Abstract Currently, inconsistent software versions lead to massive challenges for many car manufacturers. This is partly because within the product lifecycle management and the software engineering process, there is no correct handling of software versions for the “data entry” (installation of software on the ECU) of the vehicles. Furthermore, there are currently major challenges for many vehicle manufacturers to ensure transparency, integrity and full traceability of SW data status vis-à-vis the legislator. To counteract these challenges, new solutions in the field of vehicle engineering are to be developed based on a new platform called “CarEngChainNet” and Blockchain technology. On the basis of the “CarEngChainNet” platform, new main and sub-chain chains will be developed that allow tamper-proof SW data management (Peer to Peer and crypto technology) across the entire PLM chain with new methods such as model-based systems engineering of the requirement, function and integration of the SW components in different areas of vehicle development. The aim is to develop new transmission chains of vehicles with individually packaged software artefacts (e.g. ECU software) that can be securely transmitted from server to server into the vehicle.
Alexios Papacharalampopoulos, Harry Bikas, Christos K. Michail, Panagiotis Stavropoulos
Manufacturing process related functionalities, like optimization and control, are in general demanding in terms of data, computational time and efficiency. However, there are no generic certification or validation schemes that can be followed. In particular, only ISO application can verify the suitability of operations up to an extent. The current work utilizes an enhanced version of Blockchain so that functionalities at the process level can be certified as per a particular scheme. The concept of ledger is elaborated to this end, to manipulate knowledge and be able to handle it like an asset that is exchanged. Thus, a specific generic framework is proposed, herein, to reassure that the right kind of information has been exchanged during process control and optimization. Furthermore, expert distributed agents are utilized to turn knowledge into certified procedures. Encryption issues are also regarded, providing safety and security as extra characteristics. The case study of thermal process control is regarded in this sense to prove the complementary character of these concepts and the usability of the framework. Finally, the existence of additional features within this loop is discussed, like the validation of quantifying concepts like resource streams.
Open access
Flexible and Reconfigurable Manufacturing Systems
Digital Transformation in Industry
Physical Unclonable Functions (PUFs) and Hardware Security
Michael Lechner, Philipp Frey, Maximilian Kreß, Marion Merklein · 6 authors
Moderne industrielle Fertigungsprozesse müssen stetig wachsende Anforderungen an Material- und Ressourceneffizienz, Qualität und Variantenvielfalt erfüllen. Die unternehmensübergreifende Zusammenführung integritätsgesicherter Daten ist hierbei Voraussetzung für die retrospektive Identifikation von Qualitätsproblemen, die Dokumentation der Einhaltung von Standards und die Allokation von Ressourcenverbräuchen entlang der Wertschöpfungskette. In diesem Beitrag wird am Beispiel eines Materialcharakterisierungsverfahrens für den hybriden Leichtbau diskutiert, wie mit der Blockchain-Technologie ein manipulationssicheres Speicherkonzept umgesetzt werden kann.   Modern industrial manufacturing processes have to meet ever-increasing requirements in terms of material and resource efficiency, quality and product variety. The cross-company consolidation of integrity-secured data is a prerequisite for the retrospective identification of quality problems, the documentation of compliance with standards and the allocation of resource consumption along the value chain. This paper uses the example of a material characterization process for hybrid lightweight construction processes to discuss how blockchain technology can be used to implement a tamper-proof storage concept.
Luis A. Estrada-Jimenez, Terrin Pulikottil, Ricardo Silva Peres, Sanaz Nikghadam-Hojjati · 5 authors
The heterogeneity of the components of a Cyber-Physical Production System in addition to the high decentralization and autonomy required in Industry 4.0, introduces new levels of engineering complexity and dynamism that classical reductionists approaches are not able to solve. Within this context, novel solutions that rely on complexity sciences seem to be a good alternative to cope with these underline challenges. In this context, this paper presents a conceptual framework of complexity theory, self-organization and emergence and its subsequent relation to cyber manufacturing systems. Such analysis shows very promising ideas in the further development of complex, robust, adaptive and at least partial autonomous manufacturing systems.
