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In the context of Industry 4.0, intralogistics faces an increasingly complex and dynamic environment driven by a high level of product customisation and complex manufacturing processes. One approach to deal with these changing conditions is the decentralised and intelligent connectivity of intralogistics systems. However, wireless connectivity presents a major challenge in the industry due to strict requirements such as safety and real-time data transmission. In this context, the fifth generation of mobile communications (5G) is a promising technology to meet the requirements of safety-critical applications. Particularly, since 5G offers the possibility of establishing private 5G networks, also referred to as standalone non-public networks. Through their isolation from public networks, private 5G networks provide exclusive coverage for private organisations offering them high intrinsic network control and data security. However, 5G is still under development and is being gradually introduced in a continuous release process. This process lacks transparency regarding the performance of 5G in individual releases, complicating the successful adoption of 5G as an industrial communication. Additionally, the evaluation of 5G against the specified target performance is insufficient due to the impact of the environment and external interfering factors on 5G in the industrial environment. Therefore, this paper aims to develop a technical decision-support framework that takes a holistic approach to evaluate the practicality of 5G for intralogistics use cases by considering two fundamental stages. The first of these analyses technical parameters and characteristics of the use case to evaluate the theoretical feasibility of 5G. The second stage investigates the application's environment, which substantially impacts the practicality of 5G, for instance, the influence of surrounding materials. Finally, a case study validates the proposed framework by means of an autonomous mobile robot. As a result, the validation proves the proposed framework's applicability and shows the practicality of the autonomous mobile robot, when integrating it into a private 5G network testbed.
The fifth generation of mobile communication (5G) is a wireless technology developed to provide reliable, fast data transmission for industrial applications, such as autonomous mobile robots and connect cyber-physical systems using Internet of Things (IoT) sensors. In this context, private 5G networks enable the full performance of industrial applications built on dedicated 5G infrastructures. However, emerging wireless communication technologies such as 5G are a complex and challenging topic for training in learning factories, often lacking physical or visual interaction. Therefore, this paper aims to develop a real-time performance monitoring system of private 5G networks and different industrial 5G devices to visualise the performance and impact factors influencing 5G for students and future connectivity experts. Additionally, this paper presents the first long-term measurements of private 5G networks and shows the performance gap between the actual and targeted performance of private 5G networks.
Mobile assistance systems (MAS) promise to overcome personnel shortages in operating theatres worldwide. A literature review inspired by the PRISMA 2020 method determines the state of the art of MAS, and identifies a lack of application areas for MAS in the operating theatre. Interviews with subject-matter experts aim to investigate application areas for MAS. The results show that most operational tasks refer to material management and patient management. MAS, with their potential to reduce the time needed for material and patient management, and the physical and mental strain of patient management, have great potential in the operating theatre.
5G-Campusnetze sind vielversprechende Umgebungen für industrielle Anwendungen in Produktion und Intralogistik. Diese erreichen jedoch bisher nicht die versprochenen Leistungen, um intralogistischen Anwendungen das volle Potenzial von 5G bieten zu können. Die im Rahmen des Projekts 5G4KMU erhobenen und in diesem Beitrag vorgestellten Leistungsmessungen dienen zur Evaluierung der derzeitigen Praxistauglichkeit von 5G-Campusnetzen.
Global trade is plagued by slow and inefficient manual processes associated with physical documents. Firms are constantly looking for new ways to improve transparency and increase the resilience of their supply chains. This can be solved by the digitalisation of supply chains and the automation of document- and information-sharing processes. Blockchain is touted as a solution to these issues due to its unique combination of features, such as immutability, decentralisation and transparency. A lack of business cases that quantify the costs and benefits causes uncertainty regarding the truth of these claims. This paper explores how the costs and benefits of a blockchain-based solution for digitalising and automating documentation flows in cross-border supply chains compare to a conventional centralised relational database solution. The research described in this paper uses primary data collected through semi-structured interviews with industry experts, as well as secondary data from literature. Two models based on existing services were developed and the costs and benefits compared and then analysed using the Architecture Trade-off Analysis Method (ATAM) and the Analytic Network Process (ANP). Findings from the analysis show that a consortium blockchain solution like TradeLens is the favourable solution for digitalising and automating information flows in cross-border supply chains.
