abstract: The success of genetically-modified T-cells in treating hematological malignancies has accelerated the research timeline for Chimeric Antigen Receptor-T (CAR-T) cell therapy. Since there are only two approved products (Kymriah and Yescarta), the process knowledge is limited. This leads to a low efficiency at manufacturing stage with serious challenges corresponding to high cost and scalability. In addition, the individualized nature of the therapy limits inventory and creates a high risk of product loss due to supply chain failure. The sector needs a new manufacturing paradigm capable of quickly responding to individualized demands while considering complex system dynamics. The research formulates the problem of Chimeric Antigen Receptor-T (CAR-T) manufacturing design, understanding the performance for large scale production of personalized therapies. The solution looks to develop a simulation environment for bio-manufacturing systems with single-use equipment. The result is BioMan: a discrete-event simulation model that considers the role of therapy's individualized nature, type of processing and quality-management policies on process yield and time, while dealing with the available resource constraints simultaneously. The tool will be useful to understand the impact of varying factor inputs on Chimeric Antigen Receptor-T (CAR-T) cell manufacturing and will eventually facilitate the decision-maker to finalize the right strategies achieving better processing, high resource utilization, and less failure rates. / Dissertation/Thesis / Masters Thesis Industrial Engineering 2020

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.

In this paper, we introduce a framework for the adaptive control of universal mobile telecommunications system (UMTS) networks in order to improve bandwidth utilization of the radio channels. The key contribution of the paper constitutes the introduction of a performance management information base for dynamically adjusting the packet scheduler and admission controller. Thus, the adaptive control framework closes the loop between network operation and network control. Furthermore, the adaptive control framework can effectively deal with the different time scales of packet scheduling and admission control. Moreover, we present a traffic model for non-real-time UMTS traffic based on measured trace data. The analysis and scaling process of the measured trace data with respect to different UMTS bandwidth classes constitutes the basic concept of this traffic characterization. Using this traffic model and simulation on the IP level, the gain of employing the adaptive control framework is illustrated by performance curves for various quality of service measures.

In the pursuit of excellence industrial companies are increasingly employing production system development to rationalize their processes. One such approach that has been employed to great extend in the automotive industry is that of introducing modularity to the product design. This shift from integral products to modular ones, is associated with a higher level of standardization of parts and processes. However, researchers are still mapping out this correlation. As the connection between modularity and the recorded effects is still up for discussion, still fewer studies have been made on how to most effectively adopt modularisation. This thesis is therefore a research that explores the relationship between product design and production from a perspective of production system development. It is a collaborative study conducted with a manufacturer of industrial robots that is preparing to transition from an integral product design to a modular one. The case study utilizes discrete – event simulation to model the impact of such a changeover in the production system. Not resulting in a step-by-step how-to guide, the study nevertheless shows that discrete – event simulation can prove to be a valuable asset both when analysing what-if scenarios and when pinpointing pre-emptive measures in order to mitigate any negative disruption such a transition might initially bring.

