Ivan Jovović, Siniša Husnjak, Ivan Forenbacher, Sven Maček
The Industry 4.0 is experiencing significant challenges, including the need for an increased amount of data transmission with improved security, transparency and credibility. The 5th Generation Mobile Network (5G) and Blockchain are innovative emerging technologies that can respond to these needs. 5
Christoph Berger, Urs Hoffmann, Stefan Braunreuther, Gunther Reinhart
Regarding the changing market environment in terms of logic requirements, production planning and control recently contribute significantly to fulfilling these demands. Logistic command variables, particularly adherence to schedule, are becoming the crucial parameters to satisfy the customer's needs. Cyber-Physical production Systems (CPPS) with their characteristics decentralized organization, autonomous control, real-time capability and smart data processing offer new possibilities of production monitoring and control. For this purpose, this paper proposes a new event-based approach in order to improve adherence to schedule in production by using the potential of CPPS. Control loops close to production shop floor provide a fast identification of events. Based on an activity list, the production control is able to react adequately to the different events e.g. machine disturbance or urgent orders. The activities initiated by the Manufacturing Execution System (MES) affect the whole production system while the production. In a final step, the developed concept of an event-driven production control was implement in a simulation.
Industry 4.0 will enable the development of hyper-efficient plants, which facilitate the implementation of emerging production models such as Made-to-Order and Configure-to-Order. In this direction, the H2020 FAR-EDGE project has introduced a reference architecture and an accompanying platform that facilitates the implementation of digital automation solutions based on edge computing and distributed ledger technologies, which enable fast, reliable and responsive automation. In this paper, we illustrate the use of these technologies for the implementation and deployment of a practical use case in the white appliances industry. Specifically, we present how a sorter component can be automatically programmed in order to ensure that items arriving at a conveyor are optimally placed in various bays. The use case leverages the edge computing paradigm in order to ensure that each physical item is able to communicate its status to all the others. At the same time, distributed ledger technologies enable the modelling of the sorting process as a reliable smart contract among all physical entities. The benefits of the deployment include tangible improvements in productivity, along with a significant reduction in the effort and time needed for the reconfiguration of the sorter.
The advent of Industry4.0 has given rise to a large number of digital manufacturing systems, which are currently used to digitize industry and transform industrial processes like automation, maintenance and quality control. The present paper introduces a first-of-a-kind reference architecture for developing industrial automation systems based on edge computing and blockchain technologies. It also presents the design of a platform that implements this reference architecture with a view to providing functionalities in three complementary domains, namely automation, production systems’ virtualization and data analytics. The presented platform is destined to provide some distinct performance and reliability advantages, based on its edge computing and blockchain foundations.
Blockchain is a form of distributed ledger technology (DLT) that has grown in prominence, although its full potential and possible downsides are not yet fully understood, especially with respect to Operations Management (OM). This manuscript contributes to filling in this gap. We identify three research themes in applying Blockchain technology to OM, illustrated through several applications to OM problems. Elsewhere, in a companion article, (Babich and Hilary (2018)), we provide a conceptual framework for the role of Blockchain and other DLT in OM, along with specific examples of research questions, and we demonstrate how research in economics can inform research in OM on Blockchain applications. Finally, we discuss possible future uses for the technology.
Nowadays, the modern supply chain is facing the new threats and opportunities due to quality, safety, ethics, environmental impact and other serious problems aroused by the opacity of supply chain. On the contrary, a transparent and traceable supply chain can help suppliers minimize fraud and errors, enhance inventory management, reduce courier costs, lower waste and delay. Consequently, transparency and traceability are essential to the sustainable development of industrial supply chain in the future. \n \n \nDriven by growing demand for transparency and traceability from consumers, companies, and governments, some fundamental labeling technologies (e.g. RFID, QR code, NFC tag, etc.) have been already combined with web technology and applied in logistics system to identify a product with origin information. Even though, those traditional technologies fail to provide a trusted and cost-efficient system to record provenance and share information. \n \n \nThis thesis aims to find an approach to improve transparency and traceability of supply chain in a secure and cost-efficient way. To achieve this goal, an approach with an emerging technology is presented in this thesis: blockchain, a shared, distributed and permissioned ledger that records every transaction information associated with asset through supply chain, which is synchronized and verified in real time with all entities in the supply chain but can be accessed only by authorized participants. \n \n \nThe result of this research work not only provides in-depth research of blockchain technology but also proposes a concrete solution with an implementation of blockchain technology to shape a transparent and traceable supply chain network. This solution can track provenance and trajectory of an asset through the complex supply chain in real time, at the same time, provides unprecedented visibility and confidentiality. Finally, this thesis also shows a possibility to integrate the blockchain system with other web service and traditional enterprise resource planning system.
The development of robotics, the Internet of Things concept, big data processing techniques, automation, and distributed digital ledgers leads to the fourth industrial revolution. One of the main issues of new industry is interaction between the "smart factory" components both internally and with other factories based on the Internet of Things. This interaction should provide trust between the participants of the Internet of Things; control over the distribution of resources (such as maintenance time, energy, etc.) and finished products. The paper describes one of the possible ways of integrating Internet of Things and blockchain technologies to solve these issues. For this purpose, an architecture has been developed that combines Smart-M3 information sharing platform and blockchain platform. One of the main features of the proposed architecture is the use of smart contracts for processing and storing information related to the interaction between smart space components.
