The trends for manufacturing organizations are continuously increased customer expectations and demands, together with globalization of both markets and competition. As we are currently approaching the fourth industrial revolution and in order to stay competitive, companies need to adopt technological changes, differentiate themselves and improve their digital maturity. In line with this, Atlas Copco Secoroc, a Swedish manufacturing company of mining equipment and tools, has shared a divisional vision stating that they will embrace the Internet of Things and introduce some of the latest technological and digital trends. This in turn, sets some requirements on a functional traceability system. This research investigates how traceability could be improved throughout Atlas Copco Secoroc’s production chain and manufacturing processes. This research is based on an empirical study consisting of observations and interviews, all conducted at the company Atlas Copco Secoroc in Fagersta, Sweden, as well as a coherent and iterative literature review. The results emphasize the importance of understanding the overall need, clearly defining a traceability strategy and setting a suitable target level. It is vital to acquire knowledge regarding the subject and to first focus on securing the internal traceability and then expand to cover the entire supply chain. Furthermore, the findings highlight existing shortcomings, present material and recommendations that should be taken into consideration before advancing further and in-dicate the synergies with total quality management. Moreover, the master thesis resulted in concrete actions regarding how Atlas Copco Secoroc can enhance traceability within their manufacturing processes. Due to confidential information these recommendations are shown to Atlas Copco only and are not included in the published master thesis. / Trenderna för tillverkande företag är ständigt ökade kundkrav och förväntningar, tillsammans med globalisering av både marknader och konkurrens. För att vara fortsatt konkurrenskraftig när vi nu närmar oss den fjärde industrirevolutionen måste företagen adaptera tekniska förändringar, differentiera sig och förbättra den digitala mognaden. I linje med detta har Atlas Copco Secoroc, ett svenskt industriföretag som tillverkar gruvutrustning och verktyg, delat en divis-ionsvision som säger att de kommer att omfamna Internet of Things och introducera några av de senaste tekniska och digitala trenderna. Detta ställer i sin tur vissa krav på ett funktionellt spårbarhetssystem. Denna studie undersöker hur spårbarheten kan förbättras genom Atlas Copco Secorocs produktionskedja och tillhörande tillverkningsprocesser. Detta examensarbete baseras på en empirisk studie utförd hos Atlas Copco Secoroc i Fagersta. Studien bestod av ingående observationer och intervjuer samt en kontinuerlig och iterativ litteraturstudie. Resultaten betonar vikten av att förstå det övergripande behovet, tydligt definiera en spårbarhetsstrategi och sätta en lämplig spårbarhetsnivå. Det är viktigt att förvärva kunskap om ämnet och att först fokusera på att säkra den interna spårbarheten innan arbetet avser täcka hela försörjningskedjan. Vidare lyfter resultaten fram befintliga brister, material och rekommendationer som bör beaktas innan en vidareutveckling kan ske. Studien presenterar även synergierna till konceptet total kvalitetsledning.Slutligen, studien har resulterat i konkreta åtgärder avseende hur Atlas Copco Secoroc kan för-bättra spårbarheten inom sina tillverkningsprocesser. På grund av konfidentiell information presenteras dessa rekommendationer endast för Atlas Copco och ingår inte i det publicerade examensarbetet.

Dagens marknad är mycket osäker och föränderlig, vilket är en utmaning för bland annat industriföretag. För att förbli relevanta för marknaden måste företag anpassa sig. Anpassningen möjliggörs genom att företagen är flexibla i hela sin verksamhet. För ett industriföretag kan flexibilitet avse produktionsflexibilitet i produktionslayouter. Det är en mycket viktig komponent för att kunna hantera korta produktlivscykler och snabbt utvecklanya produkter. Denna kandidatuppsats undersöker vilken layout av de centrala layouterna, linan eller funktionella layouten, som är mest fördelaktig vad gäller flexibilitet och produktionskostnader givet nya lösningar från Industri 4.0. För att svara på frågan genomfördes en analys och en litteraturstudie baserade på ett studiebesök på Volvo fabriken i Köping. Analysen genomfördes genom att konstruera en lina som sedan skulle jämföras med en yteffektiviserad funktionell layout från Volvo fabriken i Köping. Resultaten av analysen visade att en lina med en rads placering har minst area men är lägre expansionsflexibel än en funktionell layout med Industri 4.0-lösningar. / Today's market is very uncertain and changing, which is a challenge for, among other things, industrial companies. To remain relevant in the market, companies must adapt. Adaptation is made possible by the companies being flexible throughout their operations. For an industrial company, flexibility can refer to production flexibility in production layouts. It is a very important component to be able to manage short product life cycles and quickly develop new products. This bachelor's thesis examines which production layout of the main layouts, a product or a functional layout, is most beneficial in terms of flexibility and production costs given new solutions from Industry 4.0. To answer the question, an analysis and a literature study were carried out based on a study visit to the Volvo factory in Köping. The analysis was carried out by constructing a product layout which would then be compared with a surface-efficient functional layout from the Volvo factory in Köping. The results of the analysis showed that a product layout with single-row placement has the least footprint but is less expansion flexible than a functional layout with Industry 4.0 solutions.