Um sich in einem schnelllebigen und globalen Markt nachhaltig wettbewerbsfähig aufzustellen, bedarf es innovativer Ansätze, Produkte sichtbar zu machen. Vorreiter wie Apple oder Microsoft stehen mit ihren Marketingstrategien und der Präsentation ihrer Produkte für eine neue Denkweise. Doch wie kann ein klein- oder mittelständiges Unternehmen (KMU) mit solchen Strategien konkurrieren und sich und die eigenen Produkte am Markt erfolgreich platzieren? Der vorliegende Beitrag zeigt auf, wie ein Markteinführungskonzept mithilfe des Design-Thinking-Ansatzes auf Basis der Kundenbedürfnisse modular und skalierbar ausgestaltet werden kann, um auf die jeweiligen Anforderungen des einzuführenden Produktes adaptierbar zu sein.
The blockchain technology represents a decentralised database that stores information securely in immutable data blocks. Regarding supply chain management, these characteristics offer potentials in increasing supply chain transparency, visibility, automation, and efficiency. In this context, first token-based mapping approaches exist to transfer certain manufacturing processes to the blockchain, such as the creation or assembly of parts as well as their transfer of ownership. This paper proposes a prototypical blockchain application that adopts an authority concept and a concept of smart non-fungible tokens. The application enables the mapping of complex products in dynamic supply chains that require the auditability of changeable assembling processes on the blockchain. Finally, the paper demonstrates the practical feasibility of the proposed application based on a prototypical implementation created on the Ethereum blockchain.
The fifth mobile communications generation (5G) can lead to a substantial change in companies enabling the full capability of wireless industrial communication. 5G with its key features of providing Enhanced Mobile Broadband, Ultra-Reliable and Low-Latency Communication, and Massive Machine Type Communication will support the implementation of Industry 4.0 applications. In particular, the possibility to set-up Non-Public Networks provides the opportunity of 5G communication in factories and ensures sole access to the 5G infrastructure offering new opportunities for companies to implement innovative mobile applications. Currently there exist various concepts, ideas, and projects for 5G applications in an industrial environment. However, the global rollout of 5G systems is a continuous process based on various stages defined by the global initiative 3rd Generation Partnership Project that develops and specifies the 5G telecommunication standard. Accordingly, some services are currently still far from their final performance capability or not yet implemented. Additionally, research lacks in clarifying the general suitability of 5G regarding frequently mentioned 5G use cases. This paper aims to identify relevant 5G use cases for intralogistics and evaluates their technical requirements regarding their practical feasibility throughout the upcoming 5G specifications.
Supply chains have evolved into dynamic, interconnected supply networks, which increases the complexity of achieving end-to-end traceability of object flows and their experienced events. With its capability of ensuring a secure, transparent, and immutable environment without relying on a trusted third party, the emerging blockchain technology shows strong potential to enable end-to-end traceability in such complex multitiered supply networks. This paper aims to overcome the limitations of existing blockchain-based traceability architectures regarding their object-related event mapping ability, which involves mapping the creation and deletion of objects, their aggregation and disaggregation, transformation, and transaction, in one holistic architecture. Therefore, this paper proposes a novel ‘blueprint-based’ token concept, which allows clients to group tokens into different types, where tokens of the same type are non-fungible. Furthermore, blueprints can include minting conditions, which, for example, are necessary when mapping assembly processes. In addition, the token concept contains logic for reflecting all conducted object-related events in an integrated token history. Finally, for validation purposes, this article implements the architecture’s components in code and proves its applicability based on the Ethereum blockchain. As a result, the proposed blockchain-based traceability architecture covers all object-related supply chain events and proves its general-purpose end-to-end traceability capabilities of object flows.
