Dissertations / Theses on the topic 'Maintenance strategies integrated into production'

Au cours de ces récentes années, le développement des énergies renouvelables, en particulier l'énergie solaire et l'énergie éolienne, a attiré comme méthode alternative de production d'énergie, l'attention du monde entier avec une croissance exceptionnelle de sa production. Selon le rapport de Global Energy, l'énergie solaire mondiale devrait avoir atteint une capacité cumulée de 1 TW, tandis que l'énergie éolienne devrait avoir été multipliée par 3 ou 4 mégas par rapport à la production en 2020. Cette augmentation des énergies solaire et éolienne implique des investissements financiers très importants. Cependant, avec cet énorme potentiel d'investissement et l'augmentation significative de la capacité de production, il y a une responsabilité supplémentaire, souvent négligée : la gestion des centrales électriques pour assurer le coût total du cycle de vie le plus bas (Life Cycle Cost). Comme tout système de production standard, les composants de production d'énergie renouvelable (solaire et éolienne dans notre cas) sont sujets à des défaillances aléatoires qui interrompent la production et l'approvisionnement de la demande. La maintenance est identifiée comme une cause majeure d'accidents, on peut noter le manque de savoir-faire technique dans l'exploitation d'un équipement ou l'absence d'un bon plan de routine de maintenance. Dans le cadre des efforts visant à améliorer l'efficacité et la performance des centrales électriques à énergie renouvelable, nous proposons des modèles pour optimiser la production d'énergie et la maintenance dans nos études de cas sélectionnées (centrale solaire de Sokoto et parc éolien de Katsina au Nigéria). À cet égard, nous avons développé de nouvelles politiques de maintenance intégrées à la production d'énergie des systèmes d'énergie solaire et éolienne. La stratégie de maintenance préventive adoptée dans cette thèse est une stratégie de maintenance parfaite sur les composants sélectionnés pour la maintenance et une maintenance sélective imparfaite sur le système (solaire PV et éolienne). Le manque de batterie en cas de sous-production et les pertes de maintenance sont des défis considérés dans cette étude. La méthodologie que nous avons développée consiste à résoudre le problème d'optimisation de la production d'énergie et de la maintenance en utilisant la méthode théorique ainsi que la méthode d'apprentissage automatique (ANN et SVM) afin de satisfaire une demande aléatoire d'énergie pendant un horizon fini. Nous avons également étudié l'influence des conditions environnementales et opérationnelles des systèmes, puis validé les modèles par des exemples numériques et des études de sensibilité prouvant la robustesse des modèles développés
The development of renewable energy, especially solar and wind energy, over the recent years has gained global attention as an alternative method of generating energy experiencing exceptional growth in its production. In The Global Energy report, global solar energy is expected to have reached a cumulative capacity of 1TW while the wind energy is expected to have multiplied up to 3 to 4 times from mega production in the year 2020. This increase in the solar and wind power implies very significant financial investments. However, with this huge investment potential and significant increase in generation capacity, there is an additional, often overlooked responsibility: managing the power plants to ensure the lowest total life cycle cost (Life Cycle Cost). Like any standard production system, renewable energy (solar and wind energy in our case) generation components are subject to random failure, which interrupts production and supply of demand. Maintenance is identified as a major cause of accidents, lack of technical know-how of an equipment and the absence of a good maintenance routine plan. As part of the efforts to improve the efficiency and performance of renewable energy power plants, we propose models to optimize the power production and maintenance of our selected case studies (Sokoto solar plant and Katsina wind farm). In this regard, we developed new integrated maintenance policies integrated with production of the energy production from solar and wind energy systems. The preventive maintenance strategy adopted in this thesis is perfect maintenance strategy on the selected components for maintenance and an imperfect selective maintenance on the system (solar PV and wind turbine). Battery shortage in case of under-production and maintenance losses are challenges considered in this study. The methodology we developed entails solving the problem of energy production and maintenance optimization by using the theoretical method as well as machine learning method (ANN and SVM) in order to satisfy a random demand of energy during a finite horizon. We also studied the influence of environmental and operational condition of the systems and then validated the models by numerical examples and sensitivity studies proving the robustness of the developed models

L'industrie de la production actuelle est caractérisée par des progrès significatifs : une augmentation massive de la haute technologie, l'émergence de clients exigeants, des marchés compétitifs, une qualité de produit variée et des demandes aléatoires ont exigé la collaboration des aspects interdépendants de la production. La production, la maintenance et la qualité sont les aspects les plus critiques du système industriel. Nous nous intéressons à l'optimisation de la maintenance qui joue un rôle essentiel dans la satisfaction du client, la durabilité et le développement des entreprises. Notre étude est centrée sur le développement de la production et de la maintenance intégrées dans une carte de contrôle de la politique de qualité. Nous proposons de nouvelles stratégies de maintenance intégrée avec une analyse approfondie des améliorations continues de la fiabilité du processus de production et traitées sous les contraintes des exigences du client (Service, qualité et coût). L'intégration et la coordination optimale de ces facteurs de production n'est pas facile et représente un défi pour les entreprises industrielles, et sont plus difficiles avec les causes multi-assignables de la variation du processus de production. Pour répondre à ce problème, ce travail de recherche a utilisé l'outil carte de contrôle en combinaison avec les principes de l'AFNOR connus sous le nom de Règle des sept comme impliqués dans la gestion de la qualité. Pour surveiller, analyser et diriger les actions de maintenance appropriées pour l'amélioration continue de la fiabilité du système le long des différents scénarios de processus multiples comme niveaux de décision. Nous utilisons les interactions entre le processus de production et la qualité du produit pour des stratégies de maintenance qui réduisent la défaillance du système de production en améliorant la fiabilité du processus et en réduisant les produits non conformes. L'étude a porté de manière significative sur la qualité, les outils de qualité et leurs applications dans le contrôle de la production et de la maintenance. La technique que nous avons utilisée pour optimiser la maintenance et le contrôle de la qualité d'un système de production intégré est un outil de carte de contrôle basé sur la mesure et l'analyse statistique des paramètres de qualité. Nous modélisons différents problèmes de production et développons une politique de contrôle pour des systèmes de production à défaillance aléatoire qui doivent satisfaire les exigences des clients de manière dynamique tout au long de l'horizon de production fini. Nous avons introduit un modèle mathématique pour minimiser les coûts totaux de production, d'inventaire, de maintenance et de contrôle de la qualité. L'optimisation de la stratégie de maintenance a été intégrée dans un outil d'information sur les cartes de contrôle. Sur la base de la variation du taux de production et de son impact sur la dégradation de la machine, le nombre de maintenance, les temps et les intervalles nécessaires à une prise de décision prudente sont déterminés par l'algorithme développé. Dans ce contexte, cette recherche présente la dérivation pour différents cas de toutes les probabilités pour le processus d'être dans ou hors de contrôle, les durées moyennes d'exécution, et les durées de cycle de restauration. Sur la base du facteur de dégradation, de nouvelles équations de taux de défaillance sont formulées, puis le taux de défaillance moyen pour chaque cas, nous avons formulé différents modèles d'optimisation des coûts de maintenance. L'approche proposée est utile pour le calcul précis et la minimisation du coût total de maintenance. Elle optimise le coût total de production en considérant tous les états possibles du processus de production dus à des causes multiples. Notre travail contribue à l'émergence de techniques de gestion de la qualité et d'amélioration des performances qui contribueront au développement des entreprises de production
The current production industry is characterise by significant progress: a massive increase in high technology, the emergence of exigent customers, competitive markets, varied product quality, and random demands required the collaborations of the inter-related aspects of production. The production, maintenance, and quality are the most critical aspects of the industrial system. We are interested in optimising maintenance that plays a critical role in customer satisfaction, sustainability, and the development of companies. Our study is centred on developing production and maintenance integrated into a control chart of quality policy. We propose new integrated maintenance strategies with an in-depth analysis of the continuous production process reliability improvements and treated under customer requirements (Service, quality, and cost) constraints. The integration and optimal coordination of these factors of production is not easy and represent a challenge for industrial companies, and are more challenging with multi-assignable causes of production process variation. To address this problem, this research work employed the use of a control chart tool in combination with the AFNOR principles known as Rule of seven as involved in quality management. To monitor, analyses and direct appropriate maintenance actions for continuous system reliability improvements along the different multiple process scenarios as decision levels. We use the interactions between the production process and product quality for strategies of maintenance which reduce the failure of the production system by improving process reliability and reducing the no conformal products. The study Significantly focused on quality, quality tools, and their applications in production and maintenance control. The technique we used to optimise the maintenance and quality control of an integrated production system is a control chart tool based on statistical measurement and analysis of quality parameters. We model different production problems and develop a control policy for randomly failing production systems that must satisfy customer requirements dynamically throughout the finite production horizon. We introduced a mathematical model to minimise the total costs of production, inventory, maintenance, and quality control. The optimisation of the maintenance strategy was integrated into a control chart tool information. Based on the production rate variation and its impact on machine degradation the number of maintenance, times, and intervals needed for prudent decision-making is determined by the developed algorithm. In this context, this research presents the derivation for different cases of all the probabilities for the process to be in or out of control, the average run lengths, and the restoration cycle durations. Based on the degradation factor, new failure rate equations are formulated, and then the average failure rate for each case, we formulated different maintenance cost optimisation models. The proposed approach is useful for precise calculation and minimisation of the total maintenance cost. Which optimises total production cost considering all possible production process statuses due to multiple causes. Our work contributes to the emergence of quality management and performance improvement techniques that will contribute to the development of production companies