The purpose of this paper was to use the Overall Equipment Effectiveness productivity formula in plant manufacturing and convert it to measuring productivity for forklifts. Productivity for a forklift was defined as being available and picking up and moving containers at port locations in Seattle and Alaska. This research uses performance measures in plant manufacturing and applies them to mobile equipment in order to establish the most effective means of analyzing reliability and productivity. Using the Internet of Things to collect data on fifteen forklift trucks in three different locations, this data was then analyzed over a six-month period to rank the forklifts’ productivity from 1 – 15 using the Operating Equipment Effectiveness formula (OPEE). This ranking was compared to the industry standard for utilization to demonstrate how this approach would yield a better performance analysis and provide a more accurate tool for operations managers to manage their fleets of equipment than current methods. This analysis was shared with a fleet operations manager, and his feedback indicated there would be considerable value to analyzing his operations using this process. The results of this research identified key areas for improvement in equipment reliability and the need for additional operator training on the proper use of machines and provided insights into equipment operations in remote locations to managers who had not visited or evaluated those locations on-site.

Många förändringar sker idag inom industrin och särskilt med tanke på omställning till industri 4.0. Dana Incorporated har genom Högskolan Väst efterfrågat en studie om automatiserade transporter i deras planerade fabrik i Åmål. Fabriken ska ligga i yttersta framkant gällande automation och effektivitet med industri 4.0 som mål. För att hitta rätt system behandlar denna rapport flera viktiga aspekter som behöver tas i beaktning vid övergång eller nyetablering av AGV/AMR truckar och robotar. Studier, intervjuer och fakta används i rapporten för att hitta rätt system i en föränderlig miljö där flexibilitet efterfrågas. Förstudierna om godsets förpackning, AGV/AMR-systemets modell och flexibilitet visar sig vara ytterst viktiga faktorer i studien. Det är stor skillnad mellan olika AGV/AMR-system i både pris och utförande, vilket gör att stora kostnader går att spara vid grundlig undersökning. Ju mer arbete och tid som läggs i förstudierna desto mer underlättar implementering och sparar på investeringskostnaden. Studien visar att ju längre tid det tar att implementera, blir kostnaden högre på grund av att företaget samtidigt belastas med operatörskostnader. Längre implementeringstid ger högre kostnad men innebär ett lägre risktagande. Att hitta den perfekta balansen mellan dessa två faktorer är svårt och tidskrävande. Det är ändå viktigt att ha vetskap om att både en för djärv och en för långsam satsning resulterar i onödiga kostnader. Strukturen och flexibilitet är andra delar som påverkar val av system. Inget AGV/AMR-system kan idag ha samma flexibilitet som en mänsklig truckförare. Organisationen måste därför struktureras till den flexibilitetsgrad som det tänkta systemet kan hantera. Vilken grad av vinst och resultat som ges genom det tänkta AGV/AMR-systemet grundas mycket genom kunskap om AGV/AMR-systemen som skulle passa företaget innan val av produkt. / Many changes are taking place today in the industry and especially with a view to conversion to industry 4.0. Through University West, Dana Incorporated has requested a study on automated transports in their planned factory in Åmål. The factory will be at the forefront of automation and efficiency with industry 4.0 as its goal. To find the right system, this report addresses several important aspects that need to be taken into account when transitioning or establishing new AGV / AMR trucks and robots. Studies, interviews and facts are used in the report to find the right system in a changing environment where flexibility is required. The feasibility studies on the packaging of the goods, the model and flexibility of the AGV / AMR system prove to be extremely important factors in the study. There is a big difference between different AGV / AMR systems in both price and design, which means that large costs can be saved during a thorough examination. The more work and time that is put into the feasibility studies, the easier it is to implement and save on the investment cost. The study shows that the longer the time implementation requires, the higher the cost due to contemporary operator costs. Longer implementation time results in higher costs but means lower risk-taking. Finding the perfect balance between these two factors is hard and time consuming. It´s still a good knowledge to know that both a too bold and a too slow investment results in unnecessary costs. The structure and flexibility are other parts that influence the choice of system. No AGV / AMR system today can have the same flexibility as a human truck driver. The organization must therefore be structured to the flexibility that is possible to handle for the selected system. The degree of profit and results given through the intended AGV / AMR system is largely based on knowledge before choosing a product.