The purpose of this paper sought to develop a collaborative framework that provides wine bottling facilities, wine cellars and their direct supply chain partner guidelines to facilitate a collaborative partnership – aiming to aid responsive decision making and improve reliability. The framework was developed using a triangulation approach, consisting of an in-depth literature review, 14 semi-structured interviews with industry experts and a theoretical case study. The developed framework was presented to wine bottling facilities and their supply chain stakeholders. Indication are that the proposed wine industry collaborative framework should enhance supply chain collaboration and will contribute towards the guidance and facilitation in developing collaboration platforms to align supply chain operations, while improving bottling responsiveness and meeting demand requirements.
Recently, blockchain-based tokens have earned an important role in fields such as the art market or online gaming. First approaches exist, which adopt the potentials of blockchain tokens in supply chain management to increase transparency, visibility, automation, and disintermediation of supply chains. In context, the tokenization of assets in supply chains refers to the practice of creating virtual representations of physical assets on the blockchain. Solutions in supply chain management based on the tokenization of assets vary in terms of application objectives, token types, asset characteristics, as well as the complexities of supply chain events to be mapped on the blockchain. Currently, however, no review exists that summarizes the characteristics of blockchain-based tokens and their scope of applications. This paper provides a clear terminological distinction of existing blockchain token types and therefore distinguishes between fungible tokens, non-fungible tokens, smart non-fungible tokens, and dynamic smart non-fungible tokens. Subsequently, the token types are classified regarding their traceability, modifiability, and authorization to evaluate suitability for mapping assets in supply chains. Given the potential of blockchain in supply chain management, the results of the review serve as a foundation for a practical guide supporting the selection process of suitable token types for industrial applications.
Blockchain is a technology for the secure processing and verification of data transactions based on a distributed peer-to-peer network that uses cryptographic processes, consensus algorithms, and backward-linked blocks to make transactions virtually immutable. Within supply chain management, blockchain technology offer potentials in increasing supply chain transparency, visibility, automation, and efficiency. However, its complexity requires future employees to have comprehensive knowledge regarding the functionality of blockchain-based applications in order to be able to apply their benefits to scenarios in supply chain and production. Learning factories represent a suitable environment allowing learners to experience new technologies and to apply them to virtual and physical processes throughout value chains. This paper presents a concept to practically transfer knowledge about the technical functionality of blockchain technology to future engineers and software developers working within supply chains and production operations to sensitize them regarding the advantages of decentralized applications. First, the concept proposes methods to playfully convey immutable backward-linked blocks and the embedment of blockchain smart contracts. Subsequently, the students use this knowledge to develop blockchain-based application scenarios by means of an exemplary product in a learning factory environment. Finally, the developed solutions are implemented with the help of a prototypical decentralized application, which enables a holistic mapping of supply chain events.
The fifth mobile communications generation (5G) offers the deployment scenario of licensed 5G standalone non-public networks (NPNs). Standalone NPNs are locally restricted 5G networks based on 5G New Radio technology which are fully isolated from public networks. NPNs operate on their dedicated core network and offer organizations high data security and customizability for intrinsic network control. Especially in networked and cloud manufacturing, 5G is seen as a promising enabler for delay-sensitive applications such as autonomous mobile robots and robot motion control based on the tactile internet that requires wireless communication with deterministic traffic and strict cycling times. However, currently available industrial standalone NPNs do not meet the performance parameters defined in the 5G specification and standardization process. Current research lacks in performance measurements of download, upload, and time delays of 5G standalone-capable end-devices in NPNs with currently available software and hardware in industrial settings. Therefore, this paper presents initial measurements of the data rate and the round-trip delay in standalone NPNs with various end-devices to generate a first performance benchmark for 5G-based applications. In addition, five end-devices are compared to gain insights into the performance of currently available standalone-capable 5G chipsets. To validate the data rate, three locally hosted measurement methods, namely iPerf3, LibreSpeed and OpenSpeedTest, are used. Locally hosted Ping and LibreSpeed have been executed to validate the time delay. The 5G standalone NPN of Reutlingen University uses licensed frequencies between 3.7-3.8 GHz and serves as the testbed for this study.
