Stoneridge, Inc. is an independent designer and manufacturer of highly engineered electrical and electronic components, modules and systems principally for the automotive, commercial vehicle, motorcycle, agricultural and off-highway vehicle markets. A subsidiary of Stoneridge, Inc. is the company Stoneridge Electronics. They specialise in instrument clusters and tachographs which are manufactured in high quantityin their production plant in Örebro, Sweden. This master thesis focuses on the production line of an instrument cluster called Angela. In close collaboration with Stoneridge Electronics, the goal was to find ways to improve the output of the Angela line by at least 10% compared to the three best months in terms of output from the year before. The Angela line was analyzed thoroughly and from different perspectives using lean tools such as value stream mapping, spaghetti diagram and continuous improvement. Finally, the simulation software ExtendSim was used in order to simulate and analyse different suggestions. The results show that various steps can be taken to improve the efficiency and output of the manufacturing line by as much as 16.3%. Due to the fact that other production lines within the production are similar to the one that the project was carried out on, the project results could be applicable for the other lines as well. / Stoneridge, Inc. är en oberoende designer och tillverkare av högteknologiska elektriska och elektroniska komponenter, moduler och system huvudsakligen för fordonsmarknaderna. Ett dotterbolag till Stoneridge, Inc. är företaget Stoneridge Electronics. De är specialiserade på instrument kluster och färdskrivare som tillverkas i produktionsanläggning i Örebro. Denna examensarbete fokuserar på produktionslinje av ett instrumentkluster som heter Angela. I nära samarbete med Stoneridge Electronics,målet var att hitta sätt att förbättra produktionen av Angela linje med minst 10 % jämförtmed de tre bästa månaderna när det gäller produktion från året innan. Angela-linjen analyserades grundligt och från olika perspektiv med lean verktyg som värdeflödesanalys, spaghetti diagram och kontinuerlig förbättring. Slutligen användes simuleringsprogrammet ExtendSim för att simulera och analysera olika förslag. Resultaten visar att olika steg kan vidtas för att förbättra effektiviteten och produktionen av produktionslinjen med så mycket som 16.3%. På grund av att andra produktionslinjer inom produktionen liknar den som projektet genomfördes på, kan projektresultaten vara tillämpliga för andra linjer också.

Inom tillverkande industrier är kännedom om produktionens kapacitet en grundläggande faktor vid bedömning av mängden produkter som kan tillverkas inom en bestämd tidsperiod. Produktionskapacitet utgör därmed grunden för vad en verksamhet kan utlova sin kund gällande leverans av produkt. Om en förväntad produktionskapacitet inte kan uppnås krävs förändringar som säkerställer att önskad kapacitet erhålls för att bemöta kundens efterfrågan. Det här examensarbetet är genomfört på transportstillverkningsföretaget Scania med anledning av att deras förväntade produktionskapacitet inte fullt ut uppnås i en del av sin produktion. Idag använder Scanias avdelning DX Transmission sig av Microsoft Excel vid beräkning av kapacitet vilket genererar högre förväntad kapacitet än vad som uppnås i verkligheten. I detta arbete har därmed möjligheten att använda simuleringar för att se verklig produktionskapacitet undersökts. Genom att kartlägga Scanias produktionsflöde för kugghjul, förenkla verkligheten och sammanställa indata har en simuleringsmodell i programvaran ExtendSim 10.0.7 skapats. Därefter genomfördes en analys av hur simuleringsmodellen kan användas för att se produktionskapacitet. Arbetet mynnade ut i ett förslag av hur en simuleringsmodell kan utformas för att spegla verklig produktionskapacitet, vilken typ av indata samt förenklingar som krävs för att åstadkomma detta. Simuleringsmodellen kan användas för att bedöma hur flödets processer samverkar i form av att se hur samtliga produktionslinor nyttjas samt materialköer som uppstår längs med flödet. Detta ger en visuell bild av produktionen över tid och vilken kapacitet som erhålls. Vid fortsatt arbete med simuleringsmodellen bör vissa indata adderas samt uppdateras för att säkerställa att simuleringsresultaten blir än mer likt verkligheten. Därefter är det möjligt att undersöka var flaskhalsar uppstår och vilka åtgärder som bör införas för att uppnå den önskade kapaciteten. / Capacity within manufacturing determines the amount of output which can be produced for a set period. Therefore, production capacity is needed to be known within a business in order to know what can be promised to its customers regarding deliveries of the product. If the company are not able to reach the expected capacity, then changes must occur to ensure the customer demand.  This bachelor thesis has been done at Scania because of their expected production capacity are not fully achieved in some parts of their production. The department DX Transmission at Scania uses Microsoft Excel when calculating capacity, which results in calculations with a higher capacity than the production later achieves. The possibility of using simulation as a tool to see the true capacity has been examined in this project. By mapping the production flow of gears, making simplifications of the reality, and collecting inputs, a simulation model has been created by using the software ExtendSim 10.0.7. An analysis of how the simulation model can be used in the context of capacity were then made.  The result of the project shows how a simulation model can be designed and how DX Transmission can use the model to see how different processes interacts. Material queues and loading of production lines are two aspects that can be examined. Suggestions of what continuous work to be done are given, which includes updating and adding inputs to the simulation model to make the model even more alike the reality. If this will be made, then it would be possible to find bottle necks and modify the production to achieve the required capacity.