Discrete event simulation is the most suitable type of simulation for analyzing a complex system where changes happen at discrete time instants. Discrete event simulation is a major experimental methodology in several scientific and engineering domains. Unfortunately, a conventional discrete event simulator cannot meet with increasing demands of computational or the structural complexities of modern systems such as peer-to-peer (P2P) systems; therefore parallel discrete event simulation has been a focus of researchers for several decades. Unfortunately, no simulator is regarded as a standard which can satisfy the demands of all kinds of applications. Thus while given a simulator yields good performance for a specific kind of applications, it may failed to be efficient for other kinds of applications. Furthermore, although technological advancements have been made in the multi-core computing hardware, none of the mainstream P2P discrete event simulators is designed to support parallel simulation that exploits multi-core architectures. The proposed HydraNetSim parallel discrete event simulator (PDES) is a step toward addressing these issues. Developing a simulator which can support very large numbers of nodes to realize a massive P2P system, and can also execute in parallel is a non-trivial task. The literature review in this thesis gives a broad overview of prevailing approaches to dealing with the tricky problems of simulating a massive, large, and rapidly changing system, and provides a foundation for adopting a suitable architecture for developing a PDES. HydraNetSim is a discrete event simulator which allows parallel simulation and exploits the capabilities of parallelization of modern computing hardware. It is based on a novel master/slave paradigm. It divides the simulation model into a number of specific slaves (a cluster of processes) considering the number of cores provided by the underlying computing hardware. Each slave can be assigned to a specific CPU on a different core. Synchronization of the slaves is achieved by proposing a variant of the classic Null-Message Algorithm (NMA) with a focus on keeping the synchronization overhead as low as possible. Furthermore, HydraNetSim provides log information for debugging purposes and introduces a new mechanism of gathering and writing simulation results to a database. The experimental results show that the sequential counterpart of HydraNetSim (SDES) takes 41.6% more time than HydraNetSim-2Slave and 23.6% than HydraNetSim-3Slave. HydraNetSim-2Slave is 1.42 times faster, consumes 1.18 times more memory, and supports 2.02 times more nodes than a sequential discrete event simulator (SDES). Whereas, HydraNetSim-3Slave executes 1.24 times faster, consumes 2.08 times more memory, and supports 3.04 times more nodes than SDES. The scaling factor of HydraNetSim is ⌈(β-1)*102.04%⌉ of the maximum numbered of nodes supported by SDES; where β is the number of slaves. / Diskret händelsesimulering är den mest passande typen av simulering för att analysera ett komplext system där förändringar sker i diskreta tidpunkter. Diskret händelsesimulering är en stor experimentell metod i flera vetenskapliga och tekniska områden. Tyvärr kan en konventionell diskret händelse simulator uppfyller inte med ökande krav på beräkningsprogram eller strukturella komplexiteten av moderna system som peer-to-peer (P2P) system, och därför parallellt diskret händelse simulering har varit ett fokus för forskare under flera årtionde. Tyvärr ingen simulator ansåg som en standard som kan uppfylla kraven på alla typer av applikationer. Så samtidigt få en simulator ger bra prestanda för en specifik typ av applikationer kan det inte vara effektivt för andra typer av applikationer. Även om tekniska framsteget har gjorts i multi-core datorhårdvara, är ingen av de vanliga P2P händelsestyrd simulatorer för att stödja parallella simulering som utnyttjar flera kärnor arkitekturer. Den föreslagna HydraNetSim parallella diskret händelse simulator (PDES) är ett steg mot att fokusera på dessa frågor. Utveckla en simulator som kan stödja ett mycket stort antal noder för att realisera en massiv P2P-system, och kan även utföra parallellt är en icke-trivial uppdrag. Litteraturstudien i denna tesen ger en bred översikt över aktuell metoder för att hantera de svåra problem som simulerar en massiv, stor och snabbt ändra system och ger en grund för att adoptera en passande struktur för att utveckla ett PDES. HydraNetSim är en diskret händelse simulator som gör det möjligt parallellt simulering och utnyttjar funktionerna i parallellisering av modern datorhårdvara. Det är baserat på en ny master / slav paradigm. Den delar simuleringsmodellen i ett antal specifika slavar (ett kluster av processer) med tanke på antalet kärnor som tillhandahålls av den underliggande datorhårdvara. Varje slav kan tilldelas en specifik CPU på en annan kärna. Synkronisering av slavarna uppnås genom att föreslå en variant av det klassiska Null-Message Algorithm (NMA) med fokus på att hålla simuleringen overhead så lågt som möjligt. Dessutom ger HydraNetSim log information för felsökning ändamål och inför en ny mekanism för att samla in och skriva simuleringar resultat till en databas. De experimentella resultaten visar att den sekventiella motsvarigheten till HydraNetSim (SDES) tar 41,6% mer tid än HydraNetSim-2Slave och 23,6% mindre än HydraNetSim-3Slave. HydraNetSim-2Slave är 1,42 gånger snabbare, förbrukar 1,18 gånger mer minne, och stöder 2.02 gånger fler noder än en sekventiell händelsestyrd simulator (SDES). I HydraNetSim-3Slave kör 1.24 gånger snabbare, förbrukar 2,08 gånger mer minne, och stöder 3,04 gånger fler noder än SDES. Skalfaktorn av HydraNetSim är ⌈(β-1)*102.04%⌉ av den maximala numrerade noder som stöds av SDES; där β är antalet slavar.

The use of simulation has been said to be a useful tool to analyze manufacturing systems, Discrete Event Simulation - DES for instance under the occurrence of different events. Information management in Manufacturing Systems is an important issue and so it is insimulation studies because some of the difficulties in building, reusing and integratingsimulation models with other applications used in manufacturing systems are related withthe data. In this context different efforts have been made to facilitate the use of simulationand overcome interoperability problems through improving the information management,one of this is the Core Manufacturing Simulation Data Information Model - CMSDIMdeveloped by The National Institute of Standards and Technology - NIST. The objective of this thesis is to contribute to the use of the CMSDIM in ExtendSim V8. A method to import databases structured based on the CMSDIM into the Simulation softwareExtendSim V8 is developed and applied in a case study in a production line of SCANIA.

The steel production is a highly capital and energy intensive industry that due to recent raw materials’ price increase and lowered demand, it has been squeezed and forced to look more deeply on how to add value to the customer at lower operative costs. The project was carried out on site at the ArcelorMittal’s millin Esch-Belval, Luxembourg which comprises an integrated melt shop, continuous casting plant and the rolling mill with the objectives of proposing optimization rules for the cold sector of the rolling mill and to analyze the impact of the future truckbay shipment area. The course of action followed was to draw a Value Stream Map (VSM) in order to understand the plants’ current status and serve as a roadmap to build a discrete event simulation model that after its validation, served as a support tool to analyze what-if scenarios. Similarly, a current status analysis of the  shipment/stock area was conducted collecting statistics about potential truckshipments and finally proposing a series of recommendations for its operation. The main proposed solutions to optimize the rolling mill’s cold sector were:(a) Integer programming model to globally optimize the scrap level when cutting the mother beams to customer size beams. (b) Updating pacemaker parameters and (c) Local process time improvements. Concerning the future truck loading, the simulation model was used as a support tool to dimension the transition area between the cranes’ and forklift operations resulting in a 6-9 bundles buffer capacity. Additionally, the current length-based storage policy was found to have competitive objectives so a turnover class-based storage policy is proposed with A, B, C classes which should provide an improved organization of the stock and travel distance of the cranes. The evaluation of the cranes’ performance remains an issue since there are currently no objective measures like, for instance, travelled distance. Optical measuring devices are suggested as one option to have a performance indicator that would help further investigate root cause problems in the shipping/stock area.