Industry 4.0 is at the moment one of the most talked-about topics amongst industry companies. Management teams of discuss the area as something they want to implement, but since it is an ongoing industrial revolution it cannot be implemented straight away. This study is looking into the subject of Industry 4.0 and the identification of nine different technology drivers that a manufacturing company can use as tools in a production environment. However, what is less known is how the tools can be applied to a global company and its different cultures. Because even though Industry 4.0 is about decentralization and giving responsibility to every co-worker, they need to work with a common framework, thus standardization. A company that has started to look into Industry 4.0 is Lantmännen Unibake, who is a global bakery group. Therefore, they serve as the case company in this exploratory study where the goal is to conduct a pre-study that gives them, and the food industry, information and guidelines on how Industry 4.0 applies to their industry. Hence, what improvements it can lead to, what tools that will be suitable, and what the prerequisites for a successful Industry 4.0- transformation will be. The method to answer the research question starts with conducting a comprehensive literature study, followed by several interviews around Europe, and ending in an analysis of the current state with help from the literature framework. The analysis has ended in a conclusion that there is no single or easy answer to the questions since food industries might vary a lot from one to another. Although, in this case, the answer would be that six out of nine tools would be applicable in a global food-supply-chain, some needing more preparatory work than others. By implementing these tools, companies will see more engaged employees that are prone to take autonomous decisions, more accurate production planning, proactive rather than reactive working ways, fewer defects, and higher customer satisfaction. Regarding the prerequisites for transformation, the answer depends on what tools that are used. But what all cases have in common is that there is a need for aware and engaged employees. Everyone will have to be in on the change, understanding why and how, and what benefits that will come out of it. For future studies, it is suggested to look into how maturity models can be applied to these kinds of issues smoothly. The existing maturity models for Industry 4.0 are very complicated and difficult to apply; thus, they would need some development. Another area would be a cost model of the different tools, as well as a comparison of the tools and food regulations. / I dagens läge är Industri 4.0 ett av de hetaste ämnena bland industriföretag. Ett problem är att det ofta diskuteras som något som bör implementeras vilket skapar en felaktig bild av vad Industri 4.0 är, en pågående industriell revolution. Denna studie undersöker ämnet Industri 4.0 och identifierar nio verktyg som kan användas som teknologiska drivkrafter i en tillverkningsmiljö. Då dagens forskning är i sin linda finns det begränsat med information om hur dessa verktyg kan anpassas till att fungera i en global miljö med flera olika kulturer. Även om Industri 4.0 till stor del handlar om decentralisering och att ge ökat ansvar till alla medarbetare så kräver den nya typen av industri också standardisering och att ett företag har ett gemensamt ramverk. Lantmännen Unibake är ett företag som har börjat undersöka möjligheterna med Industri 4.0. Lantmännen Unibake är en av Europas ledande bagerigrupper och agerar som case-företag i denna utforskande studien. Syftet är att sammanställa en förstudie om hur Lantmännen Unibake och livsmedelsindustrin kan utnyttja Industri 4.0:s potentialer, det vill säga vilka förbättringar det kan leda till, vilka verktyg som är applicerbara på industrin och vilka förutsättningar som krävs för en lyckad transformation. För att svara på dessa frågor har en omfattande litteraturstudie och flertalet intervjuer genomförts runt om i Europa. Med hjälp av nulägesanalysen och litteraturstudien har slutsatsen blivit att det varken finns ett ensidigt eller enkelt svar på frågorna då livsmedelsindustri skiljer sig väldigt från företag till företag. I detta fall har sex av nio verktyg identifierats som användbara för en global livsmedelsvärdekedja, dock kräver somliga verktyg mer förberedelser än andra. Genom att implementera dessa verktyg kan företaget komma att se motiverad personal som är mer benägna att ta autonoma och snabba beslut, mer tillförlitlig produktionsplanering, ett proaktivt snarare än reaktivt arbetssätt, minskad mängd defekter och högre kundnytta. Förutsättningar för en förändring beror på vilka verktyg som väljs, dock kräver alla att personalen är medveten om förändringen. Både varför den behöver göras, hur det kommer gå till och vad för fördelar det kommer leda till . Förslag för framtida studier är att se över hur en mognadsanalys kan appliceras på denna typ av situation då de modeller som existerar inom området i dagsläget är väldigt komplicerade och därför svåra att applicera på gemene företag. Ett annat område är en kostnadsanalys för de olika verktygen, likväl en jämförelse mellan verktygen och huruvida de uppfyller livsmedelsreglerna.