Gordon Lemme, Diana Lemme, Kilian Armin Nölscher, Steffen Ihlenfeldt
In a global sales market with networked production steps and increasing complex machine tools, scaling service ecosystems for production provide an adequate solution for handling the generated data. The existing sensor equipment at current and the extension possibility by the System-of-Systems approach for existing machine tools can offer value-added services by the smart handling of production-related data. It is important to make these data validatable and exchangeable, taking into account to different protection goals. The trust of the individual actors in such a volatile value chain and the different (partly cross-border) value creation partners play an important role. The participation of a large number of these actors creates an attractive overall system (ecosystem) with lots of services and network effects. Concerning data security there are numerous aspects, which have not been adequately answered or taken into account in the use of a service ecosystem in the production environment. The paper discusses a distributed ecosystem for production on a distributed ledger-based service ecosystem, in which services can be mapped in the machine tool environment (e.g. calibration). This technology can be used for secure data exchange in order to discuss traceability and unchangeability of data while maintaining data sovereignty.
This thesis aims to add knowledge that contributes to answering the question of how digital transformation technologies can contribute to increasing customer value in logistics and supply chain management (L&SCM), and how manufacturing companies can mindfully use them. The output of the thesis is an architectural framework that proposes performance components, approaches and methodologies that can help in capturing this customer value. To build the basis for such a framework, this research first deduces and presents the underlying definition of digital transformation and describes its potential for, as well as current barriers for its application in, L&SCM. The study uses a systematic literature review to identify nine underlying digital transformation technology bundles. These are: auto-identification technologies; information and communication technologies; the cloud; cyber physical systems; analytics; distributed ledger; automation technologies; augmented and virtual reality; and additive manufacturing. These technologies served as inputs for a nominal group technique workshop aiming to conceptualize the dimensions of customer value based on the technologies. The derived dimensions are information disclosure, time, product/production, service/assistance, quality, choice options, and planning. Based on these findings, this thesis presents an impact assessment for customer-based L&SCM performance. The three-plus-one customer value propositions are availability, servitization, co-creation, and cognition as enhancement. Expert interviews provide the data for the architectural framework for capturing customer value based on digital transformation technologies in L&SCM. The six dimensions covered are the customer value proposition; the value portfolio; scope of collaboration; human resource management and organization; performance management; as well as the (re-)adjusting value assessment. The main scientific contribution lies in conceptualizing the customer value for L&SCM based on digital transformation technologies whereas the architectural framework constitutes the main practical contributions.
Under the guiding concept of a thinking skin, the research project examines the transferability of cyber-physical systems to the application field of façades. It thereby opens up potential increases in the performance of automated and adaptive façade systems and provides a conceptual framework for further research and development of intelligent building envelopes in the current age of digital transformation. The project is characterized by the influence of digital architectural design methods and the associated computational processing of information in the design process. The possible establishment of relationships and dependencies in an architecture understood as a system, in particular, are the starting point for the conducted investigation. With the available automation technologies, the possibility of movable building constructions, and existing computer-based control systems, the technical preconditions for the realisation of complex and active buildings exist today. Against this background, dynamic and responsive constructions that allow adaptations in the operation of the building are a current topic in architecture. In the application field of the building envelope, the need for such designs is evident, particularly with regards to the concrete field of adaptive façades. In its mediating role, the façade is confronted with the dynamic influences of the external microclimate of a building and the changing comfort demands of the indoor climate. The objective in the application of adaptive façades is to increase building efficiency by balancing dynamic influencing factors and requirements. Façade features are diverse and with the increasing integration of building services, both the scope of fulfilled façade functions and the complexity of today’s façades increase. One challenge is the coordination of adaptive functions to ensure effective reactions of the façade as a complete system. The ThinkingSkins research project identifies cyber-physical systems as a possible solution to this challenge. This involves the close integration of physical systems with their digital control. Important features are the decentralized organization of individual system constituents and their cooperation via an exchange of information. Developments in recent decades, such as the miniaturisation of computer technology and the availability of the Internet, have established the technical basis required for these developments. Cyber-physical systems are already employed in many fields of application. Examples are decentralized energy supply, or transportation systems with autonomous vehicles. The influence is particularly evident in the transformation of the industrial sector to Industry 4.0, where formerly mechatronic production plants are networked into intelligent technical systems with the aim of achieving higher and more flexible