L'ordonnancement est considéré comme l'une des tâches les plus importantes en industrie, notamment dans les ateliers de production. Son but principal est d'allouer les ressources disponibles aux tâches sur une période donnée, tout en optimisant un ou plusieurs objectifs tels que la minimisation des délais de production et les coûts de stockage. En France, ces industries contribuent de manière significative à l'économie régionale et nationale, faisant de la région Hauts-de-France la quatrième région économique française. Pour rester compétitives, ces sociétés doivent reposer, d'une part, sur un système de production fiable et disponible à tout moment, et d'autre part, sur de puissants outils d'aide à la décision permettant de réagir rapidement à toute situation imprévue telle qu'une panne ou un retard de livraison de matières premières, des annulation de commande, etc. Par ailleurs, la maintenance est un autre aspect étroitement lié à l'ordonnancement de la production. L'une des hypothèses les plus courantes dans la littérature est que les machines ou les ressources sont toujours disponibles à tout moment, or, en pratique, il peut être nécessaire de les arrêter en raison de pannes ou de maintenance préventive. Compte tenu du fait que les machines sont un élément essentiel du processus de production et que les coûts de maintenance représentent un grand pourcentage du budget total des opérations, il est souhaitable de bien coordonner la planification de la maintenance et l'ordonnancement de la production. Cette thèse aborde exactement ce problème, tout en considérant d'autres contraintes comme les temps de préparation dépendant de la séquence. L'objectif principal de ce travail est de concevoir et de développer des méthodes d'optimisation pour l'aide à la décision appliquées aux problèmes d'ordonnancement avec contrainte d'indisponibilité due à la maintenance préventive. Ces outils sont validés à travers des problèmes académiques et industriels simplifiés. Par conséquent, cette thèse a conduit au développement de nouveaux algorithmes et modèles basés sur la programmation linéaire en nombres entiers, des heuristiques et des métaheuristiques pour résoudre des problèmes d'ordonnancement de la production. / Production scheduling is considered as one of the most important tasks carried out in manufacturing systems. It allows available resources to perform a number of tasks, over a given period of time, while optimizing one or more objectives such as reducing production delays or costs associated with storage. In France, these industries contribute significantly to the regional and national economy, making the Hauts-de- France region the fourth French economic region. In order to remain competitive, these companies must be based, on one side, on a reliable production system that is available at any time, and on the other side, on powerful Decision Support Systems to react quickly to any unpredictable situation such as failures, late deliveries of raw material or orders cancellation, etc. Furthermore, maintenance is another aspect closely connected to production scheduling in real manufacturing settings. One of the most common assumptions in the scheduling literature is that the machines or resources are always available but, in practice, they may have to be stopped due to failures or to preventive maintenance. Taking into account that machines are an essential part of the production process and maintenance costs represent a large percentage of the total budget of operations, it is desirable to coordinate efficiently the maintenance planning and production scheduling. This thesis addresses exactly this problem, while considering other constraints such as sequence-dependent setup times between tasks. The main objective of this work is to design and develop optimization methods for decision support systems applied to scheduling problems with unavailability constraints due to preventive maintenance. The proposed models and tools have been validated through academic problems and on the basis of simplified industrial problems. Therefore, the output of the thesis is to develop new algorithms and models based on integer linear programming, heuristics and metaheuristics to solve production scheduling problems.