Dans cette étude, on s’intéresse à un système de production par usinage qui est l’un des procédés de fabrications les plus adoptés par les différentes industries mécaniques (automobile, aéronautique, ferroviaire…). L'objectif de cette thèse pluridisciplinaire (Mécanique et Génie Industriel) est double : (1) le développement d’un nouveau modèle thermomécanique de la coupe oblique, avec vibration, en usinage à sec et (2) la maximisation du profit afin d’établir conjointement une stratégie de production et un plan de maintenance préventive. Le couplage entre l’opération d’usinage et la partie « optimisation simultanée des coûts de production et de maintenance » se fait à travers la prise en compte de l’effet des conditions de coupe sur l’état de la surface généré et sur l’usure de l’outil de coupe. Dans l’approche proposée, l’usure est prise en compte via la loi empirique de Taylor et l’état de la surface usinée est prédite à travers une nouvelle modélisation des vibrations en coupe oblique. Le premier objectif de la thèse concerne le développement d’une nouvelle modélisation thermomécanique de la coupe oblique avec vibration. Dans ce modèle analytique de coupe, le système vibratoire outil-porte outil est assimilé à un système à un seul degré de liberté dans la direction d’avance. On prend en compte le couplage entre les oscillations de l’outil, le processus thermomécanique de formation du copeau ainsi que l’effet régénératif. Ce dernier résulte de la variation de la quantité de matière à usiner entre deux passes successives. Les sorties de l’outil de la zone de coupe en fonction des conditions de coupe sont également considérées. Le couplage entre l’ensemble de ces mécanismes rend le problème à résoudre fortement non linéaire. Un algorithme de résolution permettant de réduire le temps de calcul a été mis en place. Le deuxième objectif de la thèse est réalisé par le biais du développement d’un modèle analytique. Dans ce modèle, le profit à maximiser, intègre les revenus de vente du produit fini, les coûts de production et de maintenance tout en considérant l’impact des conditions d’usinage sur les coûts de production, la qualité des pièces usinées ainsi que la dégradation du système de production. On prend donc en compte d’une manière simultanée l’impact des conditions d’usinage sur trois aspects fondamentaux pour la partie « optimisation simultanée des coûts de production et de maintenance ». Le premier concerne l’impact des conditions d’usinage sur la durée et les coûts de production. Le deuxième concerne l’impact sur la dégradation du système d’usinage et par conséquent sur le plan de maintenance optimal à adopter. Le troisième concerne l’impact sur la qualité du produit fini qui affecte directement les coûts de vente et plus précisément les coûts de reviens. Ces interactions sont prises en considération par le biais du développement d’un modèle analytique afin d’établir un plan optimal de maintenance intégrée à la production pour le système d’usinage
In this study, we are interested in a machining production system which is one of the manufacturing processes most adopted by the various mechanical industries (automotive, aviation…etc.). The objective of this multidisciplinary thesis (Mechanics and Industrial Engineering) is double: (1) the development of a new thermomechanical model of oblique cutting in dry machining and (2) the maximization of profit in order to establish a strategy production and a preventive maintenance plan.The coupling between the machining operation and the part "simultaneous optimization of production and maintenance costs" is done by considering the effect of cutting conditions on the generated surface quality and on the tool wear. In the proposed approach, wear is taken into account through Taylor's empirical law and the machined surface quality is predicted via a new model of vibrations in oblique cutting.The first objective of this work concerns the development of a new thermomechanical model of the oblique cutting with vibration. In this analytical cutting model, the vibratory system is assimilated to a system with a single degree of freedom in the tool feed direction. We take into account the coupling between tool oscillations, the thermomechanical process of chip formation as well as the regenerative effect. The latter results from the variation in the material quantity to be machined between two successive passes. The coupling between all of these mechanisms makes the problem to be solved strongly nonlinear. A resolution algorithm making it possible to reduce the computation time has been implemented.The second objective of the thesis is achieved through the development of an analytical model where the optimization consists in maximizing a profit integrating selling price of finished product, production and maintenance costs. We note the originality of this part consists in considering the impact of the machining conditions, especially the cutting speed, on the production durations and costs, the quality of the machined parts as well as the degradation of the production system. The impact of machining conditions on three fundamental aspects is therefore considered simultaneously for the "simultaneous optimization of production and maintenance costs" part. The first concerns the impact of machining conditions on production time and costs. The second concerns the impact on the degradation of the machining system and therefore on the optimal maintenance plan to be adopted. The third concerns the impact on the quality of the output product which directly affects the selling costs and more specifically the total profit. These interactions are taken into account through the development of an analytical model to establish an optimal integrated production maintenance plan for the machining system, illustrated by the optimal switching date for changing cutting speed and the optimal numbers of batches to produce before every preventive maintenance action for every production phase. Every production phase is characterized by a cutting speed