productivity. In the ThinkingSkins research project it is assumed that the implementation of cyber-physical systems based on the role model of cooperating production plants in IIndustry 4.0 can contribute to an increase in the performance of façades. Accordingly, the research work investigates a possible transfer of cyber-physical systems to the application field of building envelopes along the research question: How can cyber-physical systems be applied to façades, in order to enable coordinated adaptations of networked individual façade functions? To answer this question, four partial studies are carried out, which build upon each other. The first study is based on a literature review, in which the understanding and the state-of-the-art development of intelligent façade systems is examined in comparison to the exemplary field of application of cyber-physical systems in the manufacturing industry. In the following partial study, a second literature search identifies façade functions that can be considered as components of a cyber-physical façade due to their adaptive feasibility and their effect on the façade performance. For the evaluation of the adaptive capabilities, characteristics of their automated and adaptive implementation are assigned to the identified façade functions. The resulting superposition matrix serves as an organizational tool for the third investigation of the actual conditions in construction practice. In a multiple case study, realized façade projects in Germany are examined with regard to their degree of automation and adaptivity. The investigation includes interviews with experts involved in the projects as well as field studies on site. Finally, an experimental examination of the technical feasibility of cyber-physical façade systems is carried out through the development of a prototype. In the sense of an internet of façade functions, the automated adaptive façade functions ventilation, sun protection as well as heating and cooling are implemented in decentrally organized modules. They are connected to a digital twin and can exchange data with each other via a communication protocol. The research project shows that the application field of façades has not yet been exploited for the implementation of cyber-physical systems. With the automation technologies used in building practice, however, many technical preconditions for the development of cyber-physical façade systems already exist. Many features of such a system are successfully implemented within the study by the development of a prototype. The research project therefore comes to the conclusion that the application of cyber-physical systems to the façade is possible and offers a promising potential for the effective use of automation technologies. Due to the lack of artificial intelligence and machine learning strategies, the project does not achieve the goal of developing a façade in the sense of a true ThinkingSkin as the title indicates. A milestone is achieved by the close integration of the physical façade system with a decentralized and integrated control system. In this sense, the researched cyber-physical implementation of façades represents a conceptual framework for the realisation of corresponding systems in building practice, and a pioneer for further research of ThinkingSkins.
Christian P. Nielsen, Elias Ribeiro da Silva, Fei Yu
Digital Twins and Blockchain are key elements that when connected allow continuous data acquisition in the factory. As the connection between digital twins and blockchain is rather under-explored, the key contribution of this paper is the conceptual development of a digital twin prototype connected with an Ethereum-based blockchain. The outcome of the paper provides a concept to ensure the unique tokens represent the physical assets without being tampered with by applying digital twin technology. The paper includes a case study focused on Matrix-Structured Manufacturing Systems for Small and Medium-sized Enterprises.
The planning and control of intralogistics systems in line with versatile production systems of smart factories requires new approaches and methods to cope with changing requirements within future factories. The planning of intralogistics can no longer follow a static, sequential approach as in the past since the planning assumptions are going to change in a high frequency. Reasons for these constant changes are amongst others external turbulences like rapidly changing market conditions, decreasing batch sizes down to customer-specific products with a batch size of one and on the other hand internal turbulences (like production and logistic resource breakdowns) affecting the production system. This paper gives an insight into research approaches and results how capabilities of intelligent logistical objects (intelligent bins, autonomous transport systems etc.) can be used to achieve a self-organized, cost and performance optimized intralogistics system with autonomously controlled process execution within versatile production environments. A first consistent method has been developed which has been validated and implemented within a scenario at the pilot factory Werk150 at the ESB Business School (Reutlingen University). Based on the incoming production orders, the method of the Extended Profitability Appraisal (EPA) covering the work system value to define the most effective work system for order fulfilment is applied. To derive the appropriate intralogistics processes, an autonomous control method involving principles of decentralized and target-oriented decision-making (e.g. intelligent bins are interacting with autonomously controlled transport systems to fulfil material orders of assembly workstations) has been developed and applied to achieve a target-optimized process execution. The results of the first stage research using predefined material sources and sinks described in this paper is going to set the basis for the further development of a self-organized and autonomously controlled method for intralogistics systems considering dynamic source and sink relations. By allowing dynamic shifts of production orders in the sense of dynamic source and sink relations the cost and performance aims of the intralogistics system can be directly aligned with the aims of the entire versatile production system in the sense of self-organized and autonomously controlled systems.
