Předkládaná práce se zabývá návrhem modelu dynamiky paralelního manipulátoru optimálního pro účely návrhu řízení. Zvolený přístup je založen na modelování dynamiky systému v simulačním prostředí Matlab SimMechanics následovaném linearizací modelu. Výsledný stavový lineární model mimo jiné umožňuje snadné posouzení řiditelnosti a pozorovatelnosti modelu. Díky své relativní jednoduchosti je model také výpočetně nenáročný. Přístup je demonstrován na návrhu dvouvrstvého řízení SimMechanics modelu Stewartovy platformy, na kterém bylo následně navržené řízení úspěšně testováno. Podstatná část práce obsahuje přístup k modelování neurčitých parametrů dynamického modelu Stewartovy platformy a stejnosměrného motoru Maxon RE 35 a jeho výsledky. Předložený přístup je založen na modelování parametrické neurčitosti způsobem, kdy je neurčitost definována individuálně pro jednotlivé prvky stavových matic modelu. Samotná neurčitost je potom určena rozdílem mezi jednotlivými parametry příslušných matic nominálního modelu a modelu se stanovenou maximální neurčitostí parametrů. Výsledný neurčitostní model je vzhledem ke své stavové reprezentaci vhodný pro návrh regulátoru založeném na metodách návrhu robustního řízení, například minimalizaci normy H-nekonečno. Popsaná metoda byla použita pro kompenzaci posunu mezi pracovními body, okolo kterých je prováděna linearizace a pro kompenzaci nepřesnosti modelování vybraných parametrů modelů Stewartovy platformy a stejnosměrného motoru. Získané modely (v prostředí SimMechanics a neurčitostní model) byly experimentálně porovnány s chováním jednoho z lineárních pohonů Stewartovy platformy. Rozdíl v datech obdržených ze simulace v prostředí SimMechanics a naměřených na reálném stroji byl téměř kompletně pokryt neurčitostním modelem. Prezentovaná metoda neurčitostního modelování je velice univerzální a aplikovatelná na libovolný stavový model.

Este trabalho cria um modelo, em simulação a eventos discretos, utilizando o software ARENA 5.0, do centro de distribuição de peças de uma empresa do ramo automotivo, para geração de informações relacionadas ao deslocamento dos funcionários nos corredores. Existem diversas variáveis que estão diretamente relacionadas à movimentação no processo de retirada de itens, tais como capacidade e velocidade do transportador manual, influência do peso dos itens na coleta, dentre outras, que dificultam o processo de tomada de decisão. As técnicas propostas na bibliografia apresentam dificuldades em fornecer soluções já que não são capazes de trabalhar simultaneamente com estas variáveis, apresentando, assim, resultados discrepantes com a realidade. A simulação permite lidar com tais variáveis e fornecer resultados que servirão de suporte aos decisores para a tomada de decisão e assim gerenciar melhor os funcionários para completar a coleta de itens dos pedidos sem atrasos / This work builds a model, by the discrete event simulation, using the software ARENA 5.0, of a parts distribution centre of an automotive company, to generate information related to employees routing in aisles. There are several variables related to the movement in the retrieving process, such as capacity and velocity of the manual trolley, influence of the mass of items in the collecting process, among others, which make the decision process difficult. The techniques found in the literature demonstrate certain difficulties in providing solutions because they are not capable of dealing with those variables simultaneously, presenting, consequently, discrepancy results to the reality. The simulation permits to deal with those variables simultaneously and proving results to support managers in decisions and, therefore, to improve employees management in order to finalize the collecting of items without delay

