Manufacturing companies are constantly looking for new, innovative technologies andtools to find out the real constraints and bottlenecks that impede the performance oftheir production systems. There are several approaches and methods that have beendeveloping from decades to overcome these constraints of production processes butthey are not sufficient to pinpoint the exact location and its severity. They also generallyfall short to suggest the way to implement the right actions in the right order, to avoidsub-optimizations and wastes in time and expenses. So according to recent research inusing simulation based optimization, it is believed that some more accurate and efficientmethodology for supporting decision making in production systems development andimprovement is badly needed. SCORE (Simulation-based Constraint Removal) is apromising methodology for identifying and ranking the bottlenecks of productionsystems that utilizes simulation-based multi-objective optimization (SMO), which wasdeveloped by Pehrsson (2013) as a part of his PhD work. The main principle of thisnew methodology is the application of SMO with the objectives to maximize thethroughput and minimize the number of required improvement actions simultaneously.Additionally, by using post-optimality analysis to process the generated optimizationdataset, the precise improvement actions needed to attain a certain level of performanceof the production line are automatically put into a rank order. The main aim of thisproject is therefore to apply this new technique in a real-world context, in order tounderstand how far this technique will support for decision making, by conducting asimulation-based bottleneck analysis in one of the major Volvo group trucks facilities.This is to find out the bottlenecks and optimize it in order to increase the overallproductivity. Three research questions related to the effectiveness and accuracy of themethodology will be answered through this real-world application study. / (STREAMOD)Streamline modeling and Decision support for Facts based Production development

Every production system has its constraints. Ever since Goldratt presented the theory of constraints in the mid 80’s a lot of effort has been made to find the best methods for constraint identification and ways to minimize the constraints in order to gain higher capacity in production. A novel method presented is Simulation-based COnstraint Removal (SCORE). The SCORE method has been proved to be more effective and detailed in the identification and sorting of the constraints when compared with other bottleneck detection methods (Pehrsson 2013). The work in this bachelor’s project has been focused on applying the method to a complex production system in order to further explore the SCORE method’s ability to identify bottlenecks and reveal opportunities to increase the throughput of a production system. NorthStar Battery Company (NSB) wishes to perform a bottleneck analysis and optimization in order to find improvements to increase the throughput with 10%. By using the SCORE method, improvement options with a potential to meet the goals of NSB was identified. It also facilitated for the author to further exploit the possibilities of simulation-based optimization and knowledge extraction through the SCORE method. By building a valid discrete event simulation model of the production line and use it for optimization, followed by a knowledge extraction, it was possible to identify the top three constraints and the level of improvement needed in the constraining operations. The identified improvements could potentially increase the throughput of the production line by 10-15 percent. The project was delimited to exclude the finishing part of the production line and only one battery variant has been included. Through continued work and analysis of the line using the SCORE method it will most likely be possible to even further increase the throughput of the production system and to provide NSB with more knowledge and opportunities to enhance their production effectiveness.

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>

Universal full coverage of birth registration by 2030 is one of the sustainable development targets which itself is of great significance for the accomplishment of many development goals such as poverty eradication, inclusion, as well as improvement of several health factors. Despite the importance of this topic, not much academic attention has been paid to study the problem of birth under-registration from the perspective of development studies. This research studies the issue of birth under-registration through a case study of Iran. The four main questions of this research are the quantitative significance of the problem, the main causes of birth under-registration, the most affected social groups, and the main problematic domain of action, in the context of Iran. By utilizing an abductive content analysis method, this research aims to understand the problem, rather than proposing policy recommendations. This desk study uses secondary sources and almost all of the sources are of qualitative nature. It is not based on any pre-defined theory and therefore does not aim to generalize nor theorize the findings. It, however, is based on available theories for developing the analytical framework. The adopted analytical framework is Bottleneck analysis which is a method designed by UNICEF specifically for the purpose of birth registration programming and policy evaluation. Birth under-registration in Iran - compared to other countries in the region - turned out to be very low. The findings provide information on many good practices regarding birth registration programming and also about several areas in need of improvement in Iran. By applying the analytical framework to the findings, identified disincentives have been categorized in three domains of supply, demand, and enabling environment, and the significance of disincentives in each domain has been assessed. Based on the analysis, it can be concluded that almost all of the main causes of birth registration are of legal nature, especially patriarchal nationality laws. Also, it was found that the main risk groups were children of illegal immigrants, non-nationals, and unregistered parents, and the main problematic domain is found to be the domain of supply.

