A robust simulation-based optimization approach is proposed for truck-shovel systems in surface coal mines to maximize the expected value of revenue obtained from loading customer trains. To this end, a large surface coal mine in North America is considered as case study. A data-driven modeling framework is developed and then applied to automatically generate a highly detailed simulation model of the mine in Arena. The framework comprises a formal information model based on Unified Modeling Language (UML), which is used to input mine structural as well as production information. Petri net-based model generation procedures are applied to automatically generate the simulation model based on the whole set of simulation inputs. Then, factors encountered in material handling operations that may affect the robustness of revenue are then classified into 1) controllable; and 2) uncontrollable categories. While controllable factors are trucks locked to routes, uncontrollable factors are inverses of summation over truck haul, and shovel loading and truck-dumping times for each route. Historical production data of the mine contained in a data warehouse is used to derive probability distributions for the uncontrollable factors. The data warehouse is implemented in Microsoft SQL, and contains snapshots of historical equipment statuses and production outputs taken at regular intervals in each shift of the mine. Response Surface Methodology is applied to derive an expression for the variance of revenue as a function of controllable and uncontrollable factors. More specifically, 1) first order and second order effects for controllable factors, 2) first order effects for uncontrollable factors, and 3) two factor interactions for controllable and uncontrollable factors are considered. Latin Hypercube Sampling method is applied for setting controllable factors and the means of uncontrollable factors. Also, Common Random Numbers method is applied to generate the sequence of pseudo-random numbers for uncontrollable factors in simulation experiments for variance reduction between different design points of the metamodel. The variance of the metamodel is validated using leave-one-out cross validation. It is later applied as an additional constraint to the mathematical formulation to maximize revenue in the simulation model using OptQuest. The decision variables in this formulation are truck locks only. Revenue is a function of the actual quality of coal delivered to each customer and their corresponding quality specifications for premiums and penalties. OptQuest is an optimization add-on for Arena that uses Tabu search and Scatter search algorithms to arrive at the optimal solution. The upper bound on the variance as a constraint is varied to obtain different sets of expected value as well as variance of optimal revenue. After comparison with results using OptQuest with random sampling and without variance expression of metamodel, it has been shown that the proposed approach can be applied to obtain the decision variable set that not only results in a higher expected value but also a narrower confidence interval for optimum revenue. According to the best of our knowledge, there are two major contributions from this research: 1) It is theoretically demonstrated using 2-point and orthonormal k-point response surfaces that Common Random Numbers reduces the error in estimation of variance of metamodel of simulation model. 2) A data-driven modeling and simulation framework has been proposed for automatically generating discrete-event simulation model of large surface coal mines to reduce modeling time, expenditure, as well as human errors associated with manual development.

As competition for fossil fuels accelerates, alternative sources of chemicals, fuels, and energy production become more appealing to researchers and the layman. Among the candidates to fill this growing niche is lignocellulosic biomass. Many researchers have examined supply chain design and optimization for biofuel and bioenergy production throughout the years. However, these models often fail to capture the variability and uncertainty inherent to the biomass supply chain. Multiple factors with high degrees of stochasticity can have major impacts on the performance of a biorefinery: weather, biomass quality, feedstock availability, and market demand for products are just a few. To begin to address this issue, a discrete event simulation model has been developed to examine the economic performance of a region specific, multifeedstock biorefinery supply chain. Probability distributions developed for product demand and feedstock supply begin to address the random nature of the supply chain. Model development is discussed in the context of a multidisciplinary framework for biorefinery supply chain design. A case study, sensitivity analysis, and scenario analysis, are utilized to examine the capabilities of the model.