Este trabalho cria um modelo, em simulação a eventos discretos, utilizando o software ARENA 5.0, do centro de distribuição de peças de uma empresa do ramo automotivo, para geração de informações relacionadas ao deslocamento dos funcionários nos corredores. Existem diversas variáveis que estão diretamente relacionadas à movimentação no processo de retirada de itens, tais como capacidade e velocidade do transportador manual, influência do peso dos itens na coleta, dentre outras, que dificultam o processo de tomada de decisão. As técnicas propostas na bibliografia apresentam dificuldades em fornecer soluções já que não são capazes de trabalhar simultaneamente com estas variáveis, apresentando, assim, resultados discrepantes com a realidade. A simulação permite lidar com tais variáveis e fornecer resultados que servirão de suporte aos decisores para a tomada de decisão e assim gerenciar melhor os funcionários para completar a coleta de itens dos pedidos sem atrasos / This work builds a model, by the discrete event simulation, using the software ARENA 5.0, of a parts distribution centre of an automotive company, to generate information related to employees routing in aisles. There are several variables related to the movement in the retrieving process, such as capacity and velocity of the manual trolley, influence of the mass of items in the collecting process, among others, which make the decision process difficult. The techniques found in the literature demonstrate certain difficulties in providing solutions because they are not capable of dealing with those variables simultaneously, presenting, consequently, discrepancy results to the reality. The simulation permits to deal with those variables simultaneously and proving results to support managers in decisions and, therefore, to improve employees management in order to finalize the collecting of items without delay

Small unmanned vehicles are used to provide the eye-in-the-sky alternative to monitoring and regulating traffic dynamically. Spatial-temporal visual data are collected in real-time and they are used to generate traffic-related statistical profiles, serving as inputs to traffic simulation models. Generated profiles, which are continuously updated, are used to calibrate traffic model parameters, to obtain more accurate and reliable simulation models, and for model modifications. This method overcomes limitations of existing traffic simulation models, which suffer from outdated data, poorly calibrated parameters, questionable accuracy and poor predictions of traffic patterns.

Call centers are an important function of most companies’ day to day business activities. They are often the link between a company and its customers and hugely impact the customer’s perspective or point of view (POV) of a company. A call center in the most general sense is a place, representing a business, which receives inbound calls from customers and/or makes outbound calls to customers, the latter being most commonly referred to as telemarketing. There was a time when a typical call center strictly consisted of agents who handled inbound/outbound calls; these agents are considered specialized agents. Generally speaking, a specialized agent is one trained, in-depth, in a particular area of knowledge. Most businesses have transgressed from your typical call center into contact centers. Contact centers operate essentially the same as a call center but interact with the customer in a variety of ways including, but not limited to: Phone, Mail, Fax, Email, and Internet (via online chat and instant messaging applications). The dynamics of these kinds of call centers has caused an increase in the need for agents to become more diverse in their talents and abilities to handle different types of calls. This has lead to specialized agents becoming general or “cross-trained” agents in which they are trained, broadly, over several areas of knowledge. The purpose of this thesis is to compare specialized agents to cross-trained agents and through the use of simulation, determine which of the two are more efficient and reliable in their ability to service the customer. This thesis has three major components: Simulation, Reliability Analysis, and Comparison. The results indicate that a cross-trained model is more reliable and efficient than a specialized model. Performance metrics common to call center literature, simulation, and Lean reliability systems were used to determine the effectiveness and reliability of the two models.

Increasing competition from traditional and emerging channels has placed new emphasis on rapid innovation and continuous differentiation in every aspect of supply chain, from earliest production stage to the final distribution steps. To bridge the gap between brilliant ideas and successful business initiatives, leading companies implement engineering simulation particularly in logistics and supply chain management (LSCM). Discrete event simulation (DES) and system dynamics (SD) are two modeling approaches widely used in this field. However there are not much done researches about the applications of these simulation approaches in supply chain context of Swedish Manufacturing Industries (SMI). This study explores the application of DES and SD in LSCM of SMI by looking at the nature and level of issues modeled. Journal papers and master theses that use these modeling approaches to study supply chains, published between 1990 and 2012 are reviewed. A total of 39 articles are analyzed to identify the frequency with which the two simulation approaches are used as modeling tools in LSCM of SMI. Our findings suggest that DES has been used more frequently to model supply chains in SMI. The results also show that not all the LSCM issues have been addressed evenly and generally tactical/operational issues have been modeled more frequently. The results of this study inform the existing literature about the use of DES and SD in LSCM of SMI.