A teoria de programação da produção preocupa-se em fornecer diretrizes e métodos eficientes para a utilização dos recursos nas atividades produtivas. Este trabalho investiga o problema de programação da produção em ambientes flow shop com máquinas múltiplas e tempos de preparação das máquinas assimétricos e dependentes da seqüência de execução das tarefas. A atividade de programação da produção constitui uma das várias funções executadas pelo planejamento e controle da produção, que tem como objetivo comandar e gerenciar o processo produtivo, e caracteriza uma das atividades mais complexas no gerenciamento dos sistemas produtivos. A programação da produção preocupa-se com a alocação de recursos sobre o tempo para executar um conjunto de tarefas. No ambiente estudado neste trabalho as operações de cada tarefa são executadas em múltiplos estágios de produção, podendo variar a quantidade de máquinas em cada um deles. Cada operação é processada por apenas uma máquina em cada estágio. Os tempos de preparação das máquinas possuem uma variabilidade relevante em função da ordem de execução das tarefas nas mesmas. A função-objetivo considerada é a minimização do tempo médio de fluxo. Foram desenvolvidos quatro métodos heurísticos construtivos com base em algoritmos reportados na literatura para solução do problema flow shop permutacional e máquinas paralelas cujo tempo de setup é dependente da seqüência de execução das tarefas. Como não foram encontrados na literatura métodos de solução para o problema investigado neste trabalho, os algoritmos propostos foram comparados entre si. Foi efetuado um estudo da influência da relação entre as ordens de grandeza dos tempos de processamento das tarefas e do setup das máquinas em cada método de solução. Os resultados obtidos na experimentação computacional foram analisados e discutidos com base na porcentagem de sucesso, desvio relativo, desvio-padrão do desvio relativo e tempo médio de computação. / Scheduling theory attempts to provide guidelines and efficient methods to the use of the resources in the productive activities. This study investigates the hybrid flow shop problem with asymmetric sequence dependent setup times. The activity of production scheduling constitute is one of the several functions carried by production planning and control, which has as the objective command and management the production system, and characterize is one of the tasks most complex in production management. This activity of the scheduling aims within the allocation of the resources for the execution of jobs in a time base. In the environment studied in this work, the operations of each job are processed in multiple production stages. The number of machines in each stage can be different. Each operation is processed by only one machine in each stage. The setup times have a significant variability in function of the sequence of job processing on the machines. The objective is minimizing the mean flow time. Four constructive heuristic methods were proposed on the basis of algorithms reported in the literature for solving permutation flow shop and parallel machine problems with sequence dependent setup times. The proposed heuristic methods will have compared between themselves, since no constructive heuristics have been found in the literature for the scheduling problem considered in this work. It was carried out the study of the influence of the relations among the range of the times processing and setup times in each method. The statistics used in order to evaluate the heuristic performances were the percentage of success (in finding the best solution), relative deviation, standard deviation of relative deviation and average computation time. Results from computational experience are discussed.

A teoria de programação da produção preocupa-se em fornecer diretrizes e métodos eficientes para a utilização dos recursos nas atividades produtivas. Este trabalho investiga o problema de programação da produção em ambientes flow shop com máquinas múltiplas e tempos de preparação das máquinas assimétricos e dependentes da seqüência de execução das tarefas. A atividade de programação da produção constitui uma das várias funções executadas pelo planejamento e controle da produção, que tem como objetivo comandar e gerenciar o processo produtivo, e caracteriza uma das atividades mais complexas no gerenciamento dos sistemas produtivos. A programação da produção preocupa-se com a alocação de recursos sobre o tempo para executar um conjunto de tarefas. No ambiente estudado neste trabalho as operações de cada tarefa são executadas em múltiplos estágios de produção, podendo variar a quantidade de máquinas em cada um deles. Cada operação é processada por apenas uma máquina em cada estágio. Os tempos de preparação das máquinas possuem uma variabilidade relevante