The thesis is focused on SCM and information support for supply chain managers with emphasis on modelling and simulation. The first main aim of the work is to verify the method for applicability in SCM problem solution. The second main aim is to analyse supply chains by means of modelling and simulation and find the most suitable supply chains for the area of The New economics. The third main aim is to analyse behaviour of supply chains under changing factors on which the supply chains are initially modelled. The output of this work is applicable in the theory, practice and education

The Master Thesis deals with offshoring and its logistic requirements. The first part of thesis characterizes terms as outsourcing, offshoring and offshore outsourcing. The main reasons for foreign production are seeking of resources (typically low cost labour) and expansion into new markets. Benefits and risks of offshoring are analyzed in the thesis, as well as criteria for selection of suitable host destination. Often overlooked impacts of globalization on integrated supply chain are also considered in this thesis. Central and Eastern Europe is one of important offshoring regions. CEE offers relatively cheap and qualified labour. However, its main benefit is its small geographical distance from Western Europe. The costs of servicing markets at Western Europe from CEE are much lower compared to servicing these markets from Asia.

Arbetet har utförts vid Tekniska Högskolan i Jönköping där en studie har genomförts i samarbete med Kitron AB som är ett elektroniktillverkande företag. Kitron strävar efter att reducera kapitalbindningen för att vara kostnadseffektiva och därmed hålla hög konkurrenskraft. Studiens syfte var att identifiera de aspekter som påverkar företagets kapitalbindning och ta fram åtgärdsförslag för att minska kapitalbindningen som orsakas av materialflödet för ett av Kitrons kundprogram inom medicinteknik. Olika metoder användes för att samla in data gällande materialflödet. För att finna åtgärder analyserades materialflödet utifrån insamlad teori och genomförd värdeflödesanalys. Studien resulterade i identifiering av ett antal aspekter som påverkar kapitalbindningen och utifrån de togs åtgärder fram. De rekommenderade åtgärderna grundas i teori om Lean production. Åtgärdsförslagen bidrar till att effektivisera materialflödet och minimera den totala ledtiden för att reducera kapitalbindningen. Ett effektivare materialflöde kan uppnås genom att producera enligt principerna inom just in time och minimera slöseri. God samverkan med de kunder och leverantörer som påverkar materialflödet är också önskvärt. Den produktstruktur som Kitron utgår ifrån kan även anpassas efter produktionen för att minimera produktionsledtiden. Sammanfattningsvis krävs en kortare ledtid för att reducera kapitalbindningen inom det studerade kundprogrammet. Med hjälp av en del av de presenterade åtgärdsförslagen skapades ett idealt materialflöde som innebar reducering av produktionsledtiden med 15,5 dagar. Detta skulle medföra en reducering av kapitalbindningen med ungefär 454 000 kronor. / This project has been carried out at Jönköping University of Technology. The study has been executed in collaboration with the electronics manufacturing company, Kitron AB. Kitron aims to reduce the capital tied up to be cost efficient and improve the competitiveness. The purpose with this study was to identify the aspects that affect the company´s capital tied up and also find solutions to reduce the capital tied up caused by the material flow. A case study was executed at the company where the study was delimited to one specific customer of Kitron that make biomedical technology. Different methods were being used to gather data which has later been analyzed based on the theoretical framework. To find the solutions and identify the material flow an analyze was executed from theoretical aspects and a value stream map.  The study resulted in identification of several aspects that affect the capital tied up. From these aspects, solutions were found. The recommended solutions are based on theory about lean production. The solutions contribute to a more efficient material flow and help reduce the total lead time to enable a lower capital tied up. A more efficient material flow can be achieved by producing according to the principles of just in time and by reducing waste. It is preferable to cooperate with customers and suppliers that affect the material flow to improve it. The product structure can be arranged differently to enable a shorter production lead time. In conclusion, a shorter lead time is necessary to reduce the capital tied up concerning the studied customer. An ideal material flow was created by using some of the suggested solutions, which resulted in a shorter production lead time by 15,5 days. This would also contribute to a reduction of the capital tied up with 454 000 SEK.