The creation of large-scale simulation models is a difficult and time-consuming task. Yet simulation is one of the techniques most frequently used by practitioners in Operations Research and Industrial Engineering, as it is less limited by modeling assumptions than many analytical methods. The effective generation of simulation models is an important challenge. Due to the rapid increase in computing power, it is possible to simulate significantly larger systems than in the past. However, the verification and validation of these large-scale simulations is typically a very challenging task. This thesis introduces a simulation framework that can generate a large variety of manufacturing simulation models. These models have to be described with a simulation data specification. This specification is then used to generate a simulation model which is described as a Petri net. This approach reduces the effort of model verification. The proposed Petri net data structure has extensions for time and token priorities. Since it builds on existing theory for classical Petri nets, it is possible to make certain assertions about the behavior of the generated simulation model. The elements of the proposed framework and the simulation execution mechanism are described in detail. Measures of complexity for simulation models that are built with the framework are also developed. The applicability of the framework to real-world systems is demonstrated by means of a semiconductor manufacturing system simulation model.

This thesis concerns the design, analysis and testing of adaptive controllers for rotary wing aircraft, in particular helicopters. A non-linear helicopter model is developed and validated by trim and dynamic response analyses. A inner-outer loop cascade controller is designed with a trajectory generator in the most outer layer and an adaptive neural network controller is implemented to the inner loop. Controller is then challenged to carry out complex maneuvers autonomously under turbulence. Finally, the center of gravity location is varied to severe values to observe adaptation characteristics to investigate the requirement on the knowledge of the center of gravity location during such adaptive controller design.

Call centers are an important function of most companies’ day to day business activities. They are often the link between a company and its customers and hugely impact the customer’s perspective or point of view (POV) of a company. A call center in the most general sense is a place, representing a business, which receives inbound calls from customers and/or makes outbound calls to customers, the latter being most commonly referred to as telemarketing. There was a time when a typical call center strictly consisted of agents who handled inbound/outbound calls; these agents are considered specialized agents. Generally speaking, a specialized agent is one trained, in-depth, in a particular area of knowledge.Most businesses have transgressed from your typical call center into contact centers. Contact centers operate essentially the same as a call center but interact with the customer in a variety of ways including, but not limited to: Phone, Mail, Fax, Email, and Internet (via online chat and instant messaging applications). The dynamics of these kinds of call centers has caused an increase in the need for agents to become more diverse in their talents and abilities to handle different types of calls. This has lead to specialized agents becoming general or “cross-trained” agents in which they are trained, broadly, over several areas of knowledge.The purpose of this thesis is to compare specialized agents to cross-trained agents and through the use of simulation, determine which of the two are more efficient and reliable in their ability to service the customer. This thesis has three major components: Simulation, Reliability Analysis, and Comparison. The results indicate that a cross-trained model is more reliable and efficient than a specialized model. Performance metrics common to call center literature, simulation, and Lean reliability systems were used to determine the effectiveness and reliability of the two models.

Conserving biodiversity is suggested to be one of the most important challenges being faced by the global community. The field of conservation biology has been developed to examine the threats that drive species to low abundance, the dynamics of species in low abundance and the methods to rebuild abundance. Typically, assessing these issues requires substantial data inputs; however we are often faced with situations where little information exists. In this thesis, I addressed several key conservation priorities in the endangered Atlantic Whitefish (Coregonus huntsmani), a data poor species, which has been restricted to one watershed for most of the past century. Using molecular genetic markers Atlantic Whitefish were determined to be a distinct and basal species within the genus. Population size was suggested to be low and the incidence of inbreeding high as genetic effective population size was among the lowest of any fish species examined and genetic diversity was 2-6 times lower than regional congeners. Through laboratory experiments environmental threats to the persistence of Atlantic Whitefish were examined. Overall, Atlantic Whitefish were tolerant to a broad range of environmental conditions and were capable of surviving in harsher environments than many other regional species. Furthermore, their persistence in current habitats will likely not be influenced by the assessed environmental conditions. As part of this work, a suite of methods and metrics to compare thermal sensitivity across a range of finfish species were assessed. In order to inform recovery efforts, I developed simulation models to evaluate habitat suitability for translocation of Atlantic Whitefish. As part of this work, I examined the role of incorporating variability in species response, environment and / or life history into simulations. The results showed that the inclusion of multiple sources of variability altered the perception of optimal habitats; however, several watersheds offered suitable translocation habitats. Throughout this thesis I explored novel tools to address some of the key issues facing conservation programs of data poor species. This work is not only applicable to the conservation of Atlantic Whitefish, but also outlines some of the potential tools useful in addressing conservation priorities in other species.