In today’s modern energy sector, driven more and more towards decentralization, which includes many smaller energy producers rather than huge government projects, security against cyber-attacks is becoming more crucial for the energy grid. Since many small energy plants do not have the resources to finance very expensive existing cyber-security systems, they often have no security system in place at all. Although with small energy producers, the risks of being under attack are not as devastating as in a huge power plants, they still pose a serious threat to the energy system and to the supply of electricity to whole regions. Moreover, in the era of technology, such cyber-attacks could be carried out simultaneously at many locations, thus risking the lack of electricity to larger areas. Since there was a clearly identified need for such an instrument, the SPEAR consortium, started to develop tailor made solution for different types of actors in the energy sector, to prevent such occurrences and help secure the energy system. One of the use cases, investigated in the project, is a real operating hydro power plant in the mountain area of Bulgaria called Leshnitsa, which will be one of the four sites to first test the functionality of the finished product. The plant had no previous cyber-security system in place and had already experienced one attack, where one of the computers in the plant was hacked and a ransom was demanded from the attackers to unlock it. Exactly events like this one are proof, that the energy sector has a need to protect the growing number of small independent actors in the energy system..
Purpose This study investigates the competencies required for quality management professionals to meet the needs of industry 4.0. The authors use a case study strategy at an electronics manufacturer in southern Malaysia, to adapt their role to be relevant in the industry 4.0 environment. In doing so, this study answers the following four questions: (1) How are the changing technological trends expected to impact the future role of quality in industry 4.0? (2) What are the competencies gap between current and future roles of quality professionals? (3) What are the views and practices related to quality roles? (4) How can the gaps identified be closed to meet the quality challenges of industry 4.0? Design/methodology/approach The research methods consist of a comprehensive review of literature on the technological trends towards industry 4.0 and the impact on the role of quality and competence that may be required in the future, as well as internal document review on the current roles of quality professionals in an electronics manufacturer in southern Malaysia, to identify the competence gap. Empirical data was collected based on surveys conducted on 64 quality professionals with a response rate of 96.88%. Interviews were conducted on three decision-makers from critical areas in the electronics manufacturer for viewpoints from three different perspectives: finance, operations and talent development. Findings Quality professionals will require technical competencies to interpret large amounts of data from processes to make strategic decisions, the use of new AR tools and be aware of data security risks. Methodological competencies will be required to use data to identify the source of problems, to access reliable sources of learning and the ability to use new tools for solving complex problems efficiently. Social competencies will be required in communications across multi-sites, suppliers and customers in new collaborative virtual platforms, with the ability to retain tacit and explicit knowledge, in a decentralized environment that will require leadership ability to make decisions. Personal competencies required will be the ability to work in a flexible workplace and time and more frequent work-related changes. Research limitations/implications The limitation of the study is based on what the authors currently know of the future, which may not be much for the quality professionals in the electronics manufacturer, who have not been exposed much to the technology yet. The potential for the future landscape to change dramatically with rapid technology changes may also result in a different set of skills for future quality professionals. The quality professionals who were involved in this study were the quality executives, engineers and managers, irrespective of their gender, age, length of service and experience in the field of quality. Therefore, these variables were not taken into consideration for this research. Practical implications This research helped to identify the role of quality in industry 4.0 and key competencies that the quality professionals in the electronics manufacturer will require to adapt to their role in industry 4.0. However, based on the questionnaire and the interview comments of key personnel, it can be concluded that quality professionals lack awareness of their new roles in industry 4.0. This could be due to the fact that the new technology is not implemented by quality professionals but by the innovation team based in Singapore headquarters, as was also advised by the operations head. Social implications The benefit of industry 4.0 technology is clearly shown by Philips's new Dutch factory with robotized technology that was able to produce the same output with one-tenth of the workers of its China factory (Rifkin, 2014, chapter 8). Rojko (2017, p. 80) also shared a similar view that industry 4.0 is expected to reduce production costs by 10–30%, logistics costs by 10–30% and quality management costs by 10–20%. The importance of this research can be seen from the findings of “The Future of Jobs” (2018, p. 22), which suggests that the window of opportunity for organizations to leverage the new technology to re-skill is within the period of 2018–2022, in order to enable employees to reach full potential in the high value-added tasks. The electronics manufacturer may need to keep to this timeline to maintain its competitive advantage. Originality/value The purpose of this paper was to determine the competence gap of current quality professionals in the electronics manufacturer with the competencies required in industry 4.0. This led to the third objective, to identify the views of stakeholders based on the propositions derived from the gaps identified, to triangulate the findings, to conclude the competency gaps of the current quality professionals in the electronics manufacturer. Finally, the objective of this paper was to make a recommendation on how to prepare the quality professionals in the electronics manufacturer for their role in industry 4.0. The research identified the technical, methodological, social and personal competencies gap of the quality professionals in the electronics manufacturer by looking at the changes expected in industry 4.0 from four aspects, factory (people and process), business, product and customers.
