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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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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%.
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.
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.