em função da ordem de execução das tarefas nas mesmas. A função-objetivo considerada é a minimização do tempo médio de fluxo. Foram desenvolvidos quatro métodos heurísticos construtivos com base em algoritmos reportados na literatura para solução do problema flow shop permutacional e máquinas paralelas cujo tempo de setup é dependente da seqüência de execução das tarefas. Como não foram encontrados na literatura métodos de solução para o problema investigado neste trabalho, os algoritmos propostos foram comparados entre si. Foi efetuado um estudo da influência da relação entre as ordens de grandeza dos tempos de processamento das tarefas e do setup das máquinas em cada método de solução. Os resultados obtidos na experimentação computacional foram analisados e discutidos com base na porcentagem de sucesso, desvio relativo, desvio-padrão do desvio relativo e tempo médio de computação. / Scheduling theory attempts to provide guidelines and efficient methods to the use of the resources in the productive activities. This study investigates the hybrid flow shop problem with asymmetric sequence dependent setup times. The activity of production scheduling constitute is one of the several functions carried by production planning and control, which has as the objective command and management the production system, and characterize is one of the tasks most complex in production management. This activity of the scheduling aims within the allocation of the resources for the execution of jobs in a time base. In the environment studied in this work, the operations of each job are processed in multiple production stages. The number of machines in each stage can be different. Each operation is processed by only one machine in each stage. The setup times have a significant variability in function of the sequence of job processing on the machines. The objective is minimizing the mean flow time. Four constructive heuristic methods were proposed on the basis of algorithms reported in the literature for solving permutation flow shop and parallel machine problems with sequence dependent setup times. The proposed heuristic methods will have compared between themselves, since no constructive heuristics have been found in the literature for the scheduling problem considered in this work. It was carried out the study of the influence of the relations among the range of the times processing and setup times in each method. The statistics used in order to evaluate the heuristic performances were the percentage of success (in finding the best solution), relative deviation, standard deviation of relative deviation and average computation time. Results from computational experience are discussed.

Abstract Optimizing the use of resources plays an important role in today’s modern manufacturing and service organizations. Scheduling, involving setup times and costs, leads to better allocation of resources over time to perform a collection of required tasks. This compilation dissertation examines how the learning effect of workers and a combination of setup activities can be used to optimize resource utilization in manufacturing systems and maintenance services. The learning effect is a technique that can model improvement in worker’s ability as a result of repeating similar tasks. By considering the learning effect, setup times will be reduced, and a schedule can be determined to place jobs that share similar tools and fixtures next to each other. The purpose is to schedule a set of jobs in a hybrid flow shop environment while minimizing two criteria that represent the manufacturers’ and consumers’ concerns: namely maximum completion time (makespan) and total tardiness. Combining setup activities can also reduce setup times and costs. In the maintenance of systems consisting of multiple components, costs can be saved when several components are jointly maintained. By using this technique, a schedule can be determined to minimize the total cost of maintenance and renewal projects for various components and their relevant setup activities. Mathematical programming models that incorporate these aspects of the problem are developed in this research and the performance of the proposed models are tested on a set of problem instances. The results of this work show that the proposed techniques perform well in reducing setup times and costs and eliminate the need for setups through scheduling. This work proposes several exact, heuristic, and meta-heuristic methods to solve the developed models and compare their efficiency. This study contributes to the theoretical discussion of multi-criteria production and maintenance scheduling. For practitioners, this dissertation work provides optimization techniques and tools through scheduling that can help keep costs down and allow companies to operate according to