The aim of this thesis is to create simulation model of a conveyor node in the field of sequential stack topcoat paintshop of ŠKODA AUTO a.s. in Mladá Boleslav. Simulation model is create in Plant Simulation. The chapters of this thesis describes the overview of conveying technology used for the transportation of bodies in the solved area, basics of discrete simulation, describe solved area and process of creation a simulation model. Using the simulation model is tested overall throughput of solved area, when changes input parameters. From results of experiments are deducted the conclusions.

This thesis presents an empirical research that aims to explore insight generation in discrete-event simulation (DES) studies. It is often claimed that simulation is useful for generating insights. There is, however, almost no empirical evidence to support this claim. The factors of a simulation intervention that affect the occurrence of insight are not clear. A specific claim is that watching the animated display of a simulation model is more helpful in making better decisions than relying on the statistical outcomes generated from simulation runs; but again, there is very limited evidence to support this. To address this dearth of evidence, two studies are implemented: a quantitative and a qualitative study. In the former, a laboratory-based experimental study is used, where undergraduate students were placed in three separate groups and given a task to solve using a model with only animation, a model with only statistical results, or using no model at all. In the qualitative study, semi-structured interviews with simulation consultants were carried out, where participants were requested to account examples of projects in which clients change their problem understanding and generate more effective ideas. The two separated parts of the study found different types of evidence to support that simulation generates insight. The experimental study suggests that insights are generated more rapidly from statistical results than the use of animation. Research outcomes from the interviews include descriptions of: the phase of a simulation study where insight emerges; the role of different methods applied and means used in discovering and overcoming discontinuity in thinking (for instance, the role of consultant s influence in problem understanding); how some factors of a simulation intervention are associated with the processes of uncovering and overcoming discontinuity in thinking (for example, the role of clients team in the selection of methods used to communicate results); and the role of the model and consultant in generating new ideas. This thesis contributes to the limited existing literature by providing a more in depth understanding of insight in the context of simulation and empirical evidence on the insight-enabling benefits of simulation based on an operational definition. The findings of the study provide new insights into the factors of simulation that support fast and creative problem solving.

This diploma thesis is based on creation of a simulation model of the conveyor bridge between a paint-shop and an assembly hall in the company Škoda Auto, a.s. in Mladá Boleslav. The model was created in the simulation software Plant Simulation on the grounds of an existing model in simulation software SimPro. Analysis of the existing model in software SimPro as well as a system analysis of conveyors used in the respected production section is carried out in the thesis. Results of simulation experiments accomplished with the newly created model follow. These experiments verify the throughput rate for various production programmes. On the grounds of these results a bottleneck analysis of the conveyor system is carried out and arrangements leading to increase in its throughput rate are made.

The aim of work is to present and analyse assessment of the current state and at the same time the proposal of adjustments to the technology or parameters, the introduction of the wire into the drawing machine. The problem arises when the introduction of wire with a diameter of 14 mm from the material CK 67 to the drawbenches Schumag. If we introduce the wire into the drawing machines with two primary beams leads to a buckling of the wire and pack between the drawing die and the boot device. For the introduction of wire are used hydraulic boot collets, which are controlled semi-automatically. In connection with professional studies and on the basis of the calculation, simulation and practical experiment have been identified the conditions allowing the current method of deployment of wire to use.

Goal of this diploma thesis is to create discrete simulation model of a buffer for sorting cars by their color in order to create bigger color blocks in front of upper paint area in paintshop of ŠKODA AUTO a.s. in Mladá Boleslav. Simulation model is created in Plant Simulation software produced by Siemens PLM Software company. Section of this diploma thesis is paid to system analysis of conveyors used in solved area and to suggestion of planned modifications. It is tested by simulation model whether the planned modifications would have positive effect on production characteristic in concern area. Conclusions are deduced from mentioned experiments.

Diploma thesis is dealing with the possibility of use of discrete event simulations in a production planning. The connection of the work measurement and the production planning is described. The thesis describes the modeling methodology, design and realization of the experiment with the model. The production planning part describes the processing of the data generated from the model, which are further used to demonstrate the planning method and optimization of the production plan.

This diploma thesis is based on creation of a simulation model of paint shop in the company ŠKODA AUTO a.s. The model was created in the simulation software Tecnomatix Plant Simulation. It is tested by simulation model whether the planned modifications in a buffer for sorting cars by their color would have positive effect on Perlenkette principle. The Perlenkette principle will help to stabilize supplier processes and reduction of running production times. Conclusions are deduced from carried out simulation experiments.