In this thesis, the COMAC ARJ21 fuselage’s final assembly process is used as a case study. High production rate (i.e. number of aircraft assembled per year) with reasonable cost is the overall aim in this example. The output of final assembly will essentially affect the prior and subsequent processes of the overall ARJ21 production. From the collected field data, it was identified that a number of disruptions (or bottlenecks) in the assembly sequence were caused by breakdowns and maintenance of the (semi-)automatic assembly machines like portable computer numerical control (CNC) drilling machine, rivet gun and overhead crane. The focus of this thesis is therefore on the maintenance strategies (i.e. Condition-Based Maintenance (CBM)) for these equipment and how they impact the throughput of the fuselage assembly process. The fuselage assembly process is modelled and analysed by using agent-based simulation in this thesis. The agent approach allows complex process interactions of assembly, equipment and maintenance to be captured and empirically studied. In this thesis, the built network is modelled as the sequence of activities in each stage. Each stage is broken down into critical activities which are parameterized by activity lead-time and equipment used. CBM based models of uncertain degradation and imperfect maintenance are used in the simulation study. A scatter search is used to find multi-objective optimal solutions for the CBM regime, where the maintenance-related cost and production rate are the optimization objectives. In this thesis, in order to ease computation intensity caused by running multiple simulations during the optimization and to simplify a multi-objective formulation, multiple Min-Max weightings are applied to trace Pareto front. The empirical analysis reviews the trade-offs between the production rate and maintenance cost and how these objectives are influenced by the design parameters.

The work presented here concerns a Practical Maintenance Framework (PMF) for Small and Medium size Enterprises (SME's) aimed, ultimately, at implementing Total Productive Maintenance (TPM). Typically, the successful implementation of TPM requires large financial and human resource commitments, which are usually unrealistic in SME's. So it is usually the larger companies that are more willing and able to dedicate resources for TPM development. The PMF introduced in this work support SME's in four ways; the Model is simple and flexible for companies to implement, and typically it does not require a significant financial commitment during its implementation. Further improvements can be achieved shortly after implementation. Finally, the Model does not involve specialist TPM teams or committees; instead there is a single team to which every person in the company will be attached to. PMF is a framework that operates in an iterative and interactive process of improvement, review and analysis. The PMF is mainly built on a quantitative measure of performance basedo n data collection and subsequenta nalysiso f Overall Equipment Efficiency (OEE) originally introduced by Nakajima (1988). In addition, in this research, we show how a simplified version of this OEE measure can be usefully adopted in certain circumstances to calculate the efficiency of a production line. To illustrate some of our work we present and discuss results from one of many case studies, which demonstrate the value of maintenance strategies such as PMF. Both PMF and the OEE measure are shown to be effective when used to improve equipment efficiency. Finally, the research suggests a way that can help both equipment manufactures and equipment users to cooperate with an aim to produce more efficient equipment and products.

Production Line Systems (PLS) are ubiquitous in today’s manufacturing industry. The need for enhanced efficiencies and higher throughput in such systems has increased their complexity and size that has made performance analysis challenging for practitioners. This thesis introduces a novel approach based on Product Service System (PSS) design and analysis which simplifies Production Line System study and identifies opportunities for performance improvement that can be quantified based on the hardware and maintenance system performance. The approach involves modelling and simulation techniques based on reliability engineering principles and systems thinking. In order to apply the principles of PSS approach to PLS, it is essential to draw a comparison between PLS and PSS, so as to take account of the differences while applying the new approach; a literature review has been carried out on PSS Design and Analysis, that identified the state of the art modelling and simulation techniques in PSS. Additionally, a separate literature review on maintenance system and production line was carried out. This enabled the PSS methodology to be applied to PLS by incorporating the differences. A systems thinking approach has been employed to create the static simulation model of the integrated production line system by means of schematic representations. Key improvement areas, identified from the static simulation model have been modelled dynamically to incorporate the stochastic behaviour of the system. All the dynamic models are developed using a Discrete Event Simulation platform. These models were supported by Monte Carlo Simulation, queuing principles, probabilistical and statistical methods pertinent to reliability engineering. The novel integrated simulation model consists of a production line model and a maintenance system model. The production line model simulates two types of failures in addition to the outages in the system: breakdowns and short stops. The maintenance system model simulates the maintenance actions in the production line by considering the resources availability, repair time, and resources travelling time amongst others. In addition, the maintenance model is capable of optimizing the preventive maintenance interval for maintainable failures for cost, availability and criticality while taking into account the maintenance effectiveness value from the failure data. The simulation model is validated using an industrial case study which consists of a large production line for beer. Sensitivity studies on the simulation model enabled the case study company to focus on strategies for throughput improvement by improving the reliability and maintainability, optimal resources allocation and maintenance interval optimization in targeted areas in the large and complex system. The model developed is generic and can easily be applied to analyse other industrial production line systems. It can also be used as a design tool for new production lines.

Purple threeawn (Aristida purpurea Nutt.) is a native bunch grass that is avoided by grazers. It is capable of dominating old cropland and overgrazed pastures, limiting livestock carrying capacity, and degrading wildlife habitat. Traditional management tools have had little impact on threeawn dominance in semiarid regions of the west. Our objectives were to: 1) assess fire and nitrogen treatment effects on threeawn forage quality at various phenological stages to test their potential as pretreatments in a grazing strategy and 2) examine a threeawn-dominated plant community?s response to prescribed fire, nitrogen addition, and clipping. Fire improved threeawn forage quality with greater improvements in early phenological stages. Nitrogen had little effect on forage quality. Fire and nitrogen reduced threeawn while increasing cool season grasses. Light and moderate clipping following fire did not improve the efficacy of fire. Fire appears to an effective preliminary treatment to improve the chance of herbivory.

Master of Science
Department of Entomology
Brian P. McCornack
Robert J. Whitworth
No-till management of soybean benefits producers by lowering input costs and retaining soil moisture, but may also provide optimal conditions for increasing populations of soil-inhabiting pests. For Kansas soybean, damaging populations of soil-inhabiting isopods (Malacostraca: Isopoda) have been observed in fields under no-tillage management. To control damage to soybean stands from feeding isopods, current management strategies need to be evaluated. The objectives of my research were to evaluate the effects of chemical and cultural control combinations (seed treatment and planting date, planting date and seed size, seed treatment and natural crop residue removal, and seeding rate and seed treatment) on soybean stand densities exposed to natural isopod populations, and to evaluate the effects of burning crop residue on isopod populations and emergence rates in soybean under no-tillage management. Field studies were conducted in consecutive years (2009 and 2010) in two separate soybean fields within each year. All fields were under no-till management and had a history of damaging isopod populations. In the second chapter, we demonstrated that seed treatment with an insecticide is not a reliable strategy. Doubling normal seeding rates can potentially reduce the number of trips a grower makes across a field (single, high-density versus multiple, low-density plantings). In doing so, growers may save time and money (e.g., fuel). A high seeding rate (563,380/ha), along with a low rate (50 g a.i. / 100 kg seed) of neonicotinoid seed treatment, appears to improve soybean stands (P < 0.05). No other combinations of control methods appeared to affect stand density. In the third chapter, we show burning to be an effective strategy to directly influence isopod populations but its overall effect on soybean stands needs further investigation.