Conventional railway operations employ specialized software and hardware to ensure safe and secure train operations. Track occupation and signaling are governed by central control offices, while trains (and their drivers) receive instructions. To make this setup more dynamic, the train operations can be decentralized by enabling the trains to find routes and make decisions which are safeguarded and protocolled in an auditable manner. In this paper, we present the case study findings of a first-of-its-kind blockchain-based prototype implementation for railway control, based on decentralization but also ensuring that the overall system state remains conflict-free and safe. We also show how a blockchain-based approach simplifies usage billing and enables a train-to-train/machine-to-machine economy. Finally, first ideas addressing the use of blockchain technology as a life-cycle approach for condition-based monitoring and predictive maintenance in train operations are outlined.
Conventional railway operations employ specialized software and hardware to\nensure safe and secure train operations. Track occupation and signaling are\ngoverned by central control offices, while trains (and their drivers) receive\ninstructions. To make this setup more dynamic, the train operations can be\ndecentralized by enabling the trains to find routes and make decisions which\nare safeguarded and protocolled in an auditable manner. In this paper, we\npresent the findings of a first-of-its-kind blockchain-based prototype\nimplementation for railway control, based on decentralization but also ensuring\nthat the overall system state remains conflict-free and safe. We also show how\na blockchain-based approach simplifies usage billing and enables a\ntrain-to-train/machine-to-machine economy. Finally, first ideas addressing the\nuse of blockchain as a life-cycle approach for condition based monitoring and\npredictive maintenance in train operations are outlined.\n
In order to increase the level of global competitiveness and improve the performance of production system, a large number of manufacturing companies have implemented world class manufacturing (WCM) approach, which has developed based on the third industrial revolution and the need for mass production. The evolution in production equipment and communication technologies, and the demand of markets for personalized mass production, have forced manufacturing companies to transform their production systems and prepare for a revolution. This revolution, known as Industry 4.0 (I4.0), or the digital transformation, has been introduced as a new type of organization of manufacturing systems that is more flexible and agile, and is based on using large amounts of information and data in the decision-making process. One of the main characteristics of this concept is decentralization, which allows different subsystems to make decisions autonomously in order to have self-organization systems. There are some important differences between the principles of WCM and I4.0. World class manufacturing is mainly based on continuous improvement and cost reduction, without a global vision for profit optimization. Industry 4.0 is mainly based on using all accessible information and data of systems and making decentralized decisions, but it also involves a global vision and a systemic approach to global profit optimization. However, achieving these objectives takes a very long time, and the challenges are numerous. As with all projects, for a transformation project to succeed, it is very important to define the transition phase and the way to change and introduce these new principles. This paper presents part of our research project, in collaboration with the Fiat Powertrain Technologies company, concerning the transformation of their production system toward the factory of the future. We highlight the design principles of I4.0 and the potential of the WCM system for transformation and achieving development of the characteristics of I4.0. We focus on five of the principal technical pillars of WCM and the steps in their development, and present some modifications in adoption of the design principles of I4.0. An example of change in the professional maintenance pillar of WCM is also presented.
