across the whole manufacturing world. Total Productive Maintenance (TPM) is the cornerstone for WCM, and an integral part of any manufacturing enterprise that aspires to be world class. The purpose of the research was to carry out an assessment of alignment of maintenance practices to TPM best practice within a South African Conglomerate. The study identified current maintenance practices, challenges faced, and gaps that required improvement. It also assessed the overall alignment of such practices to full TPM implementation. A thorough investigation of current maintenance practices was done and a clear picture was established. These practices were then compared with the ideal requirements for best TPM practice and implementation. Data for the research was obtained through interviews, performance measures from reports and a confidential on line survey. Poor industrial relations, insufficient records keeping and aged equipment without any manuals all rendered it difficult to implement TPM. The results revealed that the conglomerate was in the process of implementing a maintenance program however the maintenance practices in place were not fully aligned to the requirements of TPM.XL201

Study on bridge inspections, A: identifying barriers to new practices and providing strategies for change

2021 Summer.Includes bibliographical references.Bridge inspections are one of the key elements required for a successful bridge management process to ensure adequate bridge performance. Inspections significantly inform maintenance decisions and can help in managing maintenance activities to achieve a reliable bridge network. In the United States (U.S.) routine visual inspections are required for most bridges at a maximum interval of 24-months regardless of the bridge condition. However, limitations of current bridge inspection practices impact the quality of information provided about bridge condition and the subsequent decisions made based on that information. Accordingly, the overarching goal of this research project is to support bridge inspection practices by providing a systematic and rational framework for bridge inspection planning and identifying the factors that can facilitate innovation and research transfer in the bridge inspection field. To do so, this dissertation includes three separate yet related studies; each focusing on essential aspects of bridge inspection planning. Much research in bridge inspection has been conducted to improve the inspection planning process. The first study provides an overview of current bridge inspection practices in the U.S. and conducts a systematic literature review on innovations in the field of bridge inspection planning to identify research gaps and future needs. This study provides a background on the history of bridge inspection in the U.S., including current bridge inspection practices and their limitations, and analyzes the connections between nondestructive evaluation techniques, deterioration models and bridge inspection management. The primary emphasis of the first study is a thorough analysis of research proposing and investigating different methodologies for inspection planning. Studies were analyzed and categorized into three main types of inspection planning approaches; methods that are based on: reliability, risk analysis, and optimization approaches. This study found that one of the main barriers that may be preventing the implementation of new inspection planning frameworks in practice is that the approaches presented focus on a single bridge element or deterioration mechanism in the decision-making process. Additionally, it was concluded that approaches in the literature are either complex to apply or depend solely on expert judgement. Limitations of the uniform calendar-based approach used to schedule routine inspections have been reported in the literature. Accordingly, the objective of the second study is to provide a new systematic approach for inspection planning that integrates information from bridge condition prediction models, inspection data, and expert opinion using Bayesian analysis to enhance inspection efficiency and maintenance activities. The proposed uncertainty-based inspection framework can help bridge owners avoid unnecessary or delayed inspections and repair actions, determine the inspection method, and consider more than one deterioration process or bridge component during the inspection planning process. The inspection time and method are determined based on the uncertainty and risks associated with the bridge condition. As uncertainty in the bridge condition reaches a defined threshold, an inspection is scheduled utilizing nondestructive techniques to reduce the uncertainty level. The framework was demonstrated on a new and on an existing reinforced concrete bridge deck impacted by corrosion deterioration. The results showed that the framework can reduce the number of inspections compared to conventional scheduling methods, while also reducing the uncertainty regarding the transition in the bridge deck condition and repair time. As identified through the first study, over the last two decades many researchers have focused on providing new ideas to improve conventional bridge inspection practices, however, little guidance is provided for implementing these new research products in practice. This, along with resistance to change and complexity of the proposed ideas, resulted in a lack of consistency and success in applying new technologies in bridge inspection programs across state departments of transportation (DOTs). Accordingly, the third paper presents a qualitative study set out to identify the factors that can help improve research products and accelerate change and research transfer in bridge inspection departments. This study used semi-structured interviews, written interviews, and questionnaires for data collection and engaged with twenty-six bridge staff members from different DOTs. The findings of this study are expected to be both specific to changes in bridge inspection practice and have some generalizability to other significant changes to engineering practice at DOTs. To improve research products, this study suggested that researchers need to collaborate more with DOT staff members and provide relevant research products that are not specific to certain bridge cases and can be applied on different bridges. Also, to facilitate change in transportation organizations, change leaders should focus on showing the need for change, gaining support from the FHWA, allocating the required resources, and enhancing the capacity of DOT staff members through training and effective communication. The investigation also presented participants' opinions on some of the aspects related to conventional inspection practices such as their support of a uniform inspection interval over a variable interval, and the main barriers limiting the use of NDE methods. This study contributes to the body of knowledge in the bridge inspection field by providing a new inspection planning approach that depends on the uncertainty and the risks associated with the bridge condition and uses both computational methods and expert judgment allowing bridge owners select inspection time and method while considering more than one deterioration process or bridge element. In addition, this study presents some of the factors that can help reduce the gap between research and practice and facilitate innovation and change in transportation organizations