À l’échelle mondiale, le développement de parcs éoliens connait une croissance inédite, visible à travers l’augmentation de la puissance éolienne installée annuellement et de la production éolienne mondiale. 2020 a été la meilleure année de l'histoire de l'industrie éolienne mondiale et on estime que l’installation des éoliennes devrait être trois fois plus rapide au cours de la prochaine décennie. Tout système de production d’énergie est sujet à des pannes aléatoires perturbant les plans de production. Le vieillissement, les pannes ainsi que les durées de maintenance sont des exemples de phénomènes aléatoires souvent observés dans ces systèmes. Dans le cas particulier des éoliennes, la nature hautement volatile et incertaine du vent implique que la durée des actions de maintenance doit être minimisée afin de maximiser la disponibilité de l’éolienne et donc sa production énergétique. D’autant plus que les risques liés à la maintenance font de ce celle-ci la cause majeure des accidents survenant dans le secteur éolien. A ceci, s’ajoutent le manque de formation des techniciens de maintenance et l’absence de plan de prévention. Ainsi l’élaboration d’un plan de maintenance est nécessaire, pour optimiser le nombre d’interventions et leur durée et réduire considérablement les conséquences techniques, économiques et humaines liées à ces opérations. La maintenance et la production représentent deux fonctions principales pour tout type de production. Dans la pratique, ces deux fonctions sont souvent gérées séparément malgré qu’elles soient en réalité étroitement liées. En effet, les politiques d’intégration permettent d’améliorer la productivité et de diminuer considérablement les coûts. Dans ce cadre, le travail de recherche proposé dans cette thèse consiste à déterminer de nouvelles politiques de maintenance intégrées à la production d’énergie pour un parc éolien. Deux stratégies de maintenance intégrée ont été testées : parfaite puis combinée imparfaite/sélective avec couplage à la production d’énergie satisfaisant un taux de service tout en tenant compte des contraintes environnementales et opérationnelles et. En effet, pour chaque stratégie développée, le but est de déterminer simultanément un plan de production d’énergie économique et un plan de maintenance optimal minimisant un coût total de production d’énergie et de maintenance. La particularité de cette étude est de considérer l’impact de la variation de production d’énergie sur la dégradation de l’éolienne. Le problème a été modélisé par le développement et l’optimisation de modèles analytiques, puis validé par des exemples numériques et des études de sensibilité prouvant la robustesse des modèles analytiques développés
Globally, the development of wind farms is experiencing exceptional growth, visible through the increase of wind power installed annually and global wind power production. 2020 was the best year in the history of the global wind industry and it is estimated that wind turbine installation should grow three times faster over the next decade. Any energy production system is subject to random breakdowns which trouble production plans. Aging, breakdowns and maintenance times are examples of random phenomena often observed in those systems. In the particular case of wind turbines, the highly volatile and uncertain nature of the wind means that the duration of maintenance actions must be minimized in order to maximize the availability of the wind turbine and therefore its energy production. In addition to this, the risks associated with maintenance make it the major cause of accidents in the wind energy sector. Considering the lack of training for maintenance technicians and the absence of a prevention plan, a maintenance plan optimizing the number of interventions and their duration and considerably reducing the technical, economic and human consequences linked to these operations is essential. Maintenance and production are two main functions for any type of production. In practice, these two functions are often managed separately despite being in reality so close. Indeed, integration policies can improve productivity and reduce costs considerably. In this context, the research work proposed in this thesis consists in determining new maintenance policies integrated into energy production for a wind farm. Two integrated maintenance strategies were tested: perfect then combined imperfect / selective coupled to energy production, satisfying a service rate while taking into account environmental and operational constraints and. Indeed, for each strategy developed, the goal is to simultaneously determine an economical energy production plan and an optimal maintenance plan minimizing a total cost of energy production and maintenance. The particularity of this study is to consider the impact of the variation in energy production on the degradation of the wind turbine. The problem was modeled by the development and optimization of analytical models, then validated by numerical examples and sensitivity studies proving the robustness of the analytical models developed

Inventory management is a complex system which involves different stakeholders from multiple areas in a company which creates a limitation when seeking information between involved staff. Having the right procedure of tracking regular and critical spare parts will give a better control and efficiency in the production process. It is important to have the right classification method to facilitate critical spare parts. The incorrect criteria classification can be achieved in case inventory management have the wrong systematic procedure. Classification methods have different purposes and achieve the highest utilization by combining a variety of methods. By integrating classification methods, set limits and combination of multiple criteria decision analysis can be performed. The study has conducted a case study to compare and evaluate the performance of inventory management in a trustworthy and efficient way. A theoretical framework is constructed with the intention on identify which classification methods can be combined and applied to a production factors criterion. Based on interviews with stakeholders from maintenance, warehouse, and production area related to spare parts and the company’s software system. Two perspectives were used to map the qualitative and quantitative measures. The results show 14 criteria were defined as parameters that measure the performance of criticality in spare parts. The conclusion of both perspectives suggests combining and implement an integration of AHP and ABC classification methods. A proof of concept is demonstrated on AHP analysis and ABC analysis to identify the critical spare parts and the criteria.

Thesis (MScEng)--Stellenbosch University, 2013.
ENGLISH ABSTRACT: The thesis evaluates control strategies for reconfigurable manufacturing systems by using a welding assembly cell as a case study. The cell consists of a pallet magazine, conveyor, feeder subsystem (comprising an articulated robot and singulation unit), welder subsystem (which uses a modular Cartesian robot), and inspection and removal subsystems. The research focuses on control strategies that enhance reconfigurability in terms of structure, hardware and software using agent-based control and the IEC 61499 standard, based on PC control. Reconfiguration may occur when a new product is introduced, as well as when a new subsystem is introduced or removed from the production cell. The overall control architecture is that the subsystems retain no knowledge of the product, but product information resides in the cell controller, while services offered by the subsystems are registered with the directory facilitator of the Java agent platform. The control strategies are implemented on the modular Cartesian weld robot and the cell controller for assembly cell. A layered architecture with low-level control and high-level control is used to allow separation of concerns and rapid changes in both hardware and software components. The low-level control responds in hard real-time to internal and external events, while the high-level control handles soft real-time actions involving coordination of control related issues. The results showed IEC 61499 function blocks to be better suited to low-level control application in distributed systems, while agents are more suited for high-level control. Modularity in software components enhances hardware and software scalability. Additionally, agents can support online reconfiguration of reconfigurable machines.
AFRIKAANSE OPSOMMING: Die tesis evalueer beheerstrategieë vir herkonfigureerbare vervaardigingstelsels deur gebruik te maak van ’n sweismonteersel as ’n gevallestudie. Die sel bestaan uit ’n palletmagasyn, vervoerbande, voersubstelsel (bestaande uit ’n geartikuleerde robot en singulasie-eenheid), sweissubstelsel (wat gebruik maak van ’n modulêre Cartesiese robot), en inspeksie- en verwyderingsubstelsels. Die navorsing fokus op beheerstrategieë wat herkonfigureerbaarheid verhoog in terme van struktuur, hardeware en sagteware met behulp van agent-gebaseerde beheer en die IEC 61499 standaard, wat gebaseer is op PC-beheer. Herkonfigurasie mag voorkom wanneer ’n nuwe produk in-gestel word, sowel as wanneeer ’n nuwe substelsel bygevoeg of verwyder word van die produksiesel. Die oorhoofse beheerargitektuur is dat die substelsels geen kennis van die produk hou nie, maar die produkinligting in die selbeheerder geberg, terwyl dienste wat aangebied word deur die substelsels wat geregistreer is by die gidsfasiliteerder van die Java agent platform. Die beheerstrategië is geïmplementeer op die modulere Cartesiese sweisrobot en die selbeheerder vir die monteersel. ’n Gelaagde argitektuur met ’n lae-vlak beheer en hoë-vlak beheer word gebruik om skeiding van oorwegings en vinnige veranderinge in beide hardeware en sagteware komponente toe te laat. Die lae-vlak beheer reageer hard intyds op interne en eksterne gebeure, terwyl die hoë-vlak beheer sag intyds die koördinering van beheerverwante kwessies hanteer. Die resultate het getoon dat IEC 61499 funksie-blokke beter geskik is vir lae-vlak beheer toepassing in verspreide stelsels, terwyl agente meer geskik is vir hoë-vlak beheer. Modulariteit in sagteware komponente verhoog hardeware en sagteware skaleerbaarheid. Boonop kan agente ook aanlyn herkonfigurasie van herkonfigureerbare masjiene ondersteun.