The persistent development towards decreasing batch sizes due to an ongoing product individualization, as well as increasingly dynamic market and competitive conditions lead to new changeability requirements in production environments. Since each of the individualized products might require different base materials or components and manufacturing resources, the paths of the products going through the factory as well as the required internal transport and material supply processes are going to differ for every product. Conventional planning and control systems, which rely on predefined processes and central decision-making, are not capable to deal with the arising system’s complexity along the dimensions of changing goods, layouts and throughput requirements. The concepts of “self-organization” in combination with “autonomous control” provide promising solutions to solve these new requirements by using among other things the potential of autonomous, decentralized and target-optimized decision-making. A major enabler for the development towards autonomous changeable intralogistics systems are intelligent logistical objects (e.g. smart products, bins and conveyor systems) which are able to communicate and interact with each other as well as with human workers. To investigate the potential of automation and human-robot collaboration for intralogistics, a research project for the development of a collaborative tugger train has been started at the ESB Logistics Learning Factory in line with various student projects in neighboring research areas. This collaborative tugger train system in combination with other manual (e.g. handcarts) and (semi-)automated conveyor systems (e.g. automated guided forklift) will be integrated into a dynamic, self-organized scenario with varying production batch sizes to develop a method for target-oriented self-organization and autonomous control of intralogistics systems. For a structured investigation of self-organized scenarios a generic intralogistics model as well as a criteria catalogue has been developed. The ESB Logistics Learning will serve as a practice-oriented research, validation and demonstration environment for these purposes.
Michael Hinterstocker, Florian Haberkorn, Andreas Zeiselmair, Serafin von Roon
Only a small share of German households make use of the opportunity to regularly switch their electricity supplier in order to fulfill their needs. Besides the relatively low possible monetary savings, another reason is the fact of long running contracts. The process of supplier switching for stakeholders in the energy market is quite time-consuming. This is caused by inefficient design of the process steps due to a lack of automation, of common data management and of direct communication between these stakeholders. Two options for optimizing this by means of a blockchain-based system are described and discussed here. These allow simplified communication between participating parties and therefore potentially quicker completion of the process. They enable automation of the whole process, prevent delays due to inconsistent data and therefore, allow intraday switching. An exemplary proof-of-concept implementation on the Ethereum blockchain shows the feasibility of the approach. Nevertheless, the advantages and disadvantages when compared to an alternative automated implementation, which is not blockchain-based, are still to be thoroughly examined.
José Barbosa, Paulo Leitão, Adriano Ferreira, Jonas Queiroz · 6 authors
This paper describes the development of a multiagent system (MAS) to support the implementation of zero-defect manufacturing strategies in multi-stage production systems. The MAS infrastructure, combined with on-line inspection tools, data analytics and knowledge generation, constitutes a suitable approach to integrate process and quality control in multi-stage environments. This will allow the early detection of product defects, the adaptation to operating condition changes and the optimisation of manufacturing processes. This type of integrated management structure is aligned with a zero-defect manufacturing production model which is of paramount importance in the actual state-of-the-art manufacturing paradigms. As a proof of concept, the devised manufacturing supervision model was deployed into an experimental multi-stage system that run a set of several tests on electrical motors. The agent-based solution was implemented using the JADE framework and the exchange of information structured by proper data models and industrial based Internet-of-Things and Machine-to-Machine technologies, such as OPC-UA, REST and JSON. The obtained results demonstrate the suitability of the devised integrated management model as a vehicle to achieve dynamic and continuous system improvement in multi-stage manufacturing environments.
The rise of fraudulent cases seems to be a nuisance to an organization as they're an investment of money. Various resources also gives the impression to be on someone else, who has false claims. The verification process of these organizations are long and tedious process where the organization would have lost its time and resource on. Blockchain technology was introduced fairly recently in literature, which is the underlying technology behind the very popular cryptocurrency Bitcoin. The blockchain is a decentralized approach, it is secured by design network which was to overcome double spending problem by a central server. The concept of servers is eradicated in this architecture, where the data is distributed across geographically on separate ledgers. Blockchain applications have diversified as MIT Media Labs introduced Blockcerts for certification of academic records. Ethereum is platform for developing these decentralized applications using Blockchain ledgers. Ethereum uses a concept called Merkle trees which is the concept used for verification through hashing. As per the working in the literature; this application would make verification of academic documents simple and quick with the usage of Blockchain clients such as Ethereum and an IPFS hash. In this paper we propose a system that provides a solution that addresses the above mentioned issues.
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.
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.
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
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.