The medical device industry has for a long time lagged behind other industries in terms of adopting new tools for process improvements. Despite showing promising results from various industries, some more heavily regulated than others, modelling and simulation has not yet gained traction within the medical device industry for performing production improvements. The industry has instead relied upon proven improvement philosophies which are believed to generate a desirable outcome. With the purpose of investigating how this novel tool can be combined with current improvement efforts as well as understanding why it has not yet been accepted, a case study was conducted at the Uppsala facility of Johnson &amp; Johnson Vision. A mixed methodological approach was used, where quantitative and qualitative data was analyzed in combination. Semi-structured interviews and structed observations provided empirical evidence for a thematic analysis and a simulation-based bottleneck analysis. Rather than proving that a simulation-based bottleneck was possible in this particular setting, it was used to confirm its applicability in combination with other tools and improvement philosophies. The study concludes that the issue is not strictly related to the use of modelling and simulation but is rather related to the reactive mind-set which has become a consequence of the rigorous regulatory landscape that the industry is encompassed by.

Companies are constantly seeking new ways to increase their efficiency and flexibility to be able to meet the market demand, industry 4.0 has provided companies with new tools that enables them to better track the performance of a process and more easily optimise it. In a high mix and low volume manufacturing process a lot of inefficiencies are prone to occur due to the high variety. A simulation can be a very beneficial tool to use in the optimisation of a manufacturing process. In a simulation a digital twin of the physical process is constructed to replicate the real-world results, the simulation can then be used to test how changes to the process affects the desired performance objectives. The purpose of this study was to use a simulation to optimise the process by increasing output and reduce lead time as well as increase the visual presentation of the process. The purpose was fulfilled by a review of literature on the subject, interviews, observations and a document study before a simulation model and value stream map was constructed. The bottleneck analysis and the value stream map highlighted a few inefficiencies in the process that was solved by implementing a few solutions that would improve the balance of the process and increase output and decrease lead time. A visual presentation tool was also developed to calculate the expected lead time for a new order and show how the flow of orders would develop in the near future.

Already in its Education Strategy, adopted by the Executive Board in 2007, UNICEF fully obligates to the international commitment to universal education and defines its contribution to national efforts to fulfil children’s right to education. In September 2010, UNICEF further published a special report on a study showing that an equity-focused approach to child survival and development is the most practical and cost-effective way of meeting the health MDGs for children. For the modelling process of the research a simulation was run employing the Marginal Budgeting for Bottlenecks (MBB) model, jointly developed by the World Bank and UNICEF. This model has been widely used in international public health research to design and test development strategies. In its consistency with the human-right based approach, the MBB model addresses bottlenecks in the capacity of duty-bearers to fulfil human-rights as well as barriers of the capacity of right-holders to claim their rights. Using the MBB model, policymakers and researchers can simulate varying configurations of service delivery modes to expand access of coverage and measures to encourage usage. For each strategy, the model generates the predicted impact on intervention coverage and outcomes, overall cost and cost-effectiveness. UNICEF’s global refocus on equity and the most disadvantaged children makes it necessary to introduce improved planning and monitoring instruments. In this context, the MBB model is used as a budgeting and simulation tool for UNICEF interventions in health and nutrition. UNICEF aims to use harmonized tools across different sectors to reduce transaction costs and to improve comparison and sharing of lessons learned between the different sectors. However, it is also important to adapt and develop instruments based on the diverse needs of different sectors to ensure best results. Therefore, the main purpose of this research is to find an answer to following question: Can, and if so, how can the Marginal Budgeting for Bottlenecks model, developed for the health sector, be adapted for planning, costing and budgeting allocations in the education sector? An adapted Marginal Budgeting for Bottleneck model for education could be applied for a comprehensive sector analysis, comparing intervention alternatives and setting policy goals and strategies. It could further be used to monitor the implementation of major sector reforms with regard to the comparison of potential versus actual impact of interventions on learning achievements. Applying two production functions, the MBB model applies the basic principle of Cost-Effectiveness Analysis, comparing the costs of education interventions with the corresponding expected impact on increased service coverage. However, detailed inputs, outputs, outcomes and impacts and the corresponding correlations would need to be defined for an Service Production Function (inputoutput) and an Education Production Function (output-outcome/impact). Further, a selection of globally proved remedial actions to overcome sector bottlenecks need to be specified. Education interventions largely depend on the country context and different countries and regions apply different remedial actions. Since the relationship of input and impact is not as linear as the illness-treatment relationship in health, international research and comparison of effective interventions would need to be conducted. The MBB model is applying service coverage determinants of both, supply and demand side. Therefore the approach could be a helpful instrument in the context of the Human Rights-based Approach as used within programming of the United Nations and UNICEF. However, applying further analysis on humanitarian aspects of programming always depends on the availability of disaggregated information. Based on the outline of the Service Coverage Concept and the Marginal Budgeting for Bottlenecks model and the conceptual adaptation of the MBB model for its use in education, following suggestions can be made for the Service Delivery Modes and Service Coverage Determinants: Overall, an MBB model in education could have added value for education planning, budgeting and impact simulation. However, it has to be considered that applying the model requires extensive data input for all six Service Coverage Determinants for each of the five Service Deliver Modes. Although, the MBB model could be adjusted to only cover a certain sub-sector within Quality Education for All. Five Service Delivery Modes Ten Sub-Packages 1. Pre-School Education 1.1 Public Early Childhood Education 1.2 Private Early Childhood Education 2. Formal Basic Education 2.1 Public Formal Basic Education 2.2 Private Basic Education 3. Non-Formal Basic Education 3.1 Public Non-Formal Basic Education 3.2 Private Non-Formal Basic Education 4. (Lower) Secondary Education 4.1 Public Secondary Education 4.2 Private Secondary Education 5. Adult Literacy, Continuing Education 5.1 Youth and Adult Literacy Interventions 5.2 Continuing Education Six Service Coverage Determinants Indicator Supply side 1. Availability of essential commodities Pupil-Classroom Ratio by grade Pupil-Textbook Ratio 2. Availability of human resources Pupil-Teacher Ratio (or Pupilqualified Teacher Ratio) by grade 3. Geographic and financial accessibility School-Distance School-Costs by grade Demand side 4. Initial Utilization Net-Enrolment Ratio (or Gross- Enrolment Ratio) by grade 5. Continuous Utilization Survival Rate by grade 6. Effective Utilization Graduation Ratio Graduation Test Scores Overall, an MBB model in education could have added value for education planning, budgeting and impact simulation. However, it has to be considered that applying the model requires extensive data input for all six Service Coverage Determinants for each of the five Service Deliver Modes. Although, the MBB model could be adjusted to only cover a certain sub-sector within Quality Education for All.