With the rise of Industry 4.0 and the 4:th industrial revolution withthe Internet of Things, infrastructures have become more prevalent to connect and monitor many different systems within an industrial set-ting. With many candidates for this IoT infrastructure, there is a need to evaluate the different candidates to determine the different strengthsand weaknesses of the infrastructure.This thesis investigates the use of the Eclipse Arrowhead framework in the application of scalable infrastructure used for predictive mainte-nance. This investigation is conducted by converting an existing pre-dictive maintenance implementation that is using Amazon Web Services as the IoT infrastructure into a predictive maintenance implementationusing the Eclipse Arrowhead framework as the infrastructure.This design science artifact which results from this thesis shows that the Eclipse Arrowhead framework is suitable for a scalable infrastruc-ture though some shortcomings of the framework were found during the implementation. And though it is a suitable infrastructure, the usage ofthe framework should depend on the specific needs of the infrastructureand should not be used as a “one size fits all” solution.

In modern conditions, the effective development of industrial enterprises is complicated by the low organizational and technical level of production, high costs and insufficient financial resources, which requires the active attraction of investment funds. The purpose of the master's thesis is to develop a methodological approach to the formation of the investment policy of a non-ferrous metallurgy enterprise within the framework of Industry 4.0. The research considers the concept of the investment policy of the enterprise and the correlation of the investment activity of the enterprise with the implementation of technologies of Industry 4.0. The sources used were teaching and research literature, the results of empirical research of the author and corporate statistics. In the master's thesis, the author’s methodology for the selection of investment projects was developed as part of the investment policy of an industrial non-ferrous metallurgy enterprise, which includes three stages of selection: preliminary, coefficient, final. The application of this technique allows you to deepen the analysis and assessment of the effectiveness of investment projects related to Industry 4.0. / В современных условиях эффективное развитие промышленных предприятий осложняется низким организационно-техническим уровнем производства, высокими затратами и недостаточными финансовыми ресурсами, что требует активного привлечения инвестиционных средств. Целью магистерской диссертации является разработка методического подхода к формированию инвестиционной политики предприятия цветной металлургии в рамках «Индустрии 4.0». В работе рассматривается понятие инвестиционной политики предприятия и вопросы взаимосвязи инвестиционной деятельности предприятия с внедрением технологий «Индустрии 4.0». В качестве источников использовалась учебно-методическая и научно-исследовательская литература, результаты эмпирических исследований автора и данные корпоративной статистики. В магистерской диссертации была разработана авторская методика отбора инвестиционных проектов в рамках инвестиционной политики промышленного предприятия цветной металлургии, включающая в себя три этапа отбора: предварительный, коэффициентный, заключительный. Применение данной методики позволяет углубить анализ и оценку эффективности инвестиционных проектов, связанных с «Индустрией 4.0».

