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The delivery of health care services has been under pressure due to limited funding and increasing demand. This has highlighted the need to increase not only the effectiveness but also the efficiency of health care delivery. Discrete-event simulation has been suggested as an analysis tool in health care management to support the planning of health care resources. The overall purpose of this thesis is to investigate the possibilities and requirements for using discrete-event simulation in analyzing and planning the use of hospital resources. This is achieved by three case studies that focus on improvements in patient flow of emergency patients that require a radiology examination, intensive care unit capacity planning and operating room allocation strategies, respectively. The first case investigates the current stage of digitization and process orientation in hospital care as a prerequisite for efficient process simulation and analysis. The study reveals an emergency-radiology patient flow process that is not very well measured and uncovers disparate information systems storing incompatible and fragmented data. These results indicate that the current degree of process orientation and the current IT infrastructure does not enable efficient use of quantitative process analysis and management tools like simulation. In the second case the possibilities to develop generic hospital unit simulation models by building and validating a generic intensive care unit (ICU) model are explored. The results show that some of the modeling approaches described in literature cannot replicate the actual behavior observed in all studied ICUs. It is important to identify patient groups for different admission priorities, to account for over-utilizations in the model logic, and to discover and properly model dependencies in the input data. The research shows that it is possible to develop a generic ICU simulation model that could realistically describe the performance of different real ICUs in terms of occupancy, coverage and transfers. The value of simulation modeling in health care management is examined in the third case through the development and use of a simulation model for optimal resource allocation and patient flow in a hospital operating department. The goal of the simulation modeling in this case was to identify bottlenecks in the patient flow and to try different alternatives for allocation of operating room capacity in order to increase the utilization of operating room resources. The final model was used to evaluate four different proposed changes to operating room time allocation.

This simulation study was carried out at a company in the automotive industry. In their factory, the company manufactures gearboxes, where the gearbox assembly is one step in the manufacturing process. In the main assembly line, many different gearbox variants are manufactured, each with its own cycle time in the different assembly stations. Due to this variation in cycle times the throughput in the main assembly line can fluctuate depending on which gearbox variants are produced. To maintain a desired throughput a tool for forecasting the throughput would be of great value to the company. Due to the large number of gearbox variants, the company also experiences difficulties understanding if there are stations in the assembly which are recurring bottlenecks. The purpose of this project is to create a tool that can forecast the daily throughput of the main assembly line and identify bottlenecks in the main assembly line. The purpose is also to investigate whether some stations often are bottleneck stations during a certain period. The model evaluation was based on validation of input-output-transformation. A bottleneck analysis based on the active times of the stations was carried out with the best-performing model. The best-performing model version resulted in 68 percent valid forecasts for the 57 historical production days. The forecasts were valid for all historical production days which were Mondays, Tuesdays, Wednesdays, and Thursdays. For Fridays and Sundays, 25 and 0 percent were valid, respectively. A bottleneck analysis was carried out for 37 historical production days where the result showed that, based on the share of active time, a single station was identified as the bottleneck station for all days. The difference between the bottleneck station’s share of active time and other stations’ share of active time was deemed small enough to be within the error margin. Additionally, the queues in the main assembly line indicated that the bottleneck was located within another group of stations. Due to the ambiguity of the results, the conclusion drawn was that the main assembly line did not experience any clear bottleneck station during the 37 historical production days. / <p>Examensarbetet är utfört vid Institutionen för teknik och naturvetenskap (ITN) vid Tekniska fakulteten, Linköpings universitet</p>

The background for this thesis work emanates from a desire to drive the production of the VBG Truck Equipment factory in Vänersborg a step further to catch up with the Industry 4.0 standards. Discrete Event Simulation (DES) is a widely adopted tool within industries to model real-world systems to improve their processes. The concern of bottlenecks is a vital problem in optimizing and improving the efficiency of production processes. Finding and investigating bottlenecks is one of the primary considerations of all manufacturing industries.The company aims to enhance its logistics by using automation in its processes. This work focusses on the Paint shop part of the VBG factory. Thus, the VBG would like to analyse the methods to reduce the bottlenecks and the waiting time in the Paint shop production process. There were no simulation models available to analyse the existing paint shop pro duction flow; therefore, a Discrete Event Simulation (DES) model of the VBG Paint shop was built to investigate the bottlenecks and improvement methods. In this thesis work, the DES model of the existing Paint shop that uses the Last in First Out (LIFO) method was investigated to find the throughput and lead time for the products. In comparison, a First in First Out (FIFO) method was used to get a balanced production flow, and its effects were studied. The company currently uses two shifts in their Paint shop, so the alternate arrangement of shifts using the same number of operators was analysed. The analysis of three shifts with the same number of operators gave more efficiency than the existing one, and three shifts with an increasing number of operators were also compared. The shift arrangements were compared with both the LIFO and FIFO methods, and FIFO provided more throughput and balanced production flow. The main bottleneck was identified in the forklift transport waiting time, so an alternate layout using a power and free conveyor system was developed. This alternate arrangement reduced the bottlenecks and produced an increased output. The alternate layout was also compared with LIFO and FIFO methods; FIFO was the most efficient one. The shift patterns were also analysed, and the three shifts with a 50 percent increase in staff can reduce the stock build-up during the start of the first shift. As of this study, it was identified that the alternate model with FIFO is the most suitable solution for the company, and in the coming years, they intend to implement that. From the experimental results obtained, DES can be chosen as a method to analyse the problems associated with limiting the capacity of production. The DES modelling can be extended to the other processes in the factory and can be used for improving logistics and inventory management. The company production flow can be further advanced by evaluating the changes that can be implemented in the factory with real-time data.