Fueled by a growing number of applications in science and engineering, the development of stochastic simulation metamodeling methodologies has gained momentum in recent years. A majority of the existing methods, such as stochastic kriging (SK), only focus on efficiently metamodeling the mean response surface implied by a stochastic simulation experiment. As the simulation outputs are stochastic with the simulation variance varying significantly across the design space, suitable methods for variance modeling are required. This thesis takes a dual metamodeling perspective and aims at exploiting the benefits of fitting the mean and variance functions simultaneously for achieving an improved predictive performance. We first explore the effects of replacing the sample variances with various smoothed variance estimates on the performance of SK and propose a dual metamodeling approach to obtain an efficient simulation budget allocation rule. Second, we articulate the links between SK and least-square support vector regression and propose to use a ``dense and shallow'' initial design to facilitate selection of important design points and efficient allocation of the computational budget. Third, we propose a variational Bayesian inference-based Gaussian process (VBGP) metamodeling approach to accommodate the situation where either one or multiple simulation replications are available at every design point. VBGP can fit the mean and variance response surfaces simultaneously, while taking into full account the uncertainty in the heteroscedastic variance. Lastly, we generalize VBGP for handling large-scale heteroscedastic datasets based on the idea of ``transductive combination of GP experts.'' / Doctor of Philosophy / In solving real-world complex engineering problems, it is often helpful to learn the relationship between the decision variables and the response variables to better understand the real system of interest. Directly conducting experiments on the real system can be impossible or impractical, due to the high cost or time involved. Instead, simulation models are often used as a surrogate to model the complex stochastic systems for conducting simulation-based design and analysis. However, even simulation models can be very expensive to run. To alleviate the computational burden, a metamodel is often built based on the outputs of the simulation runs at some selected design points to map the performance response surface as a function of the controllable decision variables, or uncontrollable environmental variables, to approximate the behavior of the original simulation model. There has been a plethora of work in the simulation research community dedicated to studying stochastic simulation metamodeling methodologies suitable for analyzing stochastic simulation experiments in science and engineering. A majority of the existing methods, such as stochastic kriging (SK), have been known as effective metamodeling tool for approximating a mean response surface implied by a stochastic simulation. Despite that SK has been extensively used as an effective metamodeling methodology for stochastic simulations, SK and metamodeling techniques alike still face four methodological barriers: 1) Lack of the study in variance estimates methods; 2) Absence of an efficient experimental design for simultaneous mean and variance metamodeling; 3) Lack of flexibility to accommodate situations where simulation replications are not available; and 4) Lack of scalability. To overcome the aforementioned barriers, this thesis takes a dual metamodeling perspective and aims at exploiting the benefits of fitting the mean and variance functions simultaneously for achieving an improved predictive performance. We first explore the effects of replacing the sample variances with various smoothed variance estimates on the performance of SK and propose a dual metamodeling approach to obtain an efficient simulation budget allocation rule. Second, we articulate the links between SK and least-square support vector regression and propose to use a “dense and shallow” initial design to facilitate selection of important design points and efficient allocation of the computational budget. Third, we propose a variational Bayesian inference-based Gaussian process (VBGP) metamodeling approach to accommodate the situation where either one or multiple simulation replications are available at every design point. VBGP can fit the mean and variance response surfaces simultaneously, while taking into full account the uncertainty in the heteroscedastic variance. Lastly, we generalize VBGP for handling large-scale heteroscedastic datasets based on the idea of “transductive combination of GP experts.”

The growth of serious injuries and fatalities resulting from traffic accidents at intersections is one of the main problems in urban areas. Signal control was proposed as an alternative intersection design on rural roads. There were many reasons behind this, the most outstanding of which was the traffic signals can be used as a cost effective tools for traffic management in urban areas. The LHOVRA technique was intended to improve safety and reduce lost time at signalized intersection along high speed roads. The LHOVRA technique is an isolated traffic control strategy in Sweden which is formed from different concepts. This thesis work is aimed to evaluate the LHOVRA technique with a focus on the O-function. Hence, two different scenarios, one with O-function and one without O-function were implemented in the micro traffic simulation software, VISSIM. VISSIM has been used to simulate the traffic situation of the Gamla Övägen – Albrektsvägen intersection by considering the LHOVRA scenario (with O-function) as well as traditional scenario (without O-function) of the intersection. Field measurements were used as input data for VISSIM simulation. The VISSIM simulation model was calibrated to find a close match between simulated and real data. Finally, a comparison of alternatives was carried out based on traffic performance and traffic safety measurements. The simulation experiment results gained by the comparisons were presented a higher time-to-collision value. The higher time-to-collision value the safer situation is. Both delays and travel time were reduced to primary road traffic.

The content of this diploma thesis is to create a simulation model of the logistics chain of the production area of an industrial plant in order to design the logic control of material flow. Plant Simulation software from the company Siemens PLM Software is used to create the simulation model. The diploma thesis consists of system analysis of the researched area of the production plant. With the help of the simulation model, simulation experiments and evaluation of the obtained results are made. According to the results, the conclusions are drawn.