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.
Andre Lebioda, Jens F. Lachenmaier, Daniel Burkhardt
In the course of increasing the flexibility in the area of production, industrial enterprises have been presented with cyber-physical production systems (CPPS). Through the use of autonomously acting CPPS and CPPS components – which often receive multi-agent systems as their corresponding cyber parts – new challenges arise from the need for flexibility and interoperability on the one hand and consistency, trustworthiness as well as reliability of the systems and their components on the other. In order to meet these challenges, this research paper is dedicated to the creation of a technical concept for implementing distributed ledger technology production systems. The paper follows a design-science approach, which consist of analysis, design, and evaluation. The technical concept is based on the GAIA method, which aims to design multi-agent systems and specifically addresses the security and trustworthiness of CPPS-environments. The subsequent evaluation of the concept based on discussions with experts documents its relevance and potential.
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.
Martin Holland, Josip Stjepandić, Christopher Nigischer
Within “Industrie 4.0” approach 3D printing technology is characterized as one of the disruptive innovations. Conventional supply chains are replaced by value-added networks. The spatially distributed development of printed components, e.g. for the rapid delivery of spare parts, creates a new challenge when differentiating between “original part”, “copy” or “counterfeit” becomes necessary. This is especially true for safety-critical products. Based on these changes classic branded products adopt the characteristics of licensing models as we know them in the areas of software and digital media. This paper describes the use of digital rights management as a key technology for the successful transition to Additive Manufacturing methods and a key for its commercial implementation and the prevention of intellectual property theft. Risks will be identified along the process chain and solution concepts are presented. These are currently being developed by an 8-partner project named SAMPL (Secure Additive Manufacturing Platform).
Digital Transformation in Industry
Flexible and Reconfigurable Manufacturing Systems
Additive Manufacturing and 3D Printing Technologies
Preboj tehnologije veriženja blokov je omogocil oživitev in razvoj pametnih pogodb, ki omenjeni tehnologiji predstavljajo kljucno dodano vrednost. Pametne pogodbe so trenutno v fazi zasnove koncepta in s tem sprožajo veliko zanimanje strokovne javnosti. Prav zaradi zgodnje faze v samem razvoju so izoblikovani vzorci dobrih praks razvoja pametnih pogodb in arhitektur decentraliziranih aplikacij, ki temeljijo na pametnih pogodbah, zelo okrnjeni. Ena od kljucnih lastnosti tehnologije veriženja blokov je nespremenljivost, ki se odraža tudi na pametne pogodbe. Taksna lastnost lahko predstavlja izvedbene in varnostne težave, saj so pametne pogodbe nezamenljive in hkrati nespremenljive v trenutku, ko so namescene v omrežje verig blokov. V magistrskem delu predlagamo arhitekturo ekosistema pametnih pogodb, ki bo ucinkovito omogocala zamenljivost in nadgradljivost pametnih pogodb na platformi Ethereum. Uporabo predlagane arhitekture smo predstavili na primeru resevanja realnega izziva nadgradnje poslovnega procesa implementiranega s pomocjo pametnih pogodb.
Diese Arbeit untersucht die Möglichkeiten, einen exemplarischen kaufmännischen Prozess mit verschiedenen Akteuren auf der Ethereum-Plattform abzubilden. Das Wissen über die Funktionsweise der Blockchain-Technologie stellt die Grundlage für die Bearbeitung dar. Unter Berücksichtigung der Besonderheiten verteilter Systeme hinsichtlich der Datenhaltung sowie des Datenschutzes wird ein Konzept für die Abwicklung eines Warenan- bzw. Verkaufs entwickelt. Darin wird die Integration eines zusätzlichen Systems zur Speicherung von Daten vorgestellt, das sich kryptografischer Funktionen der Ethereum-Plattform bedient. Für wichtige Teile des Systems werden zudem Implementierungshinweise gegeben.
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
With increasing product personalization and open innovation, the manufacturing paradigm has been transforming to a more decentralized and socialized one. Social manufacturing was proposed as a new paradigm for industry. It extends the crowdsourcing idea to the manufacturing area. By establishing cyber–physical–social connection via decentralized social media, various communities can be formed as complex, dynamic autonomous systems to co-create customized and personalized products and services. This article presents the concept and characteristics of social manufacturing including distributed, adaptive, and self-organization. It also addresses social intelligence in proactive decision-making for organization of socialized resources and producers in the life-cycle of product.
Hans Fleischmann, Philipp Gölzer, Jens-Erik Franke, M. Amberg
Die umfassende Vernetzung intelligenter Produkte und Produktionssysteme in Industrie 4.0 erlaubt eine dezentral agierende Produktion sowie die Fähigkeit zur Selbststeuerung und Selbstoptimierung. Die Standardisierung von Kommunikation und Datenaustausch nimmt an dieser Stelle eine entscheidende Rolle ein und ermöglicht die system- und wertschöpfungsübergreifende Interaktion von Entitäten. Im Fachbeitrag werden formalisierte Anforderungen von Industrie 4.0 und Fähigkeiten propagierter Kommunikationsprotokolle gegenübergestellt.   Comprehensive networks of intelligent products and production systems in Industry 4.0 enable an autonomous and decentralized manufacturing organization and the capability for self-control and self-optimization. Standardized communication and data exchange is the key to establish the interaction of entities and systems along the entire value chain. This paper analyses requirements of Industry 4.0 and discusses the capabilities of propagated communication protocols.
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.
Up-to-date market dynamics and intense competition have forced a production system to be more widely distributed and decentralized than ever, and the production system itself can be regarded as a collaborative network of autonomous production resources in which the responsibility of decision making is also decentralized into individual autonomous entities. The conventional resource management models, however, are not suitable for the distributed and decentralized environment because of their centralized nature. In this paper, an agent-based resource management model is proposed. The proposed model applies employment relation-driven fractal organization (FrOrg) into organizational model for distributed production resources and presents a resource management framework based on employment contracts. The fractal organization is a structured association in which a self-similar pattern recursively appears, and employment relations between production resources are recursively constructed throughout the entire production system.