time and budget constraints. / Tiivistelmä Resurssien käytön optimoinnilla on tärkeä rooli nykypäivän tuotanto- ja palveluympäristöissä. Joukko tehtäviä voidaan toteuttaa resurssitehokkaammin niille varatussa ajassa huomioimalla aikataulutuksessa asetusajat ja –kustannukset. Tämä kokoomaväitöskirja tarkastelee, kuinka työntekijöiden oppimisefektin mallinnus ja asetustoimien yhdistäminen tukevat resurssien optimointia tuotantojärjestelmissä ja kunnossapitopalveluissa. Oppimisefekti on tekniikka, jolla voidaan mallintaa työntekijän osaamisen kehittymistä samankaltaisia työtehtäviä toistettaessa. Huomioimalla oppimisefekti asetusaikoja voidaan pienentää, ja töille luoda aikataulu jossa samankaltaiset työkalut ja laitteet ovat lähellä toisiaan. Osana väitöskirjaa esitetään työerän aikataulutus tietyssä yksittäistuotantoympäristössä minimoiden kahta kriteeriä: valmistajan tavoite kokonaisläpimenoaika ja asiakkaan tavoite yksittäisten töiden aikataulussa valmistuminen. Toinen väitöskirjassa esitetty tekniikka asetusaikojen ja –kustannusten pienentämiseen on asetustöiden yhdistely. Useista komponenteista koostuvassa systeemissä kustannussäästöjä voidaan saavuttaa huoltamalla useita komponentteja yhtä aikaa. Tämän yhdistelyn avulla voidaan luoda aikataulu, joka minimoi useiden komponenttien ylläpidon, uusimisen, ja asetuskustannusten kokonaiskustannuksen. Työssä mallinnetaan näitä tekniikoita matemaattisen ohjelmoinnin keinoin, ja luotuja malleja testataan joukolla esimerkkiongelmia. Väitöskirjan tulokset osoittavat, että ehdotetuilla tekniikoilla voidaan vähentää asetusaikoja ja –kustannuksia, tai poistaa asetustöistä aiheutuvia kustannuksia kokonaan. Siinä esitetään useita eksakteja, heuristisia ja metaheuristisia menetelmiä kehitettyjen mallien ratkaisuun ja niiden suorituskyvyn vertailuun. Työn tulokset edistävät tieteellistä keskustelua monikriteeriskeduloinnin alalla, erityisesti liittyen tuotanto- ja kunnossapitosysteemeihin. Käytännön toimijoille väitöskirja tarjoaa optimointitekniikoita- ja työkaluja aikataulutukseen ja sen kautta taloudellisissa ja ajallisissa rajoitteissa toiminnan mahdollistamiseen.

På senaste tiden har leveransprecision blivit allt viktigare eftersom kunder idag kännetecknas av att vara mer tidskänsliga och ständigt söker efter produkter som är specifikt anpassade till kunden. Tid har därmed betraktats som ett kriterium för konkurrens och är betydande för företag att kunna konkurrera på marknaden. Osäkerheter i marknaden har en stor påverkan på leveransprecision och det är en stor utmaning för företag att planera produktion utifrån dessa osäkerheter. När produktion för en artikel planeras måste en planerare ta hänsyn till osäkerheter som exempelvis att en maskin kan sluta fungera, att en defekt produkt måste omarbetas eller att det tar längre tid än planerat för att utföra ett arbetsmoment som leder till att en ledtid blir längre. Syftet med studien var att identifiera orsaker till skillnaden mellan planerad och verklig produktionstid samt ge förbättringsförslag för att minska skillnaden. Syftet har uppfyllts med hjälp utav en fallstudie på AQ Group i Pålsboda och genom intervjuer där planerad och verklig produktionstid har undersökts. En litteraturstudie har utnyttjats och tre frågeställningar har formulerats till studien. Dessa frågeställningar lyder: Hur ser skillnaden ut mellan planerad och verklig produktionstid? Vad är orsakerna till dessa skillnader? Hur kan dessa orsaker elimineras? Under det teoretiska avsnittet har fokuset varit på cykeltider, ställtider, produktionstid, Lean och produktionsplanering. Resultatet visar en total skillnad på 24 % mellan den planerade och verkliga produktionstiden över en 5-dagarsperiod. Några orsaker som påträffats är att de standardiserade arbetssätten inte är uppdaterade, inte är tvingande för operatörer att utföra och att det inte existerar några illustrationer för standardiseringen. En annan orsak är onödiga arbetsmoment där verktyg ligger långt ifrån arbetsstationerna och ibland fattas som gör att produktionstiden blir längre än planerat. Avslutningsvis presenteras kritiska förbättringsförslag som specifikt påverkar skillnaden i produktionstiderna och allmänna förbättringsförslag som AQ Group i Pålsboda kan ta nytta av för att effektivisera verksamheten. / In recent times delivery precision has become more important to customers, which today are characterized by being more time sensitive and constantly looking for products that are specifically tailored to the customer. Time is being seen as a criterion for competitors and it is important for companies to be able to compete in the market. Uncertainties in the current market have an effect on delivery precision and it is a major challenge for companies to plan production based on these uncertainties. When production for an article is planned, it