Actuellement, la compétition entre les entreprises se traduit par la révision des stratégies industrielles courantes dans le but d’améliorer simultanément les plans de production et de maintenance. En réalité, la non-satisfaction du client dans les délais est due souvent à des critères aléatoires liés essentiellement à la demande et aux défaillances soudaines des systèmes de production. Par conséquent, il est nécessaire de développer des politiques de maintenance intégrées à la production en tenant compte des contraintes liées au stockage, à la demande et au taux de défaillance. Dans ce travail, nous nous intéressons à une problématique industrielle qui s’articule autour du développement de différentes politiques de maintenance intégrées à la production. Le système considéré consiste en une machine fabriquant plusieurs types de produits, dans l’optique de satisfaire des demandes aléatoire avec des niveaux de service donnés. On note que l’originalité de notre étude, par rapport à l’existant en littérature dans le domaine de la maintenance intégrée à la production, consiste à considérer un système à multi-produits. Dans cette étude nous avons développé et optimisé analytiquement des politiques de production pour un système à multi-produits devant satisfaire plusieurs demandes aléatoires caractérisant respectivement différentes clients. Ces politiques consistent à établir des plans périodiques de production pour chaque produit, minimisant les coûts liés à la production et le stockage tout en satisfaisant un taux de service prédéfini pour chaque produit. Par la suite, en tenant compte de l’influence des plans économiques de production obtenus sur l’évolution de la dégradation du système de production, nous avons développé des stratégies optimales de maintenance. Plusieurs scénarios ont été étudiés selon les durées des sous-périodes de production et le coût de setup de chaque produit. En fin, des études de cas ont été traitées afin de confronter les résultats analytiques établis
Currently, the competition between companies is reflected in the revision of the current industry strategies to improve the planning of production and maintenance. In fact, the non- satisfaction of the customer on time is often due to a random demand or a sudden failure of production system. Therefore, it is necessary to develop new maintenance and production strategies. In this memory, we treat some maintenance policies integrated with production for a manufacturing system. This paper deals with the problem of maintenance strategy and production planning for a multiple-product manufacturing system. The manufacturing system under consideration consists of one machine which produces several products in order to satisfy random demands corresponding to every product. The significance of the present study is that the study deals with the case of a system which produces several products. In this study we have developed and optimized analytically production policies for a multiple-product manufacturing system, in order to meet several random requests characterizing respectively different customers. These policies consist of establishing periodic production plans for each product, minimizing the costs of production and storage while meeting predefined service level for each product. Subsequently, we have developed optimal strategies of maintenance, taking into account the influence of economic production plans obtained, on the evolution of the degradation of the production system. Several scenarios have been studied according to the durations of the sub-periods of production and the cost of set-up of each product. In the end, case studies were treated in order to compare the developed analytical results

Actuellement, la compétition entre les entreprises se traduit par la révision des stratégies industrielles courantes dans le but d’améliorer simultanément les plans de production et de maintenance. En réalité, la non-satisfaction du client dans les délais est due souvent à des critères aléatoires liés essentiellement à la demande et aux défaillances soudaines des systèmes de production. Par conséquent, il est nécessaire de développer des politiques de maintenance intégrées à la production en tenant compte des contraintes liées au stockage, à la demande et au taux de défaillance. Dans ce travail, nous nous intéressons à une problématique industrielle qui s’articule autour du développement de différentes politiques de maintenance intégrées à la production. Le système considéré consiste en une machine fabriquant plusieurs types de produits, dans l’optique de satisfaire des demandes aléatoire avec des niveaux de service donnés. On note que l’originalité de notre étude, par rapport à l’existant en littérature dans le domaine de la maintenance intégrée à la production, consiste à considérer un système à multi-produits. Dans cette étude nous avons développé et optimisé analytiquement des politiques de production pour un système à multi-produits devant satisfaire plusieurs demandes aléatoires caractérisant respectivement différentes clients. Ces politiques consistent à établir des plans périodiques de production pour chaque produit, minimisant les coûts liés à la production et le stockage tout en satisfaisant un taux de service prédéfini pour chaque produit. Par la suite, en tenant compte de l’influence des plans économiques de production obtenus sur l’évolution de la dégradation du système de production, nous avons développé des stratégies optimales de maintenance. Plusieurs scénarios ont été étudiés selon les durées des sous-périodes de production et le coût de setup de chaque produit. En fin, des études de cas ont été traitées afin de confronter les résultats analytiques établis
Currently, the competition between companies is reflected in the revision of the current industry strategies to improve the planning of production and maintenance. In fact, the non- satisfaction of the customer on time is often due to a random demand or a sudden failure of production system. Therefore, it is necessary to develop new maintenance and production strategies. In this memory, we treat some maintenance policies integrated with production for a manufacturing system. This paper deals with the problem of maintenance strategy and production planning for a multiple-product manufacturing system. The manufacturing system under consideration consists of one machine which produces several products in order to satisfy random demands corresponding to every product. The significance of the present study is that the study deals with the case of a system which produces several products. In this study we have developed and optimized analytically production policies for a multiple-product manufacturing system, in order to meet several random requests characterizing respectively different customers. These policies consist of establishing periodic production plans for each product, minimizing the costs of production and storage while meeting predefined service level for each product. Subsequently, we have developed optimal strategies of maintenance, taking into account the influence of economic production plans obtained, on the evolution of the degradation of the production system. Several scenarios have been studied according to the durations of the sub-periods of production and the cost of set-up of each product. In the end, case studies were treated in order to compare the developed analytical results