This thesis aims to fill the gaps in the literature of the theory of constraints (TOC) in publicly funded health systems. While TOC seems to be a natural fit for this resource-constrained environment, there are still no reported application of TOC’s drum-buffer-rope tool and inadequate customizations with regards to defining system-wide goal and performance measures. The “Drum-Buffer-Rope for an Outpatient Cancer Facility” chapter is a real world case study exploring the usefulness of TOC’s drum-buffer-rope scheduling technique in a publicly funded outpatient cancer facility. With the use of a discrete event simulation model populated with historical data, the drum-buffer-rope scheduling policy is compared against “high constraint utilization” and “low wait time” scenarios. Drum-buffer-rope proved to be an effective mechanism in balancing the inherent tradeoff between the two performance measures of instances of delayed treatment and average patient wait time. To find the appropriate level of compromise in one performance measure in favor of the other, the linkage of these measures to system-wide performance measures are proposed. In the “Theory of Constraints’ Performance Measures for Publicly Funded Health Systems” chapter, a system dynamics representation of the classical TOC’s system-wide goal and performance measures for publicly traded for-profit companies is developed, which forms the basis for developing a similar model for publicly funded health systems. The model is then expanded to include some of the factors that affect system performance, providing a framework to apply TOC’s process of ongoing improvement in publicly funded health systems. The “Connecting Low-Level Performance Measures to the Goal” chapter attempts to provide a framework to link the low-level performance measures with system-wide performance measures. It is claimed that until such a linkage is adequately established, TOC has not been fully transferred to publicly funded health systems.

Despite nearly 50 years of attempts at reform, the US defense acquisition system continues to deliver weapon systems over budget, behind schedule, and with performance shortfalls. Why has acquisition reform failed? Three potential contributors were identified in the literature: the misalignment of incentives, a lack of a systems view, and a lack of objective evaluation criteria. This thesis considers these problems in the context of the most recent effort to transform the defense acquisition enterprise, evolutionary acquisition. First, game theory was employed to analyze the incentives of participants in the defense acquisition enterprise regarding the use of immature technology. It was found that there is a tragedy of the commons at work where acquisition programs serve as a common resource for stakeholders to meet their goals. The result is that participants are incentivized to use immature technology in contradiction of evolutionary acquisition policies. Second, the cost and performance of evolutionary acquisition in the context of the defense acquisition system was analyzed using a discrete event simulation. What was found was that evolutionary acquisition may lead to better performance from fielded systems and lower cost programs but also that the cost of operating the acquisition system as whole may actually rise. Finally, a method using price indices was developed to translate the gain in buying power resulting from improvements to the defense acquisition system into a monetary valuation. This allows for the application of options analysis to determine whether or not it is cost effective to pursue a potential improvement. A comparison with a more traditional approach revealed that simply using the NPV of cost savings may significantly understate value.

As systems become more interconnected, the focus of engineering design must shift to include consideration for systems of systems (SoS) e ects. As the focus shifts from singular systems to systems of systems, so too must the focus shift from performance based analysis to an evaluation method that accounts for the tendency of such large scale systems to far outlive their original operational environments and continually evolve in order to adapt to the changes. It is nearly impossible to predict the nature of these changes, therefore the rst focus of this thesis is the measurement of the exibility of the SoS and its ability to evolve and adapt. Flexibility is measured using a combination of network theory and a discrete event simulation, therefore, the second focus is the development of a simulation environment that can also measure the system's performance for baseline comparisons. The results indicate that simulated exibility is related to the performance and cost of the SoS and is worth measuring during the design process. The third focus of this thesis is to reduce the computational costs of SoS design evaluation by developing heuristics for exibility. This was done by developing a network model to correspond with the discrete event simulation and evaluating network properties using graph theory. It was shown that the network properties can correlate with simulated exibility. In such cases it was shown that the heuristics could be used in connection with an evolutionary algorithm to rapidly search the design space for good solutions. The entire methodology was demonstrated on a multi-platform maintenance planning problem in connection with the Navy Hardware Open System Technologies initiative.

The most costly and labor-intensive activity for almost every warehouse is the order picking process and a key challenge for manufacturing companies is to store parts in an efficient way. Therefore, to minimize the order retrieval time when picking from a storage, the need of a sufficient storage categorization strategy becomes vital. One of the logistics centers at Scania in Södertälje stores parts that will be transported to the chassis assembly and the assembly of gearboxes and axles when needed in the production. In one of the storage areas at the logistics center, namely the PS storage, the forklift drivers picking from the storage have experienced congestion in the storage aisles and that it might be possible to reduce the order fulfillment time when picking the orders. This master thesis aims to investigate the possibility of optimizing the picking process in the PS storage, with respect to the order fulfillment time for the forklift drivers, with categorization of the goods. This has been analyzed with a heuristic optimization approach and with the use of a discrete event simulation model, where different categorization strategies have been applied on the storage and compared to the current state. By categorizing the goods in the PS storage, a reduction of the order fulfillment time can be done of around 4% - 5% compared to the current state with all tested categorization strategies. The strategy which has been shown to give the largest improvement is by categorizing the parts in the storage according to their final delivery address at the production line, which would reduce the order fulfillment time by 5.03% compared to the current state. With this categorization method, parts that are picked on the same route are located close to each other.