Process mining (PM) has already found its place in analyzing and visualizing business processes across different sectors such as banking, healthcare, insurance, and logistics. However, its application is very limited in production systems. Production systems are very complex and dynamic, hindering the accurate capture of different process chain events. Generating the event log data out of the recorded events requires a proper understanding of the processes. The results of the bottleneck analysis can help the production experts to optimize the process. This study analyzes three to four PM tools to select an appropriate tool that can perform bottleneck analysis. The initial research will focus on various features of the PM tools such as modeling support, user friendliness, flexibility, stability, animation support, and BPMN modeling support. The feature analysis uses the event-log data generated from simulating the process model created in a Simulation-based Optimization tool FACTS Analyzer. Some PM tools can generate the BPMN model from the process model; animation support and modeling support features are vital for the bottleneck analysis. The PM tool's ability to create the process model automatically from the event log data can help save time involved in data collection through a physical visit to the site, conducting interviews, observations, etc. In contrast, the bottleneck analysis used simulated event log data and an event log generated from a real-world production system. The study focuses on finding whether PM can support the bottleneck analysis of the real-world production systems and find the appropriate PM tool available in the market for the same application. The use of process mining tools in the bottleneck analysis requires human intervention in identifying the bottlenecks in the process as the PM tools are incapable of recognizing them on their own. But, appropriate use of the PM tools in the bottleneck analysis can help save a considerable amount of time in manually building the simulation model. Performing iterative optimization could lead to socio, economic, and environmental sustainability as it helps avoid wastages in time, material, and energy.