Despite the critical importance of project completion timeliness, management practices in place today remain inadequate for addressing the persistent problem of project completion tardiness. Uncertainty has been identified as a contributing factor in late projects. This uncertainty resides in activity duration estimates, unplanned upsetting events, and the potential unavailability of critical resources. This research developed a comprehensive simulation based methodology for conducting quantitative project completion-time risk assessments. The methodology enables project stakeholders to visualize uncertainty or risk, i.e. the likelihood of their project completing late and the magnitude of the lateness, by providing them with a completion time distribution function of their projects. Discrete event simulation is used to determine a project's completion distribution function. The project simulation is populated with both deterministic and stochastic elements. Deterministic inputs include planned activities and resource requirements. Stochastic inputs include activity duration growth distributions, probabilities for unplanned upsetting events, and other dynamic constraints upon project activities. Stochastic inputs are based upon past data from similar projects. The time for an entity to complete the simulation network, subject to both the deterministic and stochastic factors, represents the time to complete the project. Multiple replications of the simulation are run to create the completion distribution function. The methodology was demonstrated to be effective for the on-going project to assemble the International Space Station. Approximately $500 million per month is being spent on this project, which is scheduled to complete by 2010. Project stakeholders participated in determining and managing completion distribution functions. The first result was improved project completion risk awareness. Secondly, mitigation options were analyzed to improve project completion performance and reduce total project cost.

Discrete Events Simulation (DES) is a powerful tool of modeling and analysis used in different disciplines. DES models require data in order to determine the different parameters that drive the simulations. The literature about DES input data management indicates that the preparation of necessary input data is often a highly manual process, which causes inefficiencies, significant time consumption and a negative user experience. The focus of this research investigation is addressing the manual data collection and processing (MDCAP) problem prevalent in DES projects. This research investigation presents an integrated framework to solve the MDCAP problem by classifying the data needed for DES projects into three generic classes. Such classification permits automating and streamlining the preparation of the data, allowing DES modelers to collect, update, visualize, fit, validate, tally and test data in real-time, by performing intuitive actions. In addition to the proposed theoretical framework, this project introduces an innovative user interface that was programmed based on the ideas of the proposed framework. The interface is called DESI, which stands for Discrete Event Simulation Inputs. The proposed integrated framework to automate DES input data preparation was evaluated against benchmark measures presented in the literature in order to show its positive impact in DES input data management. This research investigation demonstrates that the proposed framework, instantiated by the DESI interface, addresses current gaps in the field, reduces the time devoted to input data management within DES projects and advances the state-of-the-art in DES input data management automation.