Les technologies RFID présentent des avantages non négligeables en comparaison aux technologies d'identification actuelles. Cependant, l'intégration de ces technologies dans les chaînes logistiques implique souvent des coûts élevés. Ainsi, les entreprises doivent conduire des analyses poussées pour évaluer l'impact des RFID sur le fonctionnement et l'économie des chaînes logistiques et décider de l'intégration ou non de ces technologies.Dans cette thèse nous nous concentrons sur la modélisation et l'analyse de l'introduction des technologies RFID dans les chaînes logistiques. Nous présentons d'abord une information générale sur les technologies RFID. Nous analysons ensuite la littérature sur l'intégration des RFID dans les chaînes logistiques en focalisant sur les défis et les avantages liés à l'intégration de ces technologies. Nous développons deux approches (analytique et par simulation) afin d'évaluer les impacts qualitatifs et quantitatifs des technologies RFID sur le fonctionnement et le profit des chaînes logistiques. Nous développons aussi une analyse du retour sur investissement (ROI), pour comparer les revenus obtenus à l'aide des technologies RFID avec les coûts associés à leur intégration. D'autre part, nous nous intéressons à l'amélioration des avantages de RFID dans les chaînes logistiques. Nous comparons les impacts de l'intégration de différentes RFID dans les chaînes logistiques par un remplacement simple des technologies d'identification actuelles et par la réorganisation des chaînes logistiques utilisant les nouvelles possibilités des technologies RFID. Les résultats obtenus dans ce travail mettent en évidence des perspectives intéressantes pour des études futures. L'originalité de cette étude est que nous comparons les impacts de plusieurs technologies RFID en les intégrant aux systèmes actuels et en reconstruisant des chaînes logistique grâce aux possibilités offertes par des technologies RFID. Notre modèle de simulation à événements discrets peut être utilisé comme un outil d'aide à la décision pour les sociétés qui visent à intégrer des technologies RFID.L'originalité de cette étude est que nous comparons les impacts de plusieurs technologies RFID en les intégrant aux systèmes actuels et en reconstruisant des chaînes logistique par les possibilités offertes par des technologies RFID. Notre simulation peut être utilisée comme un outil d'aide à la décision pour les sociétés qui considèrent l'intégration de technologies RFID. / In the last few years, RFID technologies have drawn considerable interests as one of the possible solutions to overcome these supply chain problems. However, integrating these technologies in supply chains induces large costs. Thus, companies must evaluate the impacts of RFID technologies on supply chain performances and economics, in order to decide whether these technologies should be integrated or not.In this thesis we focus on modeling and analyzing the impacts of introducing RFID technologies in supply chain. We first provided a basic knowledge of RFID technologies that includes the working process, the challenges and the obstacles of applying RFID technologies in supply chains. We then reviewed the literature and discussed the challenges and benefits related to integrating RFID in supply chains. Finally, we developed analytical and simulation approaches to evaluate qualitative and quantitative impacts of RFID technologies on supply chain performances and profits. We also developed ROI (Return On Investment) analysis, to compare the benefits obtained by RFID technologies with the costs associated to the integration of these technologies. Furthermore, we focused on how the benefits of RFID technologies can be improved by re-engineering supply chains using the characteristics of RFID technologies. Results obtained in this thesis highlight interesting perspectives for future studies. The main originality of this study is to compare the impacts of integrating different RFID technologies to supply chains by just replacing current identification technologies and by re-engineering supply chains using the new possibilities provided by RFID technologies. Our simulation can also be used as a decision support tool by companies that integrate RFID technologies.