Towards a model for holistic mapping of supply chains by means of tracking and tracing technologies
(2022)
The usage of tracking and tracing technologies not only enables transparency and visibility of supply chains but also offers far-reaching advantages for companies, such as ensuring product quality or reducing supplier risks. Increasing the amount of shared information supports both internal and external planning processes as well as the stability and resilience of globally operating value chains. This paper aims to differentiate and define the functionalities of tracking and tracing technologies that are frequently used interchangeably in literature. Furthermore, this paper incorporates influencing factors impacting a sequencing of the connected world in Industry4.0 supply chain networks. This includes legal influences, the embedment of supply chain-related standards, and new possibilities of emerging technologies. Finally, the results are summarized in a model for the holistic mapping of supply chains by means of tracking and tracing technologies. The resulting technological solutions that can be derived from the model enable companies to address missing elements in order to enable the holistic mapping of supply chain events as well as the transparent representation of a digital shadow throughout the entire supply chain.
The proper selection of a demand forecasting method is directly linked to the success of supply chain management (SCM). However, today’s manufacturing companies are confronted with uncertain and dynamic markets. Consequently, classical statistical methods are not always appropriate for accurate and reliable forecasting. Algorithms of Artificial intelligence (AI) are currently used to improve statistical methods. Existing literature only gives a very general overview of the AI methods used in combination with demand forecasting. This paper provides an analysis of the AI methods published in the last five years (2017-2021). Furthermore, a classification is presented by clustering the AI methods in order to define the trend of the methods applied. Finally, a classification of the different AI methods according to the dimensionality of data, volume of data, and time horizon of the forecast is presented. The goal is to support the selection of the appropriate AI method to optimize demand forecasting.
The blockchain technology represents a decentralized database that stores information securely in immutable data blocks. Regarding supply chain management, these characteristics offer potentials in increasing supply chain transparency, visibility, automation, and efficiency. In this context, first token-based mapping approaches exist to transfer certain manufacturing processes to the blockchain, such as the creation or assembly of parts as well as their transfer of ownership. However, the decentralized and immutable structure of blockchain technology also creates challenges when applying these token-based approaches to dynamic manufacturing processes. As a first step, this paper investigates existing mapping approaches and exemplifies weaknesses regarding their suitability for products with changeable configurations. Secondly, a concept is proposed to overcome these weaknesses by introducing logically coupled tokens embedded into a flexible smart contract structure. Finally, a concept for a token-based architecture is introduced to map manufacturing processes of products with changeable configurations.
Today's logistics systems are characterized by uncertainty and constantly changing requirements. Rising demand for customized products, short product life cycles and a large number of variants increases the complexity of these systems enormously. In particular, intralogistics material flow systems must be able to adapt to changing conditions at short notice, with little effort and at low cost. To fulfil these requirements, the material flow system needs to be flexible in three important parameters, namely layout, throughput and product. While the scope of the flexibility parameters is described in literature, the respective effects on an intralogistics material flow system and the influencing factors are mostly unknown. This paper describes how flexibility parameters of an intralogistics system can be determined using a multi-method simulation. The study was conducted in the learning factory “Werk150” on the campus of Reutlingen University with its different means of transport and processes and validated in terms of practical experiments.