Complexity of electric/electronics (E/E) in automobiles increases tremendously due to more connectivity and real-time data processing. Hence, huge volatility of E/E artifacts is the consequence. In order to keep track of all changes made from early systems engineering to late after sales, a permeable traceability in data management systems has to be achieved. Therefore, this elaboration adapts the blockchain technology to achieve traceability of E/E development artifacts from early model-based systems engineering (MBSE) till after sales. By this, MBSE is linked to product data management and the automobile’s configuration is known at each instant of time. The Digital Twin, a digital, domain-specific representation of the physical vehicle in one front end tool, makes the complexity still feasible to handle and is empowered by the blockchain. Hence, traceability of E/E artifacts over an automobile’s lifecycle including MBSE is fostered in a manageable manner.
Open access
Flexible and Reconfigurable Manufacturing Systems
Systems Engineering Methodologies and Applications
Jan 1, 2017·Proceedings of the ... Annual Hawaii International Conference on System Sciences/Proceedings of the Annual Hawaii International Conference on System Sciences
Digital supply chain integration is becoming \ increasingly dynamic. Access to customer demand \ needs to be shared effectively, and product and service \ deliveries must be tracked to provide visibility in the \ supply chain. Business process integration is based on \ standards and reference architectures, which should \ offer end-to-end integration of product data. \ Companies operating in supply chains establish \ process and data integration through the specialized \ intermediate companies, whose role is to establish \ interoperability by mapping and integrating companyspecific \ data for various organizations and systems. \ This has typically caused high integration costs, and \ diffusion is slow. This paper investigates the \ requirements and functionalities of supply chain \ integration. Cloud integration can be expected to offer \ a cost-effective business model for interoperable \ digital supply chains. We explain how supply chain \ integration through the blockchain technology can \ achieve disruptive transformation in digital supply \ chains and networks.
Peter Ittermann, Jonathan Niehaus, Hartmut Hirsch‐Kreinsen, Johannes Dregger · 5 authors
This paper is dealing with the ongoing debate of the digitization of german industry, the so-called „Industrie 4.0“, and its social consequences. The discussed new technologies like cyber-physical production systems, autonomous logistic systems and smart devices are about to get integrated in work places, that are embedded in existing organizational and social structures, thus making ‘complementary innovations’ and a coordinated design necessary. Our paper presents a human-centered design of industrial labor in a framework depicting the dilemma between what is techno-logically feasible and labor-politically desirable, under the constraint of an economically reasonable design of work and technology. The analytical approach is the “socio-technical system” which as-sumes that there are certain varieties of organizational design at the interfaces of its sub-systems ‘technology’, ‘human’ and ‘organization’. These considerations are transformed into a framework, called Social Manufacturing and Logistics, which brings together these perspectives and leads to a complementary holistic design of industrial labor under the conditions of a progressive digitization of manufacturing. Its characteristics are: hybrid interaction between human and machine, flexible integrated work and decentralized systems. Finally, we outline some organizational and social con-ditions to realize such a framework.
Globalization, unpredictable markets, increased products customization and frequent changes in products, production technologies and machining systems have become a complexity in today’s manufacturing environment. One key strategy for coping with the evolution of this situation is to develop or apply an enable technology such as intelligent manufacturing. Intelligent manufacturing system (IMS) is characterized by decentralized, distributed, networked compositions of heterogeneous and autonomous systems. The model of IMS is inherited from the organization of the living systems in biology and nature so that the manufacturing system has the advanced characteristics inspired from biology such as self-adaptation, self-diagnosis, and selfhealing. To prove this concept, an innovative system with applying the advanced information and communication technology such as internet of things, cognitive agent are proposed to integrate, organize and allocate the machining resources. Innovative system is essential for modern machining system to flexibly and quickly adapt to new challenges of manufacturing environment.
Smart manufacturing considered as a new trend of modern manufacturing helps to satisfy objectives associated with the productivity, quality, cost and competiveness. The smart manufacturing system is characterized by decentralized, distributed, networked compositions of autonomous systems. The model of smart manufacturing is inherited from the organization of the living systems in biology and nature such as ant colony, school of fish, bee's foraging behaviors, and so on. In which, the resources of the manufacturing system are considered as biological organisms, which are autonomous entities so that the manufacturing system has the advanced characteristics inspired from biology such as self-adaptation, self-diagnosis, and self-healing. In this paper, a cloud based smart manufacturing system for machining transmission cases is considered as research object in which the advanced information and communication technology such as cognitive agent, swarm intelligence, and cloud computing are used to integrate, organize and allocate the machining resources.
Smart manufacturing (SM) considered as a new trend of modern manufacturing helps to meet objectives associated with the productivity, quality, cost and competiveness. It is characterized by decentralized, distributed, networked compositions of autonomous systems. The model of SM is inherited from the organization of the living systems in biology and nature such as ant colony, school of fish, bee’s foraging behaviors, and so on. In which, the resources of the manufacturing system are considered as biological organisms, which are autonomous entities so that the manufacturing system has the advanced characteristics inspired from biology such as selfadaptation, self-diagnosis, and self-healing. To prove this concept, a cloud machining system is considered as research object in which internet of things and cloud computing are used to integrate, organize and allocate the machining resources. Artificial life tools are used for cooperation among autonomous elements in the cloud machining system.