Die Dynamik in der Produktentwicklung und die zunehmende Bedeutung von Flexibilität in der Produktion prägen die heutige Wirtschaftslandschaft, insbesondere für Unternehmen in der Prozessund Güterindustrie. Die Antwort auf die wachsenden Anforderungen an die modulare Produktion in der Prozessindustrie kommt aus der Zusammenarbeit der deutschen Interessengemeinschaft Automatisierungstechnik der Prozessindustrie (NAMUR) und dem Zentralverband Elektrotechnik- und Elektronikindustrie (ZVEI) [1]. Gemeinsam erarbeiten sie eine Spezifikation für Prozessmodule unter dem Namen Module Type Package (MTP). Parallel dazu treibt die Plattform Industrie 4.0 die Entwicklung der Verwaltungsschale (VWS) voran und die Industrial Digital Twin Association (IDTA) entwickelt Spezifikationen, um ein gemeinsames Verständnis der Verwaltungsschale zu schaffen [2][3]. In dieser Arbeit soll ausgehend von [4] der Automatisierungsgrad eines Dampferzeugers erhöht werden, indem ein Konzept entwickelt werden soll, dass eine nahtlose Interaktion zwischen den Themen MTP und VWS unter Berücksichtigung der Namur Open Architecture (NOA) [5] ermöglichen soll.

The new Industry 4.0 technologies have the potential to increase the operational performance of lean-driven manufacturing organizations, however, there is a lack of guidance on how to select and implement Industry 4.0 technologies which often leads to digital waste. In essence, these organizations want to preserve the value of their current lean manufacturing system, without missing out on improved operational performance potential from exploiting new I4.0 technologies. Furthermore, recent research suggests that there is a complementary effect between lean manufacturing and Industry 4.0 where higher use of both domains in a factory results in higher operational performance. However, in theory, it has not been established what influencing factors lead to the increase in operational performance when the two domains, lean manufacturing and Industry 4.0, are in high concurrent use. The purpose of this study is to identify the influencing factors in the implementation process of Industry 4.0 technologies that facilitate higher Industry 4.0 maturity within factories. In this case study, a qualitative method was used to obtain the empirical data by conducting a series of interviews with individuals working in a multi-national lean-driven manufacturing organization. From a thematic analysis, seven influencing factors were identified that contributed to higher Industry 4.0 maturity: three in the governance structure, two in the selection of Industry 4.0 technologies, and two in the implementation of Industry 4.0 technologies. In the governance structure, a shared digital vision, following a roadmap, and a standardized way of working with digitalization in place facilitated a more successful implementation process. In the selection, a demand-based selection and identification of a business case around the Industry 4.0 technology increased the possibility of the technology selected reaching an implementation stage. Further, in the implementation, having local cross-functional teams and actively developing the employees' knowledge, and providing training in digitalization resulted in more successful implementations. Further, a ripple effect was seen between the influencing factors: having an effective governance structure led to more demand-based selections and thereby more successful implementations that resulted in higher Industry 4.0 maturity. / De nya industri 4.0 teknologierna har potentialen att öka de operativa resultaten inom lean-drivna industriföretag, men det saknas vägledning för hur man väljer och implementerar industri 4.0 teknologier vilket oftast resulterar i digitalt slöseri. Industriföretagen vill bevara värdet av de lean-drivna tillverkningssystemen utan att gå miste om förbättrade resultat med hjälp av industri 4.0. Dessutom tyder den senaste forskningen på att det finns en kompletterande effekt mellan lean produktion och industri 4.0 teknologier, där högre användning av båda domänerna i en fabrik resulterar i bättre operativa resultat. I teorin har det dock inte fastställts vilka de påverkande faktorerna är som leder till ett förbättrat operativt resultat när de två domänerna, lean-produktion och industri 4.0, används i hög grad samtidigt. Syftet med studien är att identifiera vilka de påverkande faktorerna är i implementeringsprocessen av industri 4.0 teknologier som främjar en högre mognadsgrad av industri 4.0 i tillverkningsfabriker. I fallstudien användes en kvalitativ metod för att erhålla empirin genom att utföra en serie av intervjuer med individer som arbetar på ett multinationellt lean-drivet industriföretag. Utifrån en tematisk analys identifierades sju påverkande faktorer som bidrog till en högre mognadsgrad av industri 4.0: tre i styrningsstrukturen, två i valet av industri 4.0 teknologier och två i implementeringen av industri 4.0 teknologier. I styrningsstrukturen återfanns att en delad vision, att följa en roadmap och att ha ett standardiserat arbetssätt för digitalisering främjade en mer framgångsrik implementeringsprocess. Inom valet av teknologier återfanns att ett val baserat på efterfrågan och generering av ett business case för industri 4.0 teknologier ökade möjligheten för den valda teknologin att nå en implementeringsfas. Till sist, i implementeringsfasen visade det sig att lokala tvärfunktionella team och att aktivt utveckla medarbetarnas kunskaper, samt att ge utbildning i digitalisering, resulterade i mer framgångsrika implementeringar. Slutligen sågs en kedjeeffekt mellan de påverkande faktorerna, nämligen att ha en effektiv styrningsstruktur ledde till fler val baserade på efterfrågan och därmed fler framgångsrika implementeringar vilket resulterade i en högre mognadsgrad av industri 4.0.

This thesis describes the implementation of a Digital Twin tied to Virtual Reality environment thatcould, by easy means be expanded to Augmented Reality-solution. The field is of interest due to thefact that movement into Industry 4.0 puts the traditional operator in a new seat of work. Previoushands-on tasks are replaced with system monitoring and supervision roles. New interconnectedindustrial hardware allows for extensive data collection, while interactive technology like VR/ARhelps monitoring live systems in completely new manners. An operator can overview and debugindustrial systems while not even being in close proximity of the physical system. This provides theopportunity to increase the level of system information presented to the operator. The Cyber PhysicalFactory created by Festo was targeted to be represented as a digital twin. The question asked: What arethe advantages and/or disadvantages of monitoring and troubleshooting a Festo CP-Factory by meansof a digital twin-driven visualization? proved to be extensive and the work included mapping ofimportant factory data and DRM-research to find visual improvements between the provided solutionsby Festo, and an implemented digital twin. The solution we produced focuses on overview anddebugging and it connects to OPC-servers on each mapped module of the Cyber Physical Factory andacquires the data. This data can then be used to expand, test and debug previous sessions. Each realimplementation of a factory has some type of logging of data, our solution allows visualization of thoselog entries as close to reality as possible, reducing the need to search databases for indications ofproblems. The Unity 3D created software also handles dynamic connections where the operator canmodify which nodes to connect to in an intuitive way, this enables our software to abstract and modifyinformation outside of the source code.

The study investigates potential of promising combination of Lean principles and Industry 4.0 tools in order to find a solution for control of manufacturing process. Firstly, each of the buzzwords is defined and their relation is explained. Then, rules which will facilitate implementation of I4.0 tools into Lean production are enumerated. Afterwards, situation at the shopfloor is observed and statistical analysis of production data is done to analyze current manufacturing process. Deep investigation revealed strong potential for improvement, which was the motive to elaborate a proposal for Lean automated process control.

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