In low-income countries where maternal and child mortality remains high, there is limited use of context-specific evidence for decision making and prioritization of interventions in the planning process at the sub-national level, such as the district level. Knowledge on the utility of tools and interventions to promote use of district-specific evidence in the planning process is limited, yet it could contribute to the prioritization of high-impact interventions for women and children. This thesis aims to investigate, in the planning process, the use of district-specific evidence to identify gaps in service delivery in the district health system in Uganda in order to contribute to improving health services for women and children. Study I evaluated the use of the modified Tanahashi model to identify bottlenecks for service delivery of maternal and newborn interventions. Study II and III used qualitative methods to document the experiences of district managers in adopting tools to facilitate the utilization of district-specific evidence, and the barriers and enablers to the use of these tools in the planning process. Study IV used qualitative methods, and analysis of district annual health work plans and reports. District managers were able to adopt tools for the utilization of district-specific evidence in the planning process. Governance and leadership were a major influence on the use of district-specific evidence. Limited decision space and fiscal space, and limited financial resources, and inadequate routine health information systems were also barriers to the utilization of district-specific evidence. Use of district-specific evidence in the planning process is not an end in itself but part of a process to improve the prioritization of interventions for women and children. In order to prioritize high impact interventions at the district level, a multifaceted approach needs to be taken that not only focuses on use of evidence, but also focuses on broader health system aspects like governance and leadership, the decision and fiscal space available to the district managers, limited resources, and inadequate routine health information systems.

The world is constantly changing and evolving faster and faster. In the industry, it is important to constantly evolve to adapt to the market and maintain competitiveness. The ongoing fourth industrial revolution is urging companies to increase digitalization and automate production. Simulation is a tool that can be used to develop, test and control production. In the pharmaceutical industry, the manufacturing and the product are required to ensure good quality. At the same time, the demand of pharmaceuticals and medical devices is high. With simulation, production systems can be evaluated, developed and improved a safer and more efficient way.  The purpose of the study is to investigate, through a simulation, whether the mass-producing pharmaceutical industry can utilize Discrete Event Simulation to improve production planning and control. The purpose was partly fulfilled by a situation assessment, which together with a literature study, was used to find out what data is required to establish a simulation model. Finally, a simulation model was established, representative of reality and a bottleneck analysis was performed as part of the validation. The study is based on a case study in which qualitative and quantitative methods have been used to answer the research questions. The method is designed to be able to be carried out remotely, since it has not been possible to attend the company where the study was conducted. Two different simulation models, which differ in detail level, are presented in the results of the study. The more detailed level model could be used as a basis for improvement work. The simplified model reflects reality thoroughly and can be used for production planning and production capacity estimations. The bottleneck analysis shows which process is the bottleneck and corresponds to the company's perception. The largest bottleneck was assembly and blister packing. The most important suggestion of improvement was increase of the process availability in the blister packing, which increases production throughput with 6 percent and reduces lead time with 1,5 days. To utilize the detailed simulation model, data collection at sub-process level is also proposed. / Världen förändras hela tiden och utvecklas snabbare och snabbare. Inom industrin gäller det att ständigt utvecklas för att kunna anpassa sig till marknaden och bibehålla konkurrenskraft. Den pågående fjärde industriella revolutionen uppmanar företag att öka digitalisering och automatisera produktionen. Simulering är ett verktyg som kan användas för att utveckla, testa och kontrollera produktionen. I läkemedelsbranschen kräver kunder att tillverkningen och produkten tillser god kvalitet. Samtidigt är efterfrågan stor på läkemedel och medicintekniska produkter. Med simulering kan produktionssystem utvecklas på ett säkrare och mer effektivt sätt.   Syftet med studien är att genom en simulering undersöka om massproducerande läkemedelsindustrin kan utnyttja händelsestyrd simulering för att förbättra produktionsplanering och styrning. Syftet uppfylldes delvis genom en nulägesanalys, som tillsammans med en litteraturstudie användes för att ta reda på vilken data som krävs för att upprätta en simuleringsmodell. Avslutningsvis upprättades en simuleringsmodell, representativ till verkligheten och en flaskhalsanalys genomfördes som del av valideringen. Studien grundar sig i en fallstudie där kvalitativa och kvantitativa metoder har använts för att besvara frågeställningarna. Metoden är utformad för att kunna utföras på distans då det ej har varit möjligt att närvara på företaget där studien är genomförd.   Två olika simuleringsmodeller, som skiljer sig i detaljnivå, presenteras i resultatet av studien. Den mer detaljerade skulle kunna användas som ett underlag för förbättringsarbete. Den förenklade modellen återspeglar produktionen översiktligt och kan användas för produktionsplanering. Flaskhalsaanalysen påvisar vilken process som är flaskhalsen och stämmer väl överens med företagets uppfattning. Montering och blistring utger sig som den största flaskhalsen och förbättringsförslag kopplat till detta är främst en ökad tillgänglighet hos processen blistring som ökar produktionstakten med 6 procentenheter och sänker produktionsledtiden med 1,5 dagar. För att kunna utnyttja den detaljerade simuleringsmodellen föreslås vidare datainsamling på delprocessnivå.