Yawar Abbas, Alberto Martinetti, Jan-jaap Moerman, Ton Hamberg · 5 authors
This study explores the potential of blockchain technology in enhancing trust among the stakeholders responsible for the maintenance of rolling stock. Although the technology has been widely successful in the financial sector, it is still novel in the maintenance field. Given the customized nature of maintenance processes, it is unclear if a suitable consensus protocol can be identified that can enhance trust among stakeholders. This problem is investigated through the lens of the Design Science Research Methodology. First, the theoretical background of blockchain technology and its role in enhancing trust are explained, followed by the analysis of a current case at a Railway company to test the proof of concept. A business network archive is developed for the maintenance management of the sliding step of the train door system. The archive encompasses the business logic and transactional data required to enhance trust among stakeholders in the quality of performed maintenance. The developed archive is deployed on Hyperledger Fabric and the effectiveness of the solution is evaluated through a survey. The results show that the developed business network, deployed on a customized Hyperledger Fabric consensus protocol, enhanced trust among the stakeholders involved.
Enterprise Resource Planning (ERP) systems are undergoing rapid transformation as organizations pursue real-time operational visibility, stronger data integrity, and scalable digital business models. Two technologies Internet of Things (IoT) and blockchain have emerged as complementary enablers of next generation ERP architectures. IoT devices provide continuous streams of sensor rich operational data that enhance forecasting, automation, and situational awareness across supply chains, manufacturing, and asset management. The integration of large-scale IoT ecosystems introduces challenges in data trustworthiness, provenance tracking, and decentralized coordination. Blockchain offers a tamper resistant ledger, distributed consensus, and programmable smart contracts capable of addressing many of these limitations. When combined, IoT and blockchain can create a secure, transparent, and autonomous ERP backbone in which data flows are verifiable, cross organizational workflows are automated, and mission critical transactions retain end-to-end auditability. This article examines the architectural synergies between IoT and blockchain within ERP frameworks explores integration patterns for secure data acquisition, decentralized validation, and smart contract driven process automation; and evaluates technical and organizational challenges including scalability, interoperability, privacy, and governance. A hybrid reference architecture is proposed to guide practitioners in designing next generation ERP ecosystems that leverage both technologies. The analysis demonstrates that IoT blockchain convergence is a strategic pathway for building resilient, intelligent, and trustworthy enterprise systems capable of supporting Industry 4.0 and data centric operating models.
Kevin Wallis, Jan Stodt, Eugen Jastremskoj, Christoph Reich
The digital transformation of companies is expected to increase the digital interconnection between different companies to develop optimized, customized, hybrid business models. These cross-company business models require secure, reliable, and traceable logging and monitoring of contractually agreed information sharing between machine tools, operators, and service providers. This paper discusses how the major requirements for building hybrid business models can be tackled by the blockchain for building a chain of trust and smart contracts for digitized contracts. A machine maintenance use case is used to discuss the readiness of smart contracts for the automation of workflows defined in contracts. Furthermore, it is shown that the number of failures is significantly improved by using these contracts and a blockchain.
This study assesses supplier selection at the beginning of project management to establish an evaluation system corresponding to blockchain tracing anti-counterfeiting platforms (BTAP). First, this paper determines 20 evaluation criteria from the four dimensions of platform overview, core technology, application support, and operations management. On this basis, multi-criteria decision making (MCDM) based on customer needs is proposed, which consists of three main steps. First, quality function deployment (QFD) and the best and worst method (BWM) are used to evaluate the four dimensions of the BTAP and specific evaluation criteria from the perspective of customers to obtain the criteria weight. Then, this method uses the extended Vlse Kriterjumska Optimizacija I Kompromisno Resenje (VIKOR) approach to sort the alternatives. Finally, the improved decision making trial and evaluation laboratory (DEMATEL) method is used to analyse the relationships between the 20 criteria in the four dimensions. The feasibility and effectiveness of this method are verified by an example. According to the sensitivity analysis and comparative analysis, the results show that this method can evaluate blockchain anti-counterfeiting enterprises. The main conclusions are as follows: the core technology is the most important factor influencing the choice of a BTAP project, and the role of application support in evaluation cannot be ignored.