The German government's "Industry 4.0" paradigm transforms technology application across domains using real-time data and connectivity. The telecom sector's reliance on digital, software-driven infrastructure for real-time data and connectivity is paramount. Data science and Artificial Intelligence (AI) are crucial, enhancing telecom networks' reliability, cutting costs, and improving service. This technology drives efficiency and innovation, shaping 33% of the market. As AI matures, discussions revolve around potential human replacement, especially in innovation management. Early AI investments yield cost-effective innovation but may not entirely replace human discretion. The exact AI implementation varies, aligning with organizational goals. This research investigates the challenges of implementing AI in the dynamic telecom industry's R&D departments, particularly in Sweden and Finland. The research employs a case-study approach, utilizing semi-structured interviews and document analysis. Thematic analysis of the qualitative data reveals key challenges, including "Lack of Understanding and Awareness," "Recruitment and Skills Gap," "Data Security and Privacy Concerns," and "Infrastructure and Funding Limitations." These findings contribute to a comprehensive understanding of AI adoption challenges in the telecom sector, offering valuable insights for future research and industry practice. Ethical considerations and credibility measures were employed to ensure the rigor and validity of the research, emphasizing the importance of impartiality and multiple perspectives in qualitative research. A thematic analysis was conducted focusing on the "People," "Position," "Process," and "Technology" themes. "Position" categorizes organizations and individuals into AI-beginners, AI-followers, and AI-leaders, showing the diverse stages of AI adoption. "People" emphasizes upskilling, culture, and employee receptiveness. "Process" delves into integration challenges, data quality, ethics, and communication. "Technology" highlights data and budget challenges, infrastructure, and scalability. The findings reveal the telecom industry's transformative AI journey and the importance of balancing technological advancements, cultural shifts, skill development, and ethical considerations for successful AI implementation. While the research followed a rigorous qualitative approach, transparency is crucial for evaluating its credibility and acknowledging potential biases and limitations. The telecom industry's future success in harnessing AI's potential relies on understanding and addressing these multifaceted challenges. This research categorizes organizations and individuals into three distinct AI adoption stages: AI-beginners, AI-followers, and AI-leaders. This framework illuminates the diverse positions within the AI adoption spectrum and emphasizes the critical role of leadership, resource allocation, and skills development. Moreover, this research underscores the significance of human factors, integration processes, and technological considerations in successful AI adoption. Practical implications encompass strategic planning, resource allocation, leadership development, cross-functional collaboration, change management, ethical considerations, and talent acquisition. While offering valuable insights, the research acknowledges limitations in sample size, subjectivity, temporal relevance, and contextual completeness. This research also explores the potential future research directions in the domain of AI adoption in the telecom industry. Drawing from the insights gathered through interviews, several promising avenues for future investigations are outlined. These include longitudinal studies to track the evolution of AI adoption, cross-industry comparisons to identify best practices, quantitative analyses of AI's impact on key performance indicators, examinations of regulatory and ethical frameworks, in-depth studies of AI-related skill development, investigations into AI's impact on employment, and explorations of cultural transformations necessary for successful AI adoption. These avenues offer opportunities to advance our understanding of AI adoption dynamics and their implications for the telecom sector.

Cyber-physical systems (CPS) connect the physical and digital domains and are often realized as spatially distributed. CPS is built on the Internet of Things (IoT) and Internet of Services, which use cloud architecture to link a swarm of devices over a decentralized network. Modern CPSs are undergoing a foundational shift as Industry 4.0 is continually expanding its boundaries of digitization. From automating the industrial manufacturing process to interconnecting sensor devices within buildings, Industry 4.0 is about developing solutions for the digitized industry. An extensive amount of engineering efforts are put to design dynamically scalable and robust automation solutions that have the capacity to integrate heterogeneous CPS. Such heterogeneous systems must be able to communicate and exchange information with each other in real-time even if they are based on different underlying technologies, protocols, or semantic definitions in the form of ontologies. This development is subject to interoperability challenges and knowledge gaps that are addressed by engineers and researchers, in particular, machine learning approaches are considered to automate costly engineering processes. For example, challenges related to predictive maintenance operations and automatic translation of messages transmitted between heterogeneous devices are investigated using supervised and unsupervised machine learning approaches. In this thesis, a machine learning-based collaboration and automation-oriented IIoT framework named Cloud-based Collaborative Learning (CCL) is developed. CCL is based on a service-oriented architecture (SOA) offering a scalable CPS framework that provides machine learning-as-a-Service (MLaaS). Furthermore, interoperability in the context of the IIoT is investigated. I consider the ontology of an IoT device to be its language, and the structure of that ontology to be its grammar. In particular, the use of aggregated language and structural encoders is investigated to improve the alignment of entities in heterogeneous ontologies. Existing techniques of entity alignment are based on different approaches to integrating structural information, which overlook the fact that even if a node pair has similar entity labels, they may not belong to the same ontological context, and vice versa. To address these challenges, a model based on a modification of the BERT_INT model on graph triples is developed. The developed model is an iterative model for alignment of heterogeneous IIoT ontologies enabling alignments within nodes as well as relations. When compared to the state-of-the-art BERT_INT, on DBPK15 language dataset the developed model exceeds the baseline model by (HR@1/10, MRR) of 2.1%. This motivated the development of a proof-of-concept for conducting an empirical investigation of the developed model for alignment between heterogeneous IIoT ontologies. For this purpose, a dataset was generated from smart building systems and SOSA and SSN ontologies graphs. Experiments and analysis including an ablation study on the proposed language and structural encoders demonstrate the effectiveness of the model. The suggested approach, on the other hand, highlights prospective future studies that may extend beyond the scope of a single thesis. For instance, to strengthen the ablation study, a generalized IIoT ontology that is designed for any type of IoT devices (beyond sensors), such as SAREF can be tested for ontology alignment. Next potential future work is to conduct a crowdsourcing process for generating a validation dataset for IIoT ontology alignment and annotations. Lastly, this work can be considered as a step towards enabling translation between heterogeneous IoT sensor devices, therefore, the proposed model can be extended to a translation module in which based on the ontology graphs of any device, the model can interpret the messages transmitted from that device. This idea is at an abstract level as of now and needs extensive efforts and empirical study for full maturity.