Classification model of supply chain events regarding their transferability to blockchain technology
(2021)
The blockchain technology represents a decentralized database that stores information securely in immutable data blocks. Regarding supply chain management, these characteristics offer potentials in increasing supply chain transparency, visibility, automation, and efficiency. In this context, first token-based mapping approaches exist to transfer certain supply chain events to the blockchain, such as the creation or assembly of parts as well as their transfer of ownership. However, the decentralized and immutable structure of blockchain technology also creates challenges. In particular, the scalability, storage capacity, and the special requirements for storage formats make it currently impossible to map all supply chain events unrestrictedly on the blockchain. As a first step, this paper identifies important supply chain events for different use cases combining blockchain technology and supply chain management. Secondly, the supply chain events are classified in terms of their expected technical properties and their relevance for the respective use case. Finally, the identified supply chain events are evaluated regarding their transferability to blockchain technology and a classification model is introduced.
The seamless fusion of the virtual world of information with the real physical world of things is considered the key for mastering the increasing complexity of production networks in the context of Industry 4.0. This fusion, widely referred to as the Internet of Things (IoT), is primarily enabled through the use of automatic identification (Auto-ID) technologies as an interface between the two worlds. Existing Auto-ID technologies almost exclusively rely on artificial features or identifiers that are attached to an object for the sole purpose of identification. In fact, using artificial features for the purpose of identification causes additional efforts and is not even always applicable. This paper, therefore, follows an approach of using multiple natural object features defined by the technical product information from computer-aided design (CAD) models for direct identification. By extending optical instance-level 3D-Object recognition by means of additional non-optical sensors, a multi-sensor automatic identification system (AIS) is realised, capable of identifying unpackaged piece goods without the need for artificial identifiers. While the implementation of a prototype confirms the feasibility of the approach, first experiments show improved accuracy and distinctiveness in identification compared to optical instance-level 3D-Object recognition. This paper aims to introduce the concept of multisensor identification and to present the prototype multi-sensor AIS.
Distributed ledger technologies such as the blockchain technology offer an innovative solution to increase visibility and security to reduce supply chain risks. This paper proposes a solution to increase the transparency and auditability of manufactured products in collaborative networks by adopting smart contract-based virtual identities. Compared with existing approaches, this extended smart contract-based solution offers manufacturing networks the possibility of involving privacy, content updating, and portability approaches to smart contracts. As a result, the solution is suitable for the dynamic administration of complex supply chains.
Supply chains have become increasingly complex, making it difficult to ensure transparency throughout the whole supply chain. In this context, first approaches came up, adopting the immutable, decentralised, and secure characteristics of the blockchain technology to increase the transparency, security, authenticity, and auditability of assets in supply chains. This paper investigates recent publications combining the blockchain technology and supply chain management and classifies them regarding the complexity to be mapped on the blockchain. As a result, the increase of supply chain transparency is identified as the main objective of recent blockchain projects in supply chain management. Thereby, most of the recent publications deal with simple supply chains and products. The few approaches dealing with complex parts only map sub-areas of supply chains. Currently no example exists which has the aim of increasing the transparency of complex manufacturing supply chains, and which enables the mapping of complex assembly processes, an efficient auditability of all assets, and an implementation of dynamic adjustments.
Die Blockchain-Technologie stellt einen vielversprechenden Ansatz für Transparenz und Resilienz in Lieferketten dar. In diesem Beitrag wird untersucht, welche Blockchain-Lösungen derzeit für die Supply-Chain zur Verfügung stehen, und die bislang umgesetzten Projekte in diesem Bereich analysiert. Die meisten der realisierten Projekte beziehen sich auf einfache Produkte und Supply-Chain-Strukturen. Der Grund ist, dass bislang Lösungen zur ganzheitlichen Abbildung von komplexen Produkten in dynamischen Supply-Chain-Strukturen gefehlt haben. Doch jetzt stehen erste vielversprechende Ansätze zur Verfügung.