The aim of this PhD research was to describe an assessment of the potential impacts of climate change as well as climate variability on rice production. It also discusses selected adaptation options within the context of the Malian agriculture. The research centers on an integrated modelling approach (BioMA) to compute current and future (2020, 2050) crop yields in the agricultural region of the Office du Niger (Mali). BioMA – Biophysical Models Application – is a platform for running biophysical models on generic spatial units. The application is based on independent components which allow implementing modelling solutions targeted to specific modelling goals. The collected data were used to (i) develop new modules (a model for simulating the height of the plant) (ii) implement the existing ones according to the peculiarities of the sub-Saharan environment (i.e. the Agromanagement module was extended in order to take into account the beginning of the rainy season) and to (iii) calibrate and validate the modelling solution defined for the purpose. Although parameterization procedures were performed in critical conditions – being reference data from the area a limiting factor – a preliminary calibration of WARM, for tropical and subtropical conditions, could be performed aromatically on Chinese datasets. Indeed these results achieved from these modelling exercises showed that the model is robust and able to reproduce yield variability within years and locations which made it suitable for the impact assessment study in Mali. The impact assessment on cropping systems was evaluated via a difference analysis with respect to the current conditions, focusing on changes in total biomass, final yield and transpiration demand. An overall reduction can be expected in 2050 (up to complete failure of the crop) whereas different results were obtained for 2020. The main season seem to be little affected by the increase of temperatures whereas the first cycle, which takes already place under extremely high temperatures, will face reductions up to 25%. Based on the results obtained in the impact assessment changes in sowing dates were tested in order to detect the most suitable management techniques which allow alleviating the negative effect of climate changes. The results suggested that changes in the sowing may be very effective in mitigating the adverse effect of climate change as well as the use of new crop cultivars with longer vegetative cycles. In fact in both systems an increase of production can be expected at short-term whereas at medium-term the losses can be significantly reduced.

La planification de l'inspection de la qualité des pièces (PQIP) est un problème important dans les systèmes de production. En raison du fort impact des activités de maintenance préventive (PM) sur le taux de non-conformité des produits (un des principaux paramètres du problème PQIP), il est nécessaire de développer une planification intégrée des activités l'inspection et les activités de maintenance afin d’obtenir une optimisation globale du système. Cette thèse présente des modèles mathématiques de programmation linéaire à nombres entiers mixtes pour le problème de planification intégrée du contrôle de la qualité et des activités de gestion de maintenance dans un système de production en série à plusieurs étapes. Les modèles déterminent simultanément le moment et l’endroit optimals pour effectuer les activités susmentionnées en prenant en compte la détérioration des étapes de production. Ces deux décisions sont effectuées via la minimisation du coût total (y compris la production, la maintenance, l'inspection, la mise au rebut, la réparation et la pénalité des articles défectueux expédiés au client) et ainsi elles optimisent la productivité du système. Dans ce cas, la productivité du système est formulée comme une mesure non linéaire, puis linéarisée par la technique d'approximation linéaire par morceaux. En plus, l’incertitude relative à l’estimation des composantes de coût et de la quantité demandée est gérée par une approche possibiliste robuste. Un exemple numérique et une étude de cas réelle sont étudiés pour valider et vérifier les modèles proposés. Le résultat le plus important de cette recherche est que la détermination des lieux d’inspection le long d’un processus de fabrication à différentes périodes avec la prise en compte d’impact des activités de maintenance préventive sur le taux de production défectueuses se traduit par une amélioration significative de la performance du système de production
Part Quality Inspection Planning (PQIP) is a significant problem in multi-stage manufacturing systems. Because of an existing strong impact of Preventive Maintenance (PM) activities on the defective production rate (which is the main input of the PQIP), developing an integrated planning for the part quality inspection and PM protects system from a local optimum. This thesis presents mixed-integer linear programming models for the integrated planning problem of the part quality inspection and PM activities in a serial multi-stage manufacturing system. The models concurrently determine the right time and place for performing the above-mentioned activities while the stages are deteriorating. These two decisions are made while the models are to minimize the total cost (including the production, PM, inspection, scrap, repair, and the penalty of shipped defective items) and maximize system productivity. Notably, the system productivity is formulized as a non-linear measure, and then it is linearized by the piecewise linear approximation technique. In addition, the uncertainty about the estimation of cost components and demand is handled by a robust possibilistic approach. A numerical example and a real case study are investigated to validate and verify the proposed models. The most important result of this research is that the determination of inspection locations along a manufacturing line in different periods of time regarding the impact of preventive maintenance activities on defective production probability results in a more efficient system

Background: Generally, operation management includes a set of complicated systems interfacing each other. Most important systems which impact and impacted by the operations management system are production management system and maintenance management system. But to treat the interfacing losses has been difficult as interact and partially overlap each other. In this study, case-operational system was treated with developed model that analysis and design integrated operational system in order to make it easier and cost effective to manage.

Methods: A model was developed based on latest literature survey work using systems paradigm methodology and systems engineering approach.

Results: Among five analysis techniques, four types of interfacing losses were identified, seven requirements were extracted, nine conceptual solutions were generated, one of them was selected and based on it the integrated operational management system were designed.

Conclusions: The results suggest that the operational system in case-company shall be integrated by organization management, process management, and control management, in addition to data management.

Bakgrund: I allmänhet har operations verksamhet en del komplicerade system där friktion kan förekomma. De viktigaste systemen som har påverkan på operations verksamhet är produktion och underhålls system. Att behandla friktions förluster har varit svårt eftersom de både samverkar och delvis överlappar varandra. I dem här studien har olika fall av operationssystem behandlats med att först utveckla en modell, analysera och designa den integrerade operationssystemet för att få den billigaste och dem mest kostnads effektiva sätt att klara av.

Metod: En modell har utvecklats baserat på de senaste metoderna genom att använda system paradigm metoder och systemtekniska angreppssätt.

Resultat: Genom att använda fem sätt att analysera, sju bestämmelser extraherade, nio lösningar generade, valdes en av lösningarna och med lösningen som grund designades operations verksamhet.

Slutsats: Resultatet förslog att operations verksamhet skall integrera organisation, process och kontroll ledningar och inte bara data ledningen.

Abstract

The aim of this thesis is to show the company the importance and the necessity of the maintenance, trough highlighting its role and impact on company’s profitability and competitiveness, and that’s happened within the analysing of the plant to figure out the failures and short stoppages, find out the causes behind them, convert them into money and the last step is to find out the most suitable and cost effective maintenance strategy based on some important factors such as economy, and quality to probably eliminate or reduce the number of failures and short stoppages. According to the analysis, capacity verifying data collection which the company has done during a random working daily shift and a technical faults list about the possibly failures and short stoppages which occur during the operation, it shows that there are some downtime due to management, operation and logistic, but the main focus was on the technical faults which has correlation with maintenance. In the result it shows which technical and mechanical problems the machines usually faces, the causes behind them, how much it cost the company when they breaks down and finally some suggestions and recommendations about how these problems can probably be solved based on economy and quality.