Manufacturing and supply chain operations are on the cusp of an era with the emergence of groundbreaking technologies. Among these, the digital twin technology is characterized as a paradigm shift in managing production and supply networks since it facilitates a high degree of surveillance and a communication platform between humans, machines, and parts. Digital twins can play a critical role in facilitating faster decision making in product trade-ins by nearly eliminating the uncertainty in the conditions of returned end-of-life products. This paper demonstrates the potential effects of digital twins in trade-in policymaking through a simulated product-recovery system through blockchain technology. A discrete event simulation model is developed from the manufacturer’s viewpoint to obtain a data-driven trade-in pricing policy in a fully transparent platform. The model maps and mimics the behavior of the product-recovery activities based on predictive indicators. Following this, Taguchi’s Orthogonal Array design is implemented as a design-of-experiment study to test the system’s behavior under varying experimental conditions. A logistics regression model is applied to the simulated data to acquire optimal trade-in acquisition prices for returned end-of-life products based on the insights gained from the system.
Maximilian Klöckner, Stefan Kurpjuweit, Chander Velu, Stephan M. Wagner
OverviewBlockchain combined with 3D printing offers businesses untapped opportunities. Blockchain can help businesses overcome intellectual property and data security barriers, allowing them to take advantage of emerging 3D printing business models. Specifically, blockchain can facilitate local manufacturing and may lay the groundwork for new business models such as secure design marketplaces and shared factories. Businesses could also improve their value proposition by offering additional services around a printed part, improving value delivery, and offering less costly and more customized products that involve fewer risks. Blockchain could transform the way firms create, deliver, and capture value in 3D printing ecosystems.
Open access
Digital Transformation in Industry
Blockchain Technology Applications and Security
Additive Manufacturing and 3D Printing Technologies
Giulia Pattini, Giuseppe Martino Di Giuda, Lavinia Chiara Tagliabue
The proposed research aims at illustrating how Blockchain technology can support the contract execution optimizing and assuring a transparent information flow during the phases of the construction process. The traditional approach, chased in the industry, is indeed more hierarchical than networked, resulting in a high fragmentation of contracts and the break of companies in numerous tiers. This context prevents effective collaboration, hindering the achievement of the project objectives. The recent digital transition, guided by Building Information Modeling (BIM), has promised the creation of a shared environment for the information created and exchanged during the entire process, in favor of collaboration and reduction of critical issues typical related to the sector. Despite the initial promises, the use of BIM has shown problems related to trust and transparency of information, not encouraging participants to collaborate in meeting common goals. For these reasons, the study aims to investigate the potential of Blockchain technology in the management of the information flow to ensure transparency and stability of the process. The research proposes four frameworks showing how Blockchain can be integrated with the construction contract to support the execution of each phase, highlighting the improvement of information sharing, traceability of each activity or service and support for collaboration.
Joachim Stanke, Martin Unterberg, Daniel Trauth, Thomas Bergs
Abstract Networking and digitization in manufacturing enable novel methods of data-driven analysis and optimization of processes through cross-process data availability. The creation of digital twins plays an important role in this. However, not all data relevant for a digital twin can be measured directly in the process. Therefore, methods are needed that enable the modelling of quantities that are difficult or impossible to measure directly in the process, such as the finite element method. In many companies, however, neither the know-how nor the necessary IT infrastructure for finite element simulations is available. External commissioning processes are also not suitable for achieving the goals of higher productivity and agility pursued with the digitization and networking of manufacturing processes. In this contribution, an architecture is presented that enables the fully automated use of finite element simulation as a service. The architecture is developed using the case study of fine blanking. First, the requirements of the architecture to be created are determined. Important characteristics of the architecture should be scalability as well as interfaces and means of payment suitable for machine communication. In addition, ensuring data integrity is an important requirement when creating the digital twin. Based on the identified requirements, an architecture is then presented that meets these requirements by using cloud computing and distributed ledger technologies and interfaces that can directly process measurement signals from the process and communicate with the architecture. Finally, the capability of the architecture is tested, possible applications and limitations are discussed, and future extensions are considered.