In the domain of operations design and analysis, the ability to see a 3D animation of processes that have been simulated allows for three very important things: 1) The developer of a simulation model can ascertain that there are no errors in the coding (Verification); 2) The experts, field personnel, and decision makers can discover differences between the way they understand the operation and the way the model developer understands it (Validation); and 3) A model can be communicated effectively which, coupled with verification and validation, makes it "credible" and thus used in making decisions. In the case of simulated construction operations, the existent body of knowledge and understanding did not generally permit modeled processes to be accurately visualized in 3D. The purpose of this research was to remedy this situation and find methods of describing animated 3D worlds that show how construction operations modeled using Discrete-Event Simulation were/can be carried out, using simple text statements and references to 3D CAD drawings. The fundamental question the work addressed was how to achieve accurate, dynamic, smooth, and continuous 3D animation of arbitrarily-complex simulated construction processes, based on meager pieces of operational information that can only be communicated when discrete events occur in simulation runs. The end result of this effort is VITASCOPE, an acronym for VIsualizaTion of Simulated Construction OPErations. VITASCOPE is a simple, parametric-text animation description language that is meant to be written out by end-user programmable software such as discrete-event simulation tools. Sequential instructions written in this language allow a computer to create a 3D virtual world that is accurate in time, space, and appearance; and that shows people, machines, and materials interacting as they build constructed facilities. / Ph. D.

A pavement investment and management process has a dynamic structure with cause and effect. Better investment decisions for maintenance will increase the condition of the flexible pavement and will end up with a better level of service. Therefore, better investments decisions on pavement maintenance will increase the economic growth and global competition for the area. However, improper allocation of money and resources would end up with further deteriorations of the facilities. So asset management encourages highway maintenance managers to spend their scarce budget for the maintenance that is really needed. A well-developed pavement management simulation model will allow highway maintenance managers to consider the impact of choosing one maintenance policy alternative versus another through what-if analysis and having informed decisions. Discrete event simulation (DES) is an alternative method of analysis that offers numerous benefits in pavement management. Unlike the models currently in use, a decision support model created by utilizing the DES technique would allow fractionalizing the pavement in smaller proportions and simulating the policies on these smaller segments. Thus, users would see how their decisions would affect these specific segments in the highway network over a period of time. Furthermore, DES technique would better model the multiple resource requirements and dynamic complexity of pavement maintenance processes. The purpose for this research is to create a decision support tool utilizing discrete event simulation technique where the highway maintenance managers can foresee the outcomes of their what-if scenarios on the specific segments and whole of the highway network evaluated. Thus, can be used for both project and network level decision support. The simulation can also be used as a guiding tool on when, where and why resources are needed on needs basis. This research relies on the budget allocation results from the linear optimization model (LOM). This model is a tool that creates the optimized budget allocation scheme for a network fitting to a determined scenario. Thus by integrating the LOM and the DES model, the maintenance managers can acquire an optimized budget allocation for their district and evaluate the results in both network and project selection level. Maintenance managers can obtain the best budget allocation plan without performing the repetitive trial and error approach like the previous decision support tools. There is a vast amount data in many varieties gathered as results from the simulation model. This fact alone demonstrates how powerful the discrete event simulation model is. By the nature of this simulation technique, the resources (highway segments, annual budget) can be traced throughout the simulation and this trait allows the design of the project selection level decision support system. By examining these reports, the maintenance managers can better observe how the scenarios evolve. Thus this tool helps the maintenance managers to have better decisions on the project selection level. The discrete event simulation model established in this research carries the project selection level pavement management from a position where maintenance managers should solely depend on their engineering judgment and experience to a position where maintenance managers can have more effective and justified plans since they can foresee the results of these decisions on the segments that are forming the network. This simulation engine is created with the discrete event simulation language called STROBOSCOPE. The model consists of two parts which work like a lock and key mechanism. The first part of the model is the data feeding mechanism where information from any network is loaded. The second part is the generic engine which can evaluate any road network data it is fed. The purpose of segregating these two components of the model is to allow the user to evaluate any network regardless of length, number of segments or the location. / Master of Science

With increased pressures from governmental and insurance agencies, today's physician devotes less time to patient care and more time to administration. To alleviate this problem, Biological & Popular Culture, Inc. (Biopop) proposed the building of partnerships with healthcare professionals to provide high-quality, cost-effective medical care in a physician network setting. To assist Biopop in evaluating potential operating procedures, a discrete-event simulation model has been constructed. The model is built in an object-oriented, visual manner utilizing the Visual Simulation Environment (VSE). The model examines both internal Biopop operations and external clinic operations. The research presented herein describes the design of the simulation model and details the analysis of the clinical environment. A methodology for determining appropriate staffing and physical resources in a clinical environment is presented. This methodology takes advantage of several simulation-based statistical techniques, including batch means; fractional factorial design; and simultaneous ranking, selection, and multiple comparisons. An explanation of the experimental design is provided and results of the experimentation are presented. Based upon the experimental results, conclusions are drawn and recommendations are made for an appropriate staffing and facility size for a two-physician family practice healthcare clinic. / Master of Science