Sammanfattning

Syftet med denna rapport är att visa hur viktigt och nödvändigt det är med att underhålla företagens maskiner och utrustningar, därför att det har stor påverkan på företagens lönsamhet och konkurrens och det skedde genom att analysera företagens produktions process, lista ut haverier och avbrott, hitta orsakerna som ligger bakom det, konvertera det till pengar och försöka lösa problemen genom att hitta den mesta lämpligaste underhåll strategi baserande på ekonomi och kvalitet. Enligt analysen som utfördes genom studiet, kapacitet verifiering data insamlingen som företaget gjorde under en slumpmässig arbetsdag skift och ett tekniskt fel lisat på eventuella avbrott och haverier. Det visade sig att det finns vissa stopp tider som har samband med management, operation, och logistik, men uppgiften är mer fokuserad på de tekniska problemen som har samband med underhåll. I resultatet ser man vilka tekniska och mekaniska problem som brukar angripa maskinerna, orsakerna som ligger bakom de, hur mycket det kostar företaget för varje maskin när den är ur funktionen, samt några förslag på eventuella lösningar och rekommendationer baserande på ekonomi och kvalitet.

博士
國立臺灣科技大學
工業管理系
92
In this paper, we develop an integrated model for the joint determination of both economic production quantity (EPQ) and level of preventive maintenance (PM) for an imperfect production process. This process has a general deterioration distribution with increasing hazard rate. The effect of PM activities on the deterioration pattern of the process is modeled using the imperfect maintenance concept. In this concept, it is assumed that after performing PM, the aging of the production system is reduced proportional to the PM level. After a period of time in production, the process may shift to out-of-control states, either type I or type II. A minimal repair will remove type I out-of-control state. If type II out-of-control state occurs, the production process has to stop followed by the restoration work. Examples of Weibull shock models are given to illustrate that performing PM results in a lower cost than no PM action.

Thesis (M.A. Agricultural Management (Plant Production)) -- University of Limpopo, 2015
Tomato (Solanum lycopersicum L.) production had been ranked as the most important commodity in terms of job and wealth creation within the auspices of the National Development Plan (NDP) framework in Limpopo Province. However, soil-borne diseases including plant-parasitic nematodes preclude the successful monoculturing of this commodity and therefore inducing instability in job creation. Generally, after growing a tomato crop for one season in commercial tomato-production systems, the land is being fallowed for 3-5 years under natural grasses. Attempts are being initiated to ensure that during the 3-5 years the land be occupied by an economic alternative crop in order to level off job instability as broadly articulated in the NDP framework. The production of sweet stem sorghum (Sorghum bicolor L.) for ethanol production during the 3-5 years fallowing period could potentially be attractive to commercial tomato-producing famers. Preliminary agronomic evaluations demonstrated that sweet stem sorghum var. ndendane-X1 had attributes to fulfil the identified need. However, the degree of nematode resistance of the variety to Meloidogyne incognita race 2 and M. javanica, which are dominant in Limpopo Province, along with the compatibility of var. ndendane-X1 to phytonematicides used in tomato production had not been documented. The objectives of the study were, therefore, to determine whether sweet stem sorghum var. ndendane-X1: (1) had any degree of nematode resistance to M. incognita race 2 under both greenhouse and microplot conditions, (2) had any degree of nematode resistance to M. javanica under greenhouse conditions, and (3) would be compatible with phytonematicides used in suppression of population densities of xiv Meloidogyne species in tomato production under field conditions. In the greenhouse trials, seeds were sown in 20-cm-diameter plastic pots and each seedling inoculated with 0, 600, 1 000, 1 400, 1 800 and 2 200 eggs and second-stage juveniles (J2s) of M. incognita race 2 or M. javanica. Treatments were arranged in a randomised complete block design (RCBD), with 10 replicates (n = 60). In the microplot trial, seeds were sown in 30-cm-diameter plastic pots and buried 75% deep in a 0.30-m intra-row and 0.25-m inter-row spacing. Treatments, namely, 0, 200, 600, 1 000, 1 400, 1 800 and 2 200 J2s of M. incognita race 2 were arranged in RCBD, with 14 replications (n = 98). In a Meloidogyne-infested field trial, seeds were sown at 0.2-m inter-row and 0.3-m intra-row spacing, with treatments 0, 2, 4, 6, 8 and 10 g nemafric-BG phytonematicide/plant, arranged in RCBD, with 13 replications (n = 78). The degree of nematode resistance was measured using host-status and host-sensitivity, which provide information on reproduction of the target nematode and plant damage due to nematode infection, respectively. Nematode reproduction was measured through the reproductive factor (RF), which is a proportion of final nematode population density (Pf) to initial nematode population density (Pi), summarised as RF = Pf/Pi. In all nematode resistance trials, RF was equivalent to zero, which implied that var. ndendane-X1 was a non-host to both M. incognita race 2 and M. javanica. Additionally, in both greenhouse and microplot trials, sweet stem sorghum var. ndendane-X1 did not suffer any significant damage due to infection by Meloidogyne species. Using nematode-plant relation concepts, sweet stem sorghum var. ndendane-X1 was resistant to M. incognita race 2 and M. javanica under greenhouse and microplot conditions. Under field conditions, nemafric-BG phytonematicide reduced eggs and J2s of Meloidogyne species in root and soil samples xv by 76-85% and 24-65%, respectively, without nematode effect on plant growth, suggesting that nemafric-BG could be integrated with nematode resistance in var. ndendane-X1 to manage nematode population densities. In conclusion, pilot projects where sweet stem sorghum var. ndendane-X1 could be used during the 3-5 years fallowing period in a tomato-sweet stem sorghum crop rotation system should be established to assess: (i) the economics of the proposed cropping system, (ii) the effect of the cropping system on soil-borne diseases, including plant-parasitic nematodes, and (iii) the effect of the cropping system on soil health.