A surge in the battery industry and market was observed a few years back. Currently, the leaders in producing batteries are Asian countries. Nevertheless, countries are attempting to penetrate the battery market and become stable manufacturing competitors of batteries, one of which is Sweden. One of the driving factors of the surge in battery usage is sustainability awareness. Industry 4.0 and digitalization have become popular within industries and firms with the years, where new concepts have emerged; one of these is the digital twin. There are different definitions of what a digital twin is. This study defines a digital twin as a virtual representation of a physical object that automatically transfers real-time data; if one of the states is altered, the other state should change. Therefore, the study aims to investigate the different applications of a digital twin, specifically in a battery manufacturing organization. Furthermore, it also gives an overview of the digital twin concept and its applications, where benefits, challenges, technologies, and data are investigated. In order to narrow and delimit the research, the primary focus has been on the assembly line, where both a manufacturing and sustainability perspective have been investigated. The research question has thus been “How could a digital twin be utilized in a fast-growing battery manufacturing firm?". With an inductive approach, both primary and secondary data have been collected through interviews and literature studies. Methods utilized for the research have been conducting, transcribing and coding the interviews. The results indicated that the technology is considered new and there are many different applications of a digital twin. Therefore, a firm needs to benchmark with other organization and lock down the digital twin's purpose before developing it. Applications recognized were visualization, measuring manufacturing KPIs as well as recording material for the material declaration of the products, to calculate the carbon footprint, and measuring the energy consumption of the machines. Depending on the purpose and application of the digital twin, the firm will know what data needs to be collected and what software is most suitable. / Sedan några år tillbaka har en ökning i batteriindustrin och marknaden observerats. För närvarande är asiatiska länder de ledande inom tillverkning av batterier. Dock försöker också andra länder etablera närvaro i batterimarknaden genom att bli en stabil tillverkningskonkurrent av batterier, ett av dessa länder är Sverige. En av de drivande faktorerna bakom ökningen av batterianvändning är ökningen av hållbarhetsmedvetenheten. Med introduktionen av Industri 4.0 har digitalisering blivit populärt inom olika industrier och företag, vilket har lett till att nya koncept dykt upp, ett av dessa koncept är digital tvilling. Det finns flera definitioner på vad en digital tvilling innebär. I denna studien är en digital tvilling en virtuell representation av ett fysiskt objekt som överför realtidsdata automatisk, om något ändras i ena objektet då ändras det i det andra också. Syftet med studien är därför att undersöka de olika tillämpningarna för en digital tvilling, särskilt för en organisation som tillverkar batterier. Denna rapporten visar en översikt över konceptet digital tvilling och dess tillämpningar, dess fördelar och utmaningar, teknologier och data som behövs. För att avgränsa forskningen har det primära fokus legat på produktionslinan, där både ett tillverknings- och hållbarhetsperspektiv har undersökts. Forskningsfrågan har alltså varit "Hur skulle en digital tvilling kunna användas i ett snabbväxande företag som tillverkar batterier?". Med ett induktivt tillvägagångsätt har både primär- och sekundärdata samlats in, i form av intervjuer och en litteraturstudie. Metoder som använts för forskningen har varit att genomföra, transkribera och koda intervjuerna. Resultaten indikerade att teknologin anses vara ny och det finns många olika applikationer av Digital Tvilling. Därmed behöver ett företag analysera hur en digital tvilling används i andra företag. Därför måste företaget låsa in syftet med den digitala tvillingen innan den börjar utvecklas. Applikationer som påträffades var visualisering för mätning av tillverknings-KPI:er samt registrering av material för materialdeklarationer av produkterna, för att beräkna koldioxidavtrycket, samt mätning av maskinernas energiförbrukning. Beroende på syftet och tillämpningen av den digitala tvillingen kommer företaget att veta vilken data som behöver samlas in och vilken programvara som är mest lämplig.