The development of more complex products has increased dependency on virtual/digital models and emphasized the role of simulations as a means of validation before production. This level of dependency on digital models and simulation togetherwith the customization level and continuous requirement change leads to a large number of iterations in each stage of the product development process. This research, studies such group of products that have multidisciplinary, highly iterative, and simulation-driven design processes. It is shown that these high-level technical products, which are commonly outsourced to suppliers, commonly suffer from a long development lead time. The literature points to several research tracks including design automation and data-driven design with possible support. After studying the advantages and disadvantages of each track, a data-driven approachis chosen and studied through two case studies leading to two supporting tools that are expected to improve the development lead time in associated design processes. Feature extraction in CAD as a way to facilitate metamodeling is proposed as the first solution. This support uses the concept of the medial axis to find highly correlated features that can be used in regression models. As for the second supporting tool, an automated CAD script is used to produce a library of images associated with design variants. Dynamic relaxation is used to label each variant with its finite element solution output. Finally, the library is used to train a convolutions neural network that maps screenshots of CAD as input to finite element field answers as output. Both supporting tools can be used to create real-time prediction models in the early conceptual phases of the product development process to explore design space faster and reduce lead time and cost. / Utvecklingen av mer komplexa produkter har ökat beroendet av virtuella/digitala modeller och ökat betydelsen av simuleringar för att validera en produkt inför produktion. Ett stort beroende av digitala modeller och simulering tillsammans med den individuella anpassningen och kontinuerliga kravförändringar leder till ett stort antal iterationer i varje steg i produktutvecklingsprocessen. Forskningen som presenteras i denna avhandling studerar denna typ av produkter som har multidisciplinära, mycket iterativa och simuleringsdrivna designprocesser. Det har visat sig att dessa tekniska produkter på hög nivå, som vanligtvis tillhandahålls av underleverantörer, vanligtvis har en lång ledtid för utveckling. Litteraturstudien pekar på flera forskningsspår, exempelvis designautomation och datadriven design, eventuellt med stöd. Efter att ha studerat fördelarna och nackdelarna med varje spår, väljs det datadrivna tillvägagångssättet och studeras genom två fallstudier som leder till att två stödjande verktyg tas fram. De förväntas förbättra utvecklingsledtiden i tillhörande designprocesser. Feature extraktion i CAD som ett sätt att underlätta metamodellering föreslås som det första verktyget. Detta stöd använder medial axis för att hitta korrelerade features som kan användas i regressionsmodeller. När det gäller det andra stödjande verktyget används ett automatiserat CAD-skript för att producera ett stort bibliotek med bilder som är associerade olika designvarianter. Dynamisk relaxation används för att märka varje variant med dess finita elementlösning. Slutligen används detta bibliotek för att träna ett konvolutionerande neuralt nätverk som kartlägger skärmdumpar av CAD som indata till finita elementfältsvar som utdata. Båda stödverktygen kan användas för att skapa modeller för förutsägelser i realtid i de tidiga konceptuella faserna av produktutvecklingsprocessen för att utforska designrymden snabbare och minska ledtid och kostnader.

Due to a changing competitive environment, SMEs have to improve their production performance. A commonly applied philosophy to improve production performance is called lean thinking. This method, derived from the Toyota Production System, banishes wasteful activities while increasing the competitive strength and responsiveness of a company.Many companies fail in their attempt to become lean and therefore techniques are needed to guide the implementation. This thesis proposes to use Value Stream Mapping as an implementation technique for SMEs. This technique is tested in a company as a case study. By applying the Value Stream Mapping tool to a specific process within this company, substantial improvement potential is revealed. Work content can be decreased by 30,3 percent, and delivery time and in-factory lead time can be decreased by at least 38,6 percent and 68 percent respectively.The thesis concludes that lean thinking is applicable to SMEs, at least under certain circumstances. Furthermore, Value Stream Mapping can be a valuable tool in revealing improvement potential.

In studies carried out at wooden house companies, it has been shown that the window assembly process has been a bottleneck. Bottlenecks cause waste in the process as it can lead to unused value-creating time. Window mounting is also done in a way that is not ergonomic for the worker which damages their productivity and health. By getting rid of the bottleneck, there is the possibility of a lead time reduction.  The purpose of the study was to investigate whether a new window mounting method can replace the existing one in an advantageous way. The study was conducted at the fall company Vida Building AB, which is a manufacturer of prefabricated wooden houses.  To fulfill the purpose, qualitative and quantitative collection methods have been used to map work steps in the production flow and its cycle times. In this way, a comparison has been made between the existing and the new window mounting method. It has then been possible to make an analysis to investigate whether it is possible to fill queue times with the new method.  Several improvement proposals have been made based on the data collected. The utilization of the new window mounting method enables a balancing in the production flow, as well as a reduction in waste partly due to ergonomic work but also due to a more efficient mounting method. To further increase productivity, proposals for aids have been specified to improve the workers working position.