This dissertation is composed of three major parts, each studying a problem related to semiconductor manufacturing. The first part of the dissertation proposes a high-level scheduling model that serves as an intermediate stage between planning and detailed scheduling in the usual planning hierarchy. The high-level scheduling model explicitly controls the WIP over time in the system and provides a more specific guide to detailed scheduling. WIP control is used to balance the WIP (Work In Process) level and to keep the bottleneck station busy to maintain a high throughput rate. A mini-fab simulation model is used to evaluate the benefits of different approaches to implementing such a high-level scheduling model, and to compare different WIP control policies. Extensive numerical studies show that the proposed approaches can achieve much shorter cycle times than the traditional planning-scheduling approach, with only a small increase in inventory and backorder costs. With increasing worldwide competition, high technology product manufacturing companies have to pay great attention to lower their production costs and guarantee high quality at the same time. Advanced process control (APC) is widely used in semiconductor manufacturing to adjust machine parameters so as to achieve satisfactory product quality. The interaction between scheduling and APC motivates the second part of this dissertation. First, a single-machine makespan problem with APC constraints is proved to be NPcomplete. For some special cases, an optimal solution is obtained analytically. In more general cases, the structure of optimal solutions is explored. An efficient heuristic algorithm based on these structural results is proposed and compared to an integer programming approach. Another important issue in manufacturing system is maintenance, which affects cycle time and yield management. Although there is extensive literature regarding maintenance policies, the analysis in most papers is restricted to conventional preventive maintenance (PM) policies, i.e., calendar-based or jobbased PM policies. With the rapid development of new technology, predictive maintenance has become more feasible, and has attracted more and more attention from semiconductor manufacturing companies in recent years. Thus, the third problem considered in this dissertation is predictive maintenance in an M/G/1 queueing environment. One-recipe and two-recipe problems are studied through semi-Markov decision processes (SMDP), and structural properties are obtained. Discounted SMDP problems are solved by linear programming and expected machine availabilities are calculated to evaluate different PM policies. The optimal policy can maintain a high machine availability with low long-run cost. The structures of the optimal PM policies show that it is necessary to consider multiple recipes explicitly in predictive maintenance models.
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In today's competitive environment, the importance of continuous production, quality improvement, and fast delivery has forced production and delivery processes to become highly reliable. Keeping equipment in good condition through maintenance activities can ensure a more reliable system. However, maintenance leads to temporary reduction in capacity that could otherwise be utilized for production. Therefore, the coordination of maintenance and production is important to guarantee good system performance. The central thesis of this dissertation is that integrating maintenance and production decisions increases efficiency by ensuring high quality production, effective resource utilization, and on-time deliveries. Firstly, we study the problem of integrated maintenance and production planning where machines are preventively maintained in the context of a periodic review production system with uncertain yield. Our goal is to provide insight into the optimal maintenance policy, increasing the number of finished products. Specifically, we prove the conditions that guarantee the optimal maintenance policy has a threshold type. Secondly, we address the problem of integrated maintenance planning and production scheduling where machines are correctively maintained in the context of a dynamic aircraft repair shop. To solve the problem, we view the dynamic repair shop as successive static repair scheduling sub-problems over shorter periods. Our results show that the approach that uses logic-based Benders decomposition to solve the static sub-problems, schedules over longer horizon, and quickly adjusts the schedule increases the utilization of aircraft in the long term. Finally, we tackle the problem of integrated maintenance planning and production scheduling where machines are preventively maintained in the context of a multi-machine production system. Depending on the deterioration process of machines, we design decomposed techniques that deal with the stochastic and combinatorial challenges in different, coupled stages. Our results demonstrate that the integrated approaches decrease the total maintenance and lost production cost, maximizing the on-time deliveries. We also prove sufficient conditions that guarantee the monotonicity of the optimal maintenance policy in both machine state and the number of customer orders. Within these three contexts, this dissertation demonstrates that the integrated maintenance and production decision-making increases the process efficiency to produce high quality products in a timely manner.

Non-Suicidal Self-Injury (NSSI) is a maladaptive behavior and it is defined as "the deliberate, self-inflicted destruction of body tissue without suicidal intent and for purposes not socially sanctioned". Although under-reported, NSSI is often revealed in community samples, and a recurring comorbidity was found with suicide, which highlights the gravity of NSSI itself, as it may lead to serious injury or even mortality. It may occur in all phases of life, but individuals appear to start such behavior very early in their life, especially in adolescence and young adulthood, with possible incidence rates that considerably vary among studies (i.e., approximately from 5% to 38%). This dissertation aims to thoroughly explore the NSSI topic. Firstly, the behavior was investigated from a psychological and experimental perspective, through observational data. After, two different approaches applying Agent-Based Modeling (ABM) were introduced to study the role of diverse factors affecting NSSI. Two main theoretical models were considered to better understand NSSI behavior, and as a background for the implementation of the numerical model. Particularly, the Experiential Avoidance Model claims NSSI is a negatively reinforced strategy for terminating unwanted emotional arousal. On the other hand, the Integrated Theoretical Model of the Development and Maintenance of Self-Injury focused on the description of the functions of NSSI (i.e., interpersonal and intrapersonal functions), and it introduces how distal factors may increase an intrapersonal and interpersonal vulnerability, and how specific factors may lead to engage in NSSI to cope with stress. Hence, the latter was suitable to thoroughly identify the complexity of factors involved in NSSI. Besides literature has showed the presence of several factors that affects NSSI, previous studies have not investigated the specific role of diverse factors in affecting NSSI. Particularly, several studies were more focused on the individual-related risk factors, omitting to adequately analyze interpersonal factors or other similar psychosocial dimensions, such as adolescent dynamics and risk behaviors in virtual social networks. To fill this gap, a few preliminary studies were conducted: we have analyzed the online social dynamics of adolescents, and the role of interpersonal and family relationships in their life, to detect possible risk factors. For what concerns the numerical modeling, we have focused on the NSSI dynamics in adolescence, through the Agent-Based Modeling (ABM). As a first approach, main NSSI risk factors (i.e., Inner Factor, Outer Factor, Media Factor) were selected from literature, assuming them as increasing the probability of self-injury. Moreover, three network topologies (i.e., Uniform, Gaussian, Exponential) and a probability to experience stressful events were settled as fixed parameters. As a dynamical parameter, the Peer Factor was introduced as the density of self-injurers in the network. The mathematical model was described, and the numerical simulations conducted were introduced, first considering the effect of each risk factor singularly, then contemplating the combined effect of all risk factors. As a second approach, a preliminary validation of the mathematical model was conducted. Risk factors were parametrized through real data collected in three secondary schools, and numerical simulations were started comparing results with those obtained through the survey. Moreover, the network was finally divided in two subclusters presenting a different density of self-injurers. Hence, the propagation of self-injurers from a subcluster to another was analyzed, as well as the number of connections between subclusters increased along numerical simulations. Results revealed a relevant effect of both risk factors and the dynamical parameter Peer Factor on NSSI dynamics, considering both results from the non-parametrized model and results from the parametrized model. On the contrary, topology displayed little or none effect on the probability of self-injury. Moreover, the model appears to adequately reproduce NSSI real trends, obtaining similar results than real data, confirming its good effectiveness in describing NSSI dynamics. Such findings highlighted interesting implications about the complex dynamics of the phenomenon, and might represent a starting point to implement an integrated model reproducing similar maladaptive behaviors (e.g., gamble).

Competitive and high-risk environments require complex high technology systems, which need to be supported and maintained over their respective life cycles. These systems often have a significant consequence of failure, and require complex management systems to achieve their operational objectives. Significant leadership and management challenges exist, not only in South Africa, but also in other developing countries, where systems may be utilised beyond the lifespan they were designed for and are susceptible to obsolescence. This study was conducted by following a structured process; the research consisted of three stages. The first stage dealt with the research problem, including the delimitations of the study. The second stage was further divided into three phases. The first phase deconstructed the appropriate literature, which included the interpretation of numerous definitions of logistics, integrated logistics support, and the integrated logistics support elements. In addition, the research was grounded in the fields of operations management, supply chain management and integrated logistics support. The second phase focused on the deconstruction of six case studies from four different high technology complex systems. From the analysis of the first two phases followed the third phase of research, which focused on the identification of areas requiring further research. Further research was conducted by means of a questionnaire, the results of which were analysed for variable dependency and variable association. The third stage of the research included the collation and analysis of the findings of the first two stages of research. The analysis utilised the principles of Mode 2 research and design science research, whereby an ILS framework and associated grounded technological rules have been recommended. These recommendations are robust in nature, as they can be applied in the most challenging environment and circumstances as identified. Furthermore, by grounding the theory in the disciplines of operations management, supply chain management and integrated logistics support, the reliability, validity, relevance, and applicability of the study could be substantiated. This implied that the generated theoretical knowledge could be transferred to and applied in practice, and as such, an organisation can reap substantial value added benefits, and gain considerable competitive advantage in the market place by applying this developed ILS framework and associated ILS grounded technological rules.
Business Leadership
D. BL.