should be planned in consideration of uncertainties, for example, a machine may break down, a defective product may need a rework or that it takes longer than planned to carry out an operation leading to a longer lead time. The purpose of the study was to identify causes of difference between planned and actual production time and to provide improvement suggestions to reduce the difference. The purpose has been achieved through a case study in AQ Group in Pålsboda with help of interviews where planned and actual production time has been investigated. A literature study has been used as well as three questions. These questions are: What is the difference between planned and actual production time? What are the causes of these differences? How can these causes be eliminated? During the theoretical section, the focus has been on cycle times, setup times, production time, Lean and production planning. The results show a total difference of 24% between the planned and actual production time over a 5-day period. Causes that have been found are that the standardized working methods are not up to date, are not mandatory for operators to perform and that there exist no illustrations for the standardization. Another cause is unnecessary work steps where tools is far away from the workstations and sometimes missing which leads to the production time being longer than planned. Lastly the study provides critical improvement suggestions that specifically affect the differences between planned and actual production times and general improvement suggestions that AQ Group in Pålsboda can take part of to streamline operations.

The global market is very competitive due to fast changes in complex business environments and to survive or expand the business, organizations must embrace organizational change. However, adapting to change is not always easy, where organizations may experience obstacles and resistance along the way. Organizations may also experience that it is very hard to implement lean successfully, due to lack of know-how but especially resistance. The traditional way is to blame the blue-collars for the disturbing circumstances but in modern times the wind has changed its course where the managers themselves can be a contributor for implementation failures. Therefore, the aim of the research is to investigate what advantages that can be obtained by implementing a certain change initiative. Furthermore, to determine where resistance occurs and how to eliminate or reduce them. The change initiative in this research is implemented by conducting a case study in a Small Medium Enterprise (SMEs), where the main goal is to reduce the changeover time of a machine, by finding improvement suggestions using the Single Minute Exchange of Die (SMED) methodology. The results generated several improvement opportunities and gave an indication that there is a huge potential for improvements and elimination of waste during a typical changeover. The positive outcomes of implementing these improvement opportunities could theoretically reduce the changeover time, which directly reduces the overall cost but higher responsiveness, flexibility and efficiency can also be obtained. However, the evidence tells a story where the organization could experience obstacles during the implementation of the improvement suggestions, due to several factors. Surprisingly, the evidence points out that one root problem for resistance is difficulties of describing the underlying reason of the change initiative to the blue-collars. Moreover, there is in fact resistance and lack of awareness of the SMED methodology among the blue-collars and the managers, where fear of the unknown is another root problem for resistance.

No description available.

The purpose of this thesis is to develop a model that will guide a company towards a decision of whether to change the current due date of work orders or not. The model will help the company to reveal the technical and financial factors that will be affected and how these factors can be assessed. After accomplishing a thorough literature review, we found no existing practical models in this specific area. We developed a model to cover this gap in the existing theories. A case study approach was used to test the developed model on our case company Elitfönster in Lenhovda who manufactures windows. We applied our model at the processing department and the change concerned going from a weekly to a daily due date of work orders. The technical factors that would be affected by the change of the due date are; setup times, lead time and output of components. The financial factors that will be affected are the tied-up capital and the manning. We found that a change could not be carried through without a purchase of an extra plane. The model also showed that the financial benefits