Open access
Manufacturing Process and Optimization
Digital Transformation in Industry
Additive Manufacturing and 3D Printing Technologies
Because of the digital revolution, also known as Industry 3.0, the boundaries between the physical and digital worlds are shrinking to give life to a more interconnected and smart factories. These factories allow employees, machines, processes, and products to interact oriented to provide a better organization of all the productive means, empowering the entire company itself to achieve higher levels of efficiency and productivity. These technologies are profoundly transforming our society, allowing customizing everything in detail, reducing goods and services costs, transforming worker's and job’s conditions for safety and security, among others. In that sense, Industry 3.0 acted as a catalyst that promoted new production mechanisms, which originated a new industrial revolution known as Industry 4.0. The concept of Industry 4.0, is used to designate the new generation of connected, robotics, and intelligent factories. Fundamentally, the vision of Industry 4.0 is to give smart capabilities to the production and physical operations to create a more holistic and better-connected ecosystem.
One crucial aspect to consider, regarding the idea of the Industry 4.0 concept, is related to integrability and interoperability of the actors involved in manufacturing processes. It means that people, things, processes, and data have to be able not only to make decisions for themselves and to carry out their work in a more autonomous way (independence) but, also, the self-management of the whole factory (need to promote integrability and interoperability). The previous statement implies that the production processes’ actors should be able to autonomously negotiate in order to reach agreements linked to achieve both individual and collective production goals. In that sense, Industry 4.0 represents not only a new way to produce goods and services but also a crucial integration challenge of the actors involved in the manufacturing processes that need connection, communication, coordination, cooperation, and collaboration (denoted as 5C) capabilities that allow them to comply with the vision of Industry 4.0.
Principally, this thesis aims at empowering processes management for Industry 4.0, proposing a stack of five levels, denoted as 5C. The 5C stack levels represent a way to deal with integration and interoperability challenges so that they can be solved incrementally at each level. From this perspective, we must start solving connection and communication issues as a first step to promote more elaborated organization processes like coordination, cooperation, and collaboration. Mainly, the 5C denote the elements needed to allow autonomous integration and interoperability of actors in Industry 4.0.
From this point of view, in this thesis project, we present a first contribution that is oriented to deal with the integration challenges regarding the Industry 4.0 context at the level of connection and communication. This solution is based in a Multi-agent system in which the physical elements of the system are characterized virtually as agents. Notably, the use of Multi-agent systems allows creating an intelligent environment dotted with characteristics of autonomy, decentralization, self-organization, self-direction, standardized protocol, and other properties of Multi-agent systems. Moreover, the proposed solution allows actors to extend their limited capabilities with service deployed through the Internet, as an intent to automatize, optimize, and in more mature stages, transform any environment into a fully integrated, automated, and intelligent environment. Consequently, the proposed architecture will be evaluated and compared to previous researches in this field.
In the second place, we will solve some integration challenges of Industry 4.0 at the level of coordination, cooperation, and collaboration. In this case, we design a framework for autonomous integration of actors in Industry 4.0, to allow them to autonomously coordinate, cooperate, and collaborate. This framework uses technologies like the Internet of Everything, Everything mining, and Autonomic computing. Next, we design some autonomic cycles of data analytics tasks, oriented to enable autonomous coordination in manufacturing processes. Fundamentally, these data analytics tasks create the knowledge bases needed in a production environment to support self-planning, self-manage, self-supervising, self-healing, etc. to the manufacturing process.
Finally, we implement an autonomous cycle of data analytics tasks for self-supervising, using several Everything-mining techniques over data sources corresponding to a real manufacturing process. It defines a self-value-driven supervisory system, according to the classification made by Xu et al. (2017), that can process and verify the functionalities and applicability of our framework in manufacturing processes. Moreover, the self-supervising system developed in this thesis project is compared to other research works.