Digitalization changes the manufacturing dramatically. In regard of employees’ demands, global trends and the technological vision of future factories, automotive manufacturing faces a huge number of diverse challenges. Currently, research focuses on technological aspects of future factories in terms of digitalization. New ways of work and new organizational models for future factories have not been described yet. There are assumptions on how to develop the organization of work in a future factory but up to now, literature shows deficits in scientifically substantiated answers in this research area. Consequently, the objective of this paper is to present an approach on a work organization design for automotive Industry 4.0 manufacturing. Future requirements were analyzed and deducted to criteria that determine future agile organization design. These criteria were then transformed into functional mechanisms, which define the approach for shopfloor organization design
Globalisation, shorter product life cycles, and increasing product varieties have led to complex supply chains. At the same time, there is a growing interest of customers and governments in having a greater transparency of brands, manufacturers, and producers throughout the supply chain. Due to the complex structure of collaborative manufacturing networks, the increase of supply chain transparency is a challenge for manufacturing companies. The blockchain technology offers an innovative solution to increase the transparency, security, authenticity, and auditability of products. However, there are still uncertainties when applying the blockchain technology to manufacturing scenarios and thus enable all stakeholders to trace back each component of an assembled product. This paper proposes a framework design to increase the transparency and auditability of products in collaborative manufacturing networks by adopting the blockchain technology. In this context, each component of a product is marked with a unique identification number generated by blockchain-based smart contracts. In this way, a transparent auditability of assembled products and their components can be achieved for all stakeholders, including the custome.
Companies are becoming aware of the potential risks arising from sustainability aspects in supply chains. These risks can affect ecological, economic or social aspects. One important element in managing those risks is improved transparency in supply chains by means of digital transformation. Innovative technologies like blockchain technology can be used to enforce transparency. In this paper, we present a smart contract-based Supply Chain Control Solution to reduce risks. Technological capabilities of the solution will be compared to a similar technology approach and evaluated regarding their benefits and challenges within the framework of supply chain models. As a result, the proposed solution is suitable for the dynamic administration of complex supply chains.
Der Anteil mittelständischer Unternehmen, die Standorte im Ausland unterhalten, nimmt seit einigen Jahren zu. Oft finden Auslandsaktivitäten dieser Art in Niedriglohnländern statt. Dort ergeben sich u.a durch die infrastrukturellen Gegebenheiten und durch die verfügbaren Personalressourcen diverse Herausforderungen, insbesondere für die Produktivitätsermittlung und -bewertung innerhalb der Produktion. Dieser Beitrag soll für diese Herausforderungen geeignete Technologien und eine mögliche Vorgehensweise für deren Auswahl vor dem Hintergrund der ländertypischen Herausforderungen aufzeigen.
Der Digitale Zwilling ist ein Technologie-Trendthema mit großen Potenzialen in einer Vielzahl von Anwendungsbereichen – insbesondere für produzierende Unternehmen. Eine Studie des Reutlinger Zentrums Industrie 4.0 beschäftigt sich mit heutigen und zukünftigen Anwendungsmöglichkeiten von Digitalen Zwillingen und gibt Impulse für eine schrittweise Implementierung im Unternehmen.
Because of saturated markets and of the low profit margins in the sales of cars, car manufacturers focus more and more on profitable product related services. This paper deals with the question how to classify product related services in the automotive industry and which characteristic product related services are offered to the end-users (consumers) in a standardized format. Two research studies on the provided product related services in 2010 und 2017 by 15 car manufacturers and 20 exemplary automotive brands in Germany revealed that the application degree by the OEM (original equipment manufacturers) in these years increased considerably. While in 2010, the average range of services only amounted to 33%, the value in the automotive industry increased until 2017 to 57%.