In today’s world, simulation and optimization are playing a vital role in reducing the time, cost and preserving resources. In manufacturing industries, there are ample amount of problems that go on with the expansion of the industry. In such cases, to tackle these problems simulation can be helpful to check whether any change in the current situation makes any effect on the current efficiency of the overall plant. In the presented case study, a solution to the problem of internal and external logistics has been designed by using simulation and optimization to improve part of a material flow of an organization. Basically, the organization whose major production is established in the south of Sweden deals with the manufacturing and assembly of equipment. Before the dispatch, all of them go to the painting section which is the expansion of the present shop floor. However, the design and analysis of the material handling system to feed the new painting line which is going to be established by the organization is the aim of this case study. While achieving this aim the literature regarding the discrete event simulation, Lean and Simulation-Based optimization related to the material handling system has been done. Furthermore, the appropriate material handling systems along with the different scenarios were suggested to reduce the cost and the lead times between the production line and the new painting line. To support this process a methodology combining simulation, optimization and lean production has been implemented under the framework of the design and creation research strategy. In the Kaizen workshop organized at a company with managers and stakeholders, the designed scenarios were presented and after some discussion one of them was chosen and the selected scenario was designed and optimized. Moreover, the Simulation-Based multi-objective optimization has been helpful for the optimization of the designed model proposed as a final solution.

Made available in DSpace on 2016-06-02T19:50:13Z (GMT). No. of bitstreams: 1 Retido.pdf: 19733 bytes, checksum: 6aad255badc436a06364517de2344ab6 (MD5) Previous issue date: 2011-11-28 / Brazil is one of the greatest sugarcane producers of the world, with figures that exceeds 620 million tons in 2010/2011 harvest season. There is an expectation of strong increase of Brazilian sugarcane production in next years due to increase in sales estimulated by the low production cost of sugar and alcohol and also the increase of the internal and external demands for ethanol, in substitution to fossil fuels. At the same time, environmental issues led the publication of a specific legislation that established a schedule to the next years to stop sugarcane burning previous to hand cutting, a traditional activity. This legal restriction brought a new scenario, as an increasing amount of biomass, that used to be burnt, will be available for other uses such as ethanol extra production, by technologies still in development or to energy generation, similar to what is done with bagasse (by means of cogeneration). Independent of its use, sugarcane and its biomass processing configures a complex operation as big volumes of materials are handled using high cost equipment which a high interaction among them. Several systems can be configured to do this task, varying equipments and settings of the operations performed by them. The selection of equipment and operational proceedings is one of the main tasks of managers at sugarcane mills. In order to help in decision taking situations, in this study, a discrete event simulation model was designed and modeled to represent sugarcane harvesting systems with biomass recovery. Conventional sugarcane harvesting and partial cleaning sugarcane harvesting were represented in a unique simulation model, as well as the correspondent alternatives of biomass recovery and delivery at mills. The operational characteristics of these systems were previously set in the model and can be modified through electronic spreadsheets, interfaced with the simulation model that manages the input and output of data. Field tests were done to evaluate equipment performance and generate data to the simulation model, which was used in two studies. In the first study, three sugarcane harvesting and biomass recovery systems were simulated using the data collected at each field test, representing those systems differently, under their own observed conditions. In the second study, the three systems were again compared, however, under the same conditions, with the same set of assumptions, in order to permit their comparison in equal basis. All scenarios considered a typical mill operation that processes two million tons of sugarcane per harvest season. The simulation model enabled the evaluation of the selected systems considering sugarcane and biomass production as well as their economic evaluation. / O Brasil é um dos maiores produtores mundiais de cana-de-açúcar, com processamento superior a 620 milhões de toneladas na safra 2010/2011. A perspectiva para os próximos anos é de forte crescimento da produção de açúcar e de etanol, impulsionada pelo aumento das vendas decorrentes do baixo custo de produção e do aumento do consumo de etanol, interno e externo, em substituição ao uso de combustíveis fósseis. Simultaneamente, a maior preocupação ambiental levou à implantação de leis que estipulam a redução gradativa da queima controlada, tradicionalmente utilizada no manejo da cana-de-açúcar previamente ao corte manual. Este fato estabeleceu uma mudança de cenário, pois, a biomassa que outrora era queimada, surgiu como subproduto passível de utilização, seja para a fabricação de etanol, por tecnologias ainda em desenvolvimento para escala comercial, ou para a geração de energia, da mesma forma que o bagaço (cogeração). Independente da destinação, o processamento da cana-de-açúcar e de sua biomassa caracteriza um sistema logístico complexo, pois grandes volumes de material são movimentados, utilizando equipamentos de alto custo e com algo grau de interação. Diversos sistemas podem ser configurados com a finalidade de processamento da cana e da biomassa, variando equipamentos e operações. A seleção destas opções constitui uma das principais tarefas da gestão das operações das usinas. Com o objetivo de auxiliar tomadas de decisão, neste trabalho desenvolveu-se um modelo de simulação de eventos discretos dos sistemas de colheita de cana-de-açúcar com aproveitamento da biomassa. Os processos de colheita de cana-de-açúcar com limpeza convencional e colheita com limpeza parcial foram representados em um único modelo, bem como as alternativas de recolhimento e entrega da biomassa. As características operacionais dos sistemas foram parametrizadas, sendo possível configurar cenários de interesse por meio de planilhas eletrônicas, que interagem com o modelo e facilitam a inserção de dados e a análise de resultados. Ensaios de campo foram conduzidos para testar o desempenho dos equipamentos e gerar dados para o modelo de simulação, que foi usado para realizar dois estudos. No primeiro estudo simularam-se três alternativas de sistemas de colheita de cana-deaçúcar e processamento de biomassa diferentemente, reproduzindo as condições operacionais observadas em cada ensaio de campo. No segundo estudo, os três sistemas foram novamente comparados, porém em igualdade de condições, com o mesmo conjunto de premissas, de forma a poder compará-los. Em todos os cenários adotou-se como padrão uma usina com capacidade de processamento de dois milhões de toneladas de cana por safra. O modelo permitiu avaliar os sistemas selecionados, tanto do ponto de vista operacional, com análise das produções de cana-de-açúcar e de biomassa, como também do ponto de vista econômico.