Although there have been oscillations in airship interest since their use in the early 1900s, technological advancements and the need for more flexible and environmentally friendly transportation modes have caused a stream of study and surge in airship development in recent years. For companies and governments to understand how airships can be incorporated into their fleets to fulfil new or existing mission types, system design space exploration is an important step in understanding airships, their uses, and their design parameters. A decision support system (DSS), Design Exploration of Lighter-Than-Air Systems (DELTAS), was developed to help stakeholders with this task. DELTAS allows users to design airships and missions to determine how a design will perform in the scenario. Simulations can also be run for a given mission to find the Pareto-optimal designs for user-defined ranges of high-level airship design parameters. A case study is provided that demonstrates how DELTAS can be used to explore the airship design space for three specified missions. These three mission case studies show how design of experiments is important to more thoroughly cover the design space and to find and understand the relationships between airship design variables that lead to optimal mission times and costs. This research also explores the impacts of introducing an airship into operation. Engineered products have economic, environmental, and social impacts, which comprise the major dimensions of sustainability. This paper seeks to determine the interaction between design parameters when social impacts are incorporated into the concept development phase of the systems design process. Social impact evaluation is increasing in importance similar to what has happened in recent years with environmental impact consideration in the design of engineered products. Concurrently, research into new airship design has increased. Airships have yet to be reintroduced at a large scale or for a range of applications in society. Although airships have the potential for positive environmental and economic impacts, the social impacts are still rarely considered. This paper presents a case study of the hypothetical introduction of airships in the Amazon region of Brazil to help local farmers transport their produce to market. It explores the design space in terms of both engineering parameters and social impacts using a discrete-event simulation to model the system. The social impacts are found to be dependent not only on the social factors and airship design parameters, but also on the farmer-airship system, suggesting that socio-technical systems design will benefit from integrated social impact metric analysis. This thesis seeks to demonstrate how computer-aided engineering tools can be used to predict social impacts, to more effectively explore a system's design space, and to optimize the system design for maximum positive impact, using the modern airship as a case study.

Decision-making by one or more individuals to select a course of action is predicated on the values and preferences to identify, choose options, and finally select the option that is evaluated to be the “best option.” Decision theory provides the means to model and analyze both the processes and options available to the decision-makers. This dissertation assembled in three phases: 1) An effort to collect and review existing literature relating to the concept of expanding decision analysis options to provide a model of decision-making made with time-dependent factors along with uncertainty and risk. Further, adding the concept of a decision to update time-dependent decision data in a Bayesian fashion aids in modeling decision-making thought processes. This review included a total of 395 research artifacts. 2) Development of a technical approach using the information gathered in the literature review to guide planning for a decision-making simulation of individuals and organizations. The approach emphasizes creating a decision-making simulation framework with capabilities to model time-dependent factors, information processing and communication, and fuzzy-stochastic data. 3) Use of the technical approach to develop a simulation framework to simulate complex decision-making and work packages at multiple levels in an organization using time-dependent factors, information processing and communication, and fuzzy-stochastic data. Using a Discrete Event Simulation (DES) and Agent-Based Models (ABM) to simulate people and their interactions, this framework was then be used to simulate decision-making and work processes within an organization. Ultimately, the Agile Enterprise Simulation (AES) capability was created and demonstrated.

No description available.

No description available.