In der zunehmenden Individualisierung von Produkten zeigt sich, dass Kundennähe und digital vernetzte Zusammenarbeit aller Partner wertvolle Erfolgspotenziale darstellen. Für komplexe Kundenauftragsprozesse gilt es, zu vernetzen und die Prozesse und Systeme in Form eines ganzheitlichen Ansatzes zukunftsfähig zu gestalten. Dabei wird der Herausforderung begegnet, Daten und Dokumente zu digitalisieren und den manuellen Aufwand zu reduzieren. Der Untersuchungsgegenstand ist der Abwicklungsprozess, ausgehend von einer Online-Konfiguration durch den Kunden bis zur Bestellabwicklung. In diesem Beitrag wird ein Vorgehensmodell aufgezeigt, das Unternehmen in die Lage versetzt, ihren Kundenauftragsprozess durch ein digitales Geschäftsmodell zukunftsfähig auszugestalten. Nutzenpotenziale sind eine verstärkte Kundenbindung durch eng verzahnte digitale Kollaboration, verstärkte Wirtschaftlichkeit durch Reduktion der Prozesskosten sowie eine Optimierung der Customer Experience durch effiziente Abläufe.
Indoor localization systems are becoming more and more important with the digitalization of the industrial sector. Sensor data such as the current position of machines, transport vehicles, goods or tools represent an essential component of cyber physical production systems (CCPS). However, due to the high costs of these sensors, they are not widespread and are used mainly in special scenarios. However, especially optical indoor positioning systems (OIPS) based on cameras have certain advantages due to their technological specifications. In this paper, the application scenarios and requirements as well as their characteristics are presented and a classification approach of OIPS is introduced.
The paper describes a new stimulus using learning factories and an academic research programme - an M.Sc. in Digital Industrial Management and Engineering (DIME) comprising a double degree - to enhance international collaboration between four partner universities. The programme will be structured in such a way as to maintain or improve the level of innovation at the learning factories of each partner. The partners agreed to use Learning Factory focus areas along with DIME learning modules to stimulate international collaboration. Furthermore, they identified several research areas within the framework of the DIME program to encourage horizontal and vertical collaboration. Vertical collaboration connects faculty expertise across the Learning Factory network to advance knowledge in one of the focus areas, while Horizontal collaboration connects knowledge and expertise across multiple focus areas. Together they offer a platform for students to develop disciplinary and cross-disciplinary applied research skills necessary for addressing the complex challenges faced by industry. Hence, the university partners have the opportunity to develop the learning factory capabilities in alignment with the smart manufacturing concept. The learning factory is thus an important pillar in this venture. While postgraduate students/researchers in the DIME program are the enablers to ensure the success of entire projects, the learning factory provides a learning environment which is entirely conducive to fostering these successful collaborations. Ultimately, the partners are focussed on utilising smart technologies in line with the digitalization of the production process.
What does the factory of tomorrow have to offer for companies? This question and its aspects are the focus of many actual articles and publications. According to Gartner digital twins, one of 2017 strategic technology trends will play a big role for the future of manufacturing. At the moment digital twins are gaining more importance for the industrial application. If companies want to be competitive in the future they have to implement the digital twin in the factories of today. Therefore this paper provides a basic overview of the concept of the smart factory and its requirements. In addition, digital twins are identified as a necessary concept for the evolution of the factory of today.
Zur Entwicklung einer Sofortpreiskalkulation für CNC-Drehteile werden Machine-Learning-Ansätze sowie ein deterministischer Algorithmus untersucht. Der deterministische Algorithmus funktioniert ausschließlich für Drehteile mit geringer Komplexität. Die Machine Learning Modelle hingegen sind zukunftsfähiger, da die ersten Ergebnisse bereits sehr geringe Abweichungswerte zu den festgelegten Referenzpreisen erreichen können. Mit steigendem Datenaufkommen können beide Machine-Learning-Modelle mit geringem Aufwand weiter verbessert werden.