Purpose:The primary purpose of the current thesis is to develop a virtual model using discrete event simulation (DES), which aims at supporting the decision-making process regarding automation solution proposals for SMEs.  Method:The research approach is positivism, and it considers quantitative and empirical information. A literature search is conducted to generate a base for obtaining the theory required for the current report to answer the research questions. This search included the trace of relevant and reviewed topics regarding automation, discrete event simulation, and production lines. Then, a scenario simulation is designed and studied based on empiric knowledge and how automation would affect it, followed by a collection of information from the simulation iterations. Findings& Analysis: Two scenarios are presented. One with a fully manually operated assembly line consisting of only human operators and a second scenario, a semi-automated assembly line that includes some robots in specific areas doing specific operations. The two scenarios are simulated to check to what extend the KPI’s and parameters improved between each scenario. The experiment result concludes that by introducing automation elements in the production line, there is an increase in the overall efficiency, throughput rate, and a considerable gap against humans in WIP. Conclusions and recommendations: The results obtained from the experimentation in discrete event simulation software and study from previous research show that discrete event simulation has a significant contribution when considering a decision-making tool's role. Since it allows to understand and study the specific scenario by imitation and try different solutions in the same production system, it also allows studying several indicators from the scenarios to be checked to what extent they could be improved. Delimitations: The current thesis includes several delimitations. First, it focuses only on an operational level. Also, this study consists of a specific type of product with many variants, and finally, there are only two scenarios studied: a fully manual scenario and a semi-automated scenario with the presence of robots.

There is no doubt Medical Devices have a crucial role in hospital processes such as surgeries and therapeutic procedures. Medical devices available in hospitals are of two types; reusable and non-resalable medical devices. Reusable medical devices are washed and sterilized after each use. The process of sterilizing medical devices is performed in the sterilization department. Each medical device travels through a cycle each time it is utilized. It is explicit that any part of the sterilization cycle that delays the process can cause serious problems for hospitals’ performance. The washing step of the sterilization process has been a bottleneck in the system. Thus, optimization approaches can be highly advantageous to improve this bottleneck. The data of the medical devices are usually unknown prior to the scheduling process since the finishing time of the surgeries are not known in advance. Thus, there is no information available on the ready time of medical devices to be sterilized. Due to this factor, to develop applicable solutions, it is critical to consider this problem as an online problem and develop online scheduling methods. In this thesis, we take advantage of mathematical programming and heuristic algorithms to solve both the offline and online settings of the problem. We model the washing step of the sterilization cycle as a scheduling problem. Batch scheduling and bin packing, two well-known optimization approaches, are used for this purpose. Medical devices are batched together first and then scheduled on machines to reduce the total washing time of all medical devices. First, a mathematical model for the offline problem is provided and tested to solve the problem. Then a series of heuristic algorithms are developed using the batch scheduling approach for solving both offline and online problems. Moreover, a special case with divisible job sizes and equal release dates is studied. It was proved that for the strongly divisible sequence the First Fit Increasing algorithm finds the optimal solution, also for the weakly divisible sequence a Dynamic Programming algorithm is developed. Finally, we couple optimization with simulation to test the impact of the optimization of the washing step on the entire sterilization system. Moreover, since the next step of the sterilization cycle, the sterilization step, is very similar to the washing step, we also implement the developed heuristics in this step to evaluate its performance and improve it further. The results show that as long as the washing step is optimized it does not differ which algorithm is used in the sterilization step, thus, the optimization of this step is not necessary.

The Southern Swedish hospital region is the home of nearly 2 million people, inwhich 5,684 individuals were diagnosed by stroke during 2016, according tostatistics from the hospitals in the region. With this large number ofstroke-diagnosed patients across the region, an effective stroke transport policy isinevitably important to provide fast treatment for these patients.In this thesis, we developed an agent-based simulation model for evaluating theperformance of transport logistics policies. We followed the Design ScienceResearch methodology in order to design and develop the model. Using the model,we assessed two transport logistics policies for the Southern Swedish hospitalregion. We used a synthetic set of stroke patients, which we generated using Montecarlo simulation, for the processes of developing the model and assessing our twostroke transport logistics policies.We argue that the assessment of transport logistics policies is important for theability to improve the planning process, for example, when choosing hospital fordiagnosis of patients showing stroke symptoms. The optimization of the strokelogistics process aims to ensure the quality and operational efficiency of the hospitalsector as well as to increase the chance of survival of stroke patients.