Forest fuel is an important source of energy with potential for increased use in the Nordic countries. Profitable forest operations are dependent on logistics as the forest is a natural resource with varying conditions over widespread areas. In comparison to saw log and pulp wood supply, forest fuel supply has to face challenges like low product value, seasonality and irregularity of customer demand, low bulk density and the need to process the biomass prior to delivery. In order to utilize both the economic potential and societal benefits from replacing fossil-based fuels with renewable forest fuels these challenges must be managed. This requires efficient long distance transports, with changes of transport mode typically required. This thesis examines preconditions necessary for logistic planning to achieve cost and energy efficient long distance transports within supply chains for forest fuel. The thesis has an explorative approach, including both qualitative and quantitative techniques. Paper I provides a review of the development within forestry logistics in Sweden and Finland since the beginning of the century, with focus on transports, terminal usage and storage related aspects. Paper II uses qualitative interviews to deepen the understanding of a specific forest fuel supply chain by focusing on communications and relations between the actors. Paper III is a study of  the influence of a terminal before maritime transport of wood chips using simulation.  Paper I shows that forestry logistics faces challenges, primarily related to increased variations in field conditions caused by climate change. The importance of terminal storage for the supply of forest products will likely increase as an effect. Also the entrepreneurs interviewed in Paper II stressed the benefits of terminals in the supply chain, e.g. enhanced planning opportunities and a more even workflow over the year. Paper III puts cost for extra terminal handling in relation to storage costs in a port and demonstrates the importance of including variation in logistic planning. The terminal flows were not profitable in the case of a small port. In order to make a well-founded decision gains in other parts of the supply chain must also be considered, even when they are harder to quantify. This deserves attention in future research. / Skogsbränsle är en viktig energikälla i de nordiska länderna och det finns potential att öka användningen. Ett lönsamt skogsbruk är beroende av god logistik då skogen är en naturresurs som är spridd över stora arealer och där förutsättningarna varierar i landet. Utöver de utmaningar som påverkar försörjningskedjorna för timmer och massaved måste skogsbränslesektorn förhålla sig till ett lågt produktvärde, stor säsongsvariation på efterfrågesidan, låg bulkdensitet och behov av sönderdelning inför transport. För att realisera de samhällsnyttor och den ekonomiska potential som finns i att ersätta fossila bränslen med förnybara måste dessa utmaningar hanteras. Det förutsätter effektiva transporter på längre avstånd, vilket normalt kräver byte av transportslag.  Avhandlingen studerar vilka förutsättningar som är viktiga för att skapa kostnads- och energieffektiva transporter över långa avstånd, avseende skogsbränsle. Den har ett explorativt angreppssätt och inkluderar både kvalitativa och kvantitativa metoder. Artikel I beskriver utvecklingen inom skoglig logistik i Sverige och Finland sedan år 2000. Bland fokusområdena finns transporter, terminalanvändning och aspekter kring lagring. Artikel II syftar till att fördjupa förståelsen kring en specifik försörjningskedja för skogsbränslen genom en intervjustudie. I fokus är kommunikation och relationer mellan aktörerna i kedjan. I artikel III används en simuleringsmodell för att undersöka hur införandet av en terminal påverkar logistiken vid fartygsleveranser av flisat skogsbränsle. Artikel I visar att den skogliga logistiken står inför utmaningar relaterade till ökande variationer i väderförhållanden som en följd av klimatförändringar. Som en konsekvens kommer möjligheten att lagra material på terminaler sannolikt öka i betydelse. Också i Artikel II lyfts vikten av terminallagring av de intervjuade entreprenörerna, som nämner ökade planeringsmöjligheter och ett jämnare arbetsflöde över året som fördelar med terminaler. Artikel III jämför kostnader för terminalhantering med kostnaderna för lagring i hamn och demonstrerar vikten av att inkludera variation i logistikplaneringen. Terminalflödena var inte lönsamma i fallet med en mindre hamn, men övriga studier tydliggör vikten av att inkludera effekter för hela försörjningskedjan, också när dessa är svåra att kvantifiera. Detta område förtjänar uppmärksamhet i framtida forskning.

Data-intensive scientific applications often process an enormous amount of data. The scalability of such applications depends critically on how to manage the locality of data. Our study explores two common types of applications that are vastly different in terms of memory access pattern and workload variation. One includes those with multi-stride accesses in regular nested parallel loops. The other is for processing large-scale irregular social network graphs. In the former case, the memory location or the data item accessed in a loop is predictable and the load on processing a unit work (an array element) is relatively uniform with no significant variation. On the other hand, in the latter case, the data access per unit work (a vertex) is highly irregular in terms of the number of accesses and the locations being accessed. This property is further tied to the load and presents significant challenges in the scalability of the application performance. Designing platforms to support extreme performance scaling requires understanding of how application specific information can be used to control the locality and improve the performance. Such insights are necessary to determine which control and which abstraction to provide for interfacing an underlying system and an application as well as for designing a new system. Our goal is to expose common requirements of data-intensive scientific applications for scalability. For the former type of applications, those with regular accesses and uniform workload, we contribute new methods to improve the temporal locality of software-managed local memories, and optimize the critical path of scheduling data transfers for multi-dimensional arrays in nested loops. In particular, we provide a runtime framework allowing transparent optimization by source-to-source compilers or automatic fine tuning by programmers. Finally, we demonstrate the effectiveness of the approach by comparing against a state-of-the-art language-based framework. For the latter type, those with irregular accesses and non-uniform workload, we analyze how the heavy-tailed property of input graphs limits the scalability of the application. Then, we introduce an application-specific workload model as well as a decomposition method that allows us to optimize locality with the custom load balancing constraints of the application. Finally, we demonstrate unprecedented strong scaling of a contagion simulation on two state-of-the-art high performance computing platforms. / Ph. D.