Der Einsatz von Data Science in der Produktion ermöglicht eine neue Art der Optimierung von Prozessen und Systemen. Die Bedeutung der datengetriebenen Produktionsoptimierung wächst zunehmend im produzierenden Gewerbe. Im Gegensatz zu konventionellen Ansätzen, wie z. B. die des Lean Managements, basiert dieser anhaltende Trend auf der steigenden Verfügbarkeit von Daten im Zuge der digitalen Transformation. Vor allem kleine und mittlere Unternehmen stehen vor der Herausforderung abzuwägen, welche Maßnahmen hierfür ergriffen werden sollten und welche Nutzenpotenziale sich daraus ergeben. Diese Arbeit stellt einen strukturierten Leitfaden zur Vorgehensweise bei Datenanalyseprojekten bezogen auf einen spezifischen Anwendungsfall im Kontext einer frühen Fehlerdetektion und -prävention dar.
Zukünftige Montagearbeitsplätze müssen veränderten Herausforderungen, wie z. B. der zunehmenden Anzahl von Mensch Roboter-Kollaborationen, gerecht werden. Die Virtual Reality (VR)-Technik bietet im Rahmen der Arbeitsplatzgestaltung neue Möglichkeiten, diesen veränderten Planungsherausforderungen gerecht zu werden. Die Ausarbeitung stellt eine Methode zur Bewertung des sinnvollen Einsatzes der VR-Technik für einen spezifischen Arbeitsplatz vor. Außerdem wird aufgezeigt, wie die VR-Technik in den Prozess der Arbeitsplatzgestaltung integriert werden kann.
Der Zusammenschluss von Unternehmen in Lieferantennetzwerken auf Basis digitaler Plattformen bietet eine Möglichkeit, der Forderung nach Flexibilität in der Industrie 4.0 nachzukommen. Anhand der Charakterisierung eines realen Lieferantennetzwerkes werden use cases für die Lieferantenanbindung hergeleitet. Diese dienen als Diskussionsgrundlage von Potenzialen und Herausforderungen der Anbindung, wobei sich die Frage nach der optimalen Integrationstiefe stellt. Hierzu wurde ein anwenderorientiertes Entscheidungsmodell abgeleitet.
Angesichts des breiten Angebotsspektrums neuer Technologien und der Vielzahl verschieden verwendeter Begriffe rund um Industrie 4.0, stehen Unternehmen nicht selten orientierungslos vor der Herausforderung, individuelle Umsetzungsstrategien abzuleiten. Das vorliegende Reifegradmodell ermöglicht die Erfassung bereits im Produktionssystem implementierter Lean Management-Prinzipien und gibt praktikable Antworten auf die evolutionären Visionen, indem es realisierbare und individuelle Migrationspfade in Richtung Industrie 4.0 für Unternehmen aufzeigt.
Digitisation forms a part of Industrie 4.0 and is both threatening, but also providing an opportunity to transform business as we know it; and can make entire business models redundant. Although companies might realise the need to digitise, many are unsure of how to start this digital transformation. This paper addresses the problems and challenges faced in digitisation, and develops a model for initialising digital transformation in enterprises. The model is based on a continuous improvement cycle, and also includes triggers for innovative and digital thinking within the enterprise. The model was successfully validated in the German service sector.
Efficiency in supply chain risk management (SCRM) is a major topic in industries with serial production and a complex supply chain due to limited management and financial resources. A high number of possible risk situations and intertwined processes create a more challenging environment for resource allocation. Managers cannot perform SCRM in all possible supply chain areas and hence have to decide where available resources should be utilised for highest possible risk reduction. This makes it important to quickly and systematically evaluate input and output relationships among risk mitigation actions to determine which actions are deployed first for efficient risk level reduction. This paper introduces a new SCRM method based on the failure mode and effects analysis (FMEA) in order to perform an efficiency-oriented risk action prioritisation. By considering the cost-benefit evaluation of identified risk mitigation actions for each assessed risk and by determining the implementation effort for risk mitigation actions, also considered as the cost for realising a specific risk action the method allows finding those risk and risk mitigation actions, which are most efficient for risk reduction and should be implemented first in the process of risk steering.