Lean management is considered a key to lead time reduction while being efficient, in order to survive in the actual market. Despite this, there is relatively little research done about implementation of lean management in ETO processes. Knowing that ETO processes are a reality in the industry, because there is a demand of customized products in the market. Nonetheless, the early phases of the ETO processes are critical. The purpose of this study was therefore to investigate how lean management can be used to understand and early phases of ETO processes, in order to evaluate potential lead time reduction. Analysing issues that arise when implementing lean in this kind of processes, such as variety, variation and standardization. The empirical data was collected from two different companies with ETO processes on different stages of lean implementation. A theoretical background in the area is supported by a comparison of the historical development and current state of two companies. The access to these two companies provides a view of the state before lean implementation and during implementation, and also a brief view of the effects. This helps to understand how lean management could be implemented in ETO processes. As a result, this research describes what should be considered when implementing lean management in early phases of ETO processes and what the effect of this implementation could be.

Online software businesses constantly face new challenges. Businesses are competing to deliver high-quality software solutions to their end users as quickly as possible. The performance of a software team in terms of software delivery needs to be measured to identify bottlenecks and understand what can be improved. This project is a case study of a software organisation that delivers online web solutions for a business. The organisation strives to follow a DevOps mindset and work data-driven by collecting data, learning from it and acting on the learnings. Our method to perform the case study was to study existing data collected by the organisation and conduct interviews with software professionals to get their insights about the software delivery performance of three software teams within the organisation. We focus on two metrics - deployment frequency and lead time for change - which measure the throughput of a software team and how often and fast it can deploy changes to production. Software organisations that adopt a DevOps approach are facing challenges with collecting data about their software delivery performance and learning from that data to improve their throughput. We aim to identify these challenges and discuss various problems that software organisations need to be aware of when measuring software delivery performance. We present the results from the interviews and collected metrics, analyse them and discuss them, as well as give suggestions on future research. We observe that there are multiple factors impacting software delivery performance and various challenges with measuring it accurately. This is related to the way of reporting data reliably and developing models to study and understand the collected data.

Artificial Intelligence (AI) has proven to be highly suitable for a wide range of problems in manufacturing environments, including the prediction of lead times. Most of these solutions are based on ”black-box” algorithms, which hinder practitioners to understand the prediction process. Explainable Artificial Intelligence (XAI) provides numerous tools and methods to counteract this problem. There is however a need to qualify the methods with human-centered studies in manufacturing environments, since explainabilityis context-specific. The purpose of this mixed-method case study is to examine the explainability of regression models for lead time prediction in quality control laboratories at a biopharmaceutical production site in Sweden. This entails the research questions of which methods can increase the explainability of lead time prediction, what type of explanation is required to enable explainability and what are the benefits of explaining regression models in this context. This is why relevant literature in the field of XAI and AI-based lead time prediction is reviewed. An explainable lead time prediction modelis developed and a Delphi study is carried out to gauge the importance of different explanation types and to identify explainability-related benefits. The results show a transparency-performance trade-off and highlight eight benefits that are mapped to the model’s life cycle. These findings provide new insights into the explainability requirements and benefits in quality control processes and support practitioners in steering their implementation efforts. / Artificiell Intelligens (AI) har visat sig vara mycket lämplig för ett stort antal problem i tillverkningsmiljöer, bland annat när det gäller att förutsäga ledtider. De flesta av dessa lösningar är baserade på algoritmer som är ”svarta lådor”, vilket gör det svårt för tillämparna att förstå förutsägelseprocessen. Explainable Artificial Intelligence (XAI) erbjuder många verktyg och metoder för att motverka detta problem. Det finns dock ett behov av att kvalificera metoderna med människocentrerade studier i tillverkningsmiljöer, eftersom förklarbarhet är kontextspecifikt. Syftet med denna fallstudie med blandad metod är att undersöka förklaringsbarheten hos regressionsmodeller för prediktion av ledtider i kvalitets kontrolllaboratorier vid en biopharmaceutisk produktionsanläggning i Sverige. Vilket syftar till forskningsfrågorna samt vilka metoder som kan öka förklaringsbarheten och av prognoser för ledtider, vilken typ av förklaring som krävs för att möjliggöra en förklarbarhet och vilka fördelar som finns med att förklara regressionsmodeller i detta sammanhang. Det är därför som relevant litteratur på området XAI och AI baserade prognostisering av ledtider granskas. En förklaringsbar modell för prognostisering av ledtider utvecklas och en Delphi-studie genomförs för att bedöma betydelsen av olika typer av förklaringar och för att identifiera förklaringsrelaterade fördelar.

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