Le travail de recherche présenté dans cette thèse est l’un des premiers dans le domaine de la gestion optimisée des services d’aide médicale urgente en France. Il est conduit dans le cadre d’un projet ANR qui vise à proposer de nouveaux scénarios d’organisation pour le SAMU du département du Val-de-Marne pour offrir aux patients l’accès adapté aux soins, tout en disposant de ressources limitées. Pour cela, nous développons un modèle de simulation à évènements discrets qui modélise et évalue la performance actuelle de ce système complexe et identifie des pistes d’amélioration susceptibles de réduire la durée entre la réception de l’appel et l’arrivée d’une équipe sur le lieu de l’accident, appelé temps de réponse, qui est un aspect critique dans les systèmes d’urgence pré-hospitaliers. Ce modèle de simulation est utilisé pour quantifier l’impact de divers scénarii se rapportant aux nombres de ressources humaines et matérielles, à la localisation de ces ressources à travers le territoire du Val-de-Marne de manière statique et à l’affectation de ces ressources aux interventions. En outre, nous avons effectué des analyses de sensibilité sur différents paramètres du modèle comme le nombre d’appels reçus, les temps de trajet et les temps de service. Finalement, nous avons utilisé deux approches d’optimisation par simulation afin d’étudier l’impact de la relocalisation des équipes dans différentes bases du département plusieurs fois dans une journée afin de tenir compte des fluctuations des temps de trajet et du nombre de ressources. Les résultats de ces deux approches ont été analysés puis comparés au regard des temps de calcul et de la distribution du temps de réponse. / The research addressed in this thesis is one of the first studies to address the Emergency Medical Service in France, known as SAMU (which stands for the French acronym of Urgent Medical Aid Services). It is funded by the French National Research Agency and aims at improving the organizational processes of the Val-de-Marne department SAMU system in order to meet the population’s needs under limited resources. For this purpose, we develop a discrete event simulation model in order to assess the current performance of this complex system, as well as to investigate the effects of potential process changes that would lead to enhanced operational efficiency, in terms of response time performance (i.e. the period between the receipt of a call and the first arrival of a rescue team at the scene), which is a critical aspect for SAMU providers. This model was used as a decision-support tool for comparing the relative benefits of several scenarios mainly related to the needed resource levels and static location of rescue teams throughout the Val-de-Marne area and their assignment to incoming calls. Sensivity analyses were also performed by changing values of some input parameters such as arrival rates of calls, travel times and service times. Finally, we used two simulation optimization approaches to analyze the impact of rescue teams assignment to bases by considering temporal fluctuations of travel times and number of resources during a day. Experimental results of the two approaches were analyzed and compared regarding computational times and response time distribution.