that the change generated could not surpass the costs that an extra plane would cause. Thereby, our recommendations to the case company are to keep the current due date of work orders until the rest of the company can handle the extra components that can be produced after the change. / Syftet med denna uppsats är att utveckla en modell som ska vägleda ett företag mot ett beslut om man ska ändra den nuvarande tidpunkt när en arbetsorder ska vara färdigställd, eller inte. Modellen kommer att hjälpa företaget att påvisa de tekniska och finansiella faktorer som kommer att påverkas och hur dessa kan bedömas. Efter att ha gjort en grundlig litteraturstudie kunde vi inte hitta några existerande modeller inom detta specifika område. Vi utvecklade en modell för att täcka denna brist i den existerande teorin. Vi använde oss av en fallstudie för att testa vår utvecklade modell på Elitfönster i Lenhovda som tillverkar fönster. Vi applicerade vår modell på maskinverkstaden och förändringen handlade om att gå från att färdigställa arbetsorder på en vecka till att färdigställa dem på en dag. De tekniska faktorer som skulle påverkas av en förändring är; ställtiderna, ledtiden och mängden producerade komponenter. De finansiella faktorerna som kommer att påverkas är mängden bundet kapital samt bemanningen. Vi kom fram till att en förändring inte kunde genomföras utan att köpa in en extra hyvel. Modellen visade också att de finansiella fördelarna som en förändring skulle generera inte skulle motsvara de kostnader som den extra hyveln skulle orsaka. Våra rekommendationer till företaget är således att fortsätta med den nuvarande tidpunkt när en arbetsorder ska vara färdigställd tills resten av företaget kan hantera de extra komponenter som skulle kunna bli producerade efter förändringen.

<p>The purpose of this thesis is to develop a model that will guide a company towards a decision of whether to</p><p>change the current due date of work orders or not. The model will help the company to reveal the technical and</p><p>financial factors that will be affected and how these factors can be assessed. After accomplishing a thorough</p><p>literature review, we found no existing practical models in this specific area. We developed a model to cover this</p><p>gap in the existing theories. A case study approach was used to test the developed model on our case company</p><p>Elitfönster in Lenhovda who manufactures windows. We applied our model at the processing department and the</p><p>change concerned going from a weekly to a daily due date of work orders. The technical factors that would be</p><p>affected by the change of the due date are; setup times, lead time and output of components. The financial</p><p>factors that will be affected are the tied-up capital and the manning. We found that a change could not be carried</p><p>through without a purchase of an extra plane. The model also showed that the financial benefits that the change</p><p>generated could not surpass the costs that an extra plane would cause. Thereby, our recommendations to the</p><p>case company are to keep the current due date of work orders until the rest of the company can handle the extra</p><p>components that can be produced after the change.</p> / <p>Syftet med denna uppsats är att utveckla en modell som ska vägleda ett företag mot ett beslut om man ska</p><p>ändra den nuvarande tidpunkt när en arbetsorder ska vara färdigställd, eller inte. Modellen kommer att hjälpa</p><p>företaget att påvisa de tekniska och finansiella faktorer som kommer att påverkas och hur dessa kan bedömas.</p><p>Efter att ha gjort en grundlig litteraturstudie kunde vi inte hitta några existerande modeller inom detta specifika</p><p>område. Vi utvecklade en modell för att täcka denna brist i den existerande teorin. Vi använde oss av en</p><p>fallstudie för att testa vår utvecklade modell på Elitfönster i Lenhovda som tillverkar fönster. Vi applicerade vår</p><p>modell på maskinverkstaden och förändringen handlade om att gå från att färdigställa arbetsorder på en vecka</p><p>till att färdigställa dem på en dag. De tekniska faktorer som skulle påverkas av en förändring är; ställtiderna,</p><p>ledtiden och mängden producerade komponenter. De finansiella faktorerna som kommer att påverkas är</p><p>mängden bundet kapital samt bemanningen. Vi kom fram till att en förändring inte kunde genomföras utan att</p><p>köpa in en extra hyvel. Modellen visade också att de finansiella fördelarna som en förändring skulle generera</p><p>inte skulle motsvara de kostnader som den extra hyveln skulle orsaka. Våra rekommendationer till företaget är</p><p>således att fortsätta med den nuvarande tidpunkt när en arbetsorder ska vara färdigställd tills resten av företaget</p><p>kan hantera de extra komponenter som skulle kunna bli producerade efter förändringen.</p>