Shengjing Sun, Xiaochen Zheng, Javier Villalba-Díez, Joaquín Ordieres‐Meré
Information-intensive transformation is vital to realize the Industry 4.0 paradigm, where processes, systems, and people are in a connected environment. Current factories must combine different sources of knowledge with different technological layers. Taking into account data interconnection and information transparency, it is necessary to enhance the existing frameworks. This paper proposes an extension to an existing framework, which enables access to knowledge about the different data sources available, including data from operators. To develop the interoperability principle, a specific proposal to provide a (public and encrypted) data management solution to ensure information transparency is presented, which enables semantic data treatment and provides an appropriate context to allow data fusion. This proposal is designed also considering the Privacy by Design option. As a proof of application case, an implementation was carried out regarding the logistics of the delivery of industrial components in the construction sector, where different stakeholders may benefit from shared knowledge under the proposed architecture.
Agriculture and livestock play a vital role in social and economic stability. Food safety and transparency in the food supply chain are a significant concern for many people. Internet of Things (IoT) and blockchain are gaining attention due to their success in versatile applications. They generate a large amount of data that can be optimized and used efficiently by advanced deep learning (ADL) techniques. The importance of such innovations from the viewpoint of supply chain management is significant in different processes such as for broadened visibility, provenance, digitalization, disintermediation, and smart contracts. This article takes the secure IoT-blockchain data of Industry 4.0 in the food sector as a research object. Using ADL techniques, we propose a hybrid model based on recurrent neural networks (RNN). Therefore, we used long short-term memory (LSTM) and gated recurrent units (GRU) as a prediction model and genetic algorithm (GA) optimization jointly to optimize the parameters of the hybrid model. We select the optimal training parameters by GA and finally cascade LSTM with GRU. We evaluated the performance of the proposed system for a different number of users. This paper aims to help supply chain practitioners to take advantage of the state-of-the-art technologies; it will also help the industry to make policies according to the predictions of ADL.
Contemporary 300mm semiconductor manufacturing systems have highly automated and digitalized cyber-physical integration. They suffer from the profound problems of integrating large, centralized legacy systems with small islands of automation. With the recent advances in disruptive technologies, semiconductor manufacturing has faced dramatic pressures to reengineer its automation and computer integrated systems. This paper proposes a Distributed-Ledger, Edge-Computing Architecture (DLECA) for automation and computer integration in semiconductor manufacturing. Based on distributed ledger and edge computing technologies, DLECA establishes a decentralized software framework where manufacturing data are stored in distributed ledgers and processed locally by executing smart contracts at the edge nodes. We adopt an important topic of automation and computer integration for semiconductor research &development (R&D) operations as the study vehicle to illustrate the operational structure and functionality, applications, and feasibility of the proposed DLECA software framework.
The ground work for establishing the industrial 4.0 age involves the tiered architectures that are made up of multiple planes encompassed with the physical things that are embedded with internet capabilities. This infrastructure enables an incorporation of the various functions that are necessary in a manufacturing industry to enhance the efficiency of the industry, and contrivance a highly supple and a self-organizing industry that is smart. On the other hand it becomes essential to preserve the information's safely as many internet enabled devices are utilized and more networks are formed for the proper incorporation of the various activities taking place. Since the conventional methods are inadequate the block chain method was most preferred due to its transparency and highly reliable and expedient services. To further structure a tamper proof network the blockchain is built with the smart contract laid on the system providing the impermeable authenticity on the industrial data transferred by securing the information's against the authentication that is anonymous. The performance of the system is validated to on the basis of security provided on the transactions made, and the cost spent on the proposed design
Blockchain technologies provide a platform for a new wave of project management systems, providing managers with a range of characteristics, capabilities, and feature sets to aid their praxis as they engage in increasingly complex processes and projects. This paper presents an explorative case-study in which open-ended interviews are conducted with practicing project managers. The interviews are analysed to understand currently deployed project management tools, technologies, and methods and to contextualise how blockchain based systems may allow for improvments. Five constructs emerge: transparency, control, dynamic status updating, incentives, and trust. Feedback suggests blockchain based alternatives could offer significantly better performance within each of these constructs, and thus should be explored as the technological backbone to the next generation of project management systems.
Tadas Limba, Andrejus Novikovas, Andrius Stankevičius, Antanas Andrulevičius · 5 authors
Two mainstream topics have been widely discussed over the past few years: ways to reduce the human impact on nature and the way that the industrial revolution 4.0 changes industries. The aim of this research topic is to analyse the positive and negative factors of big data implementation in the sector of cryptocurrency (as part of the industrial revolution 4.0) and in the sector of municipal waste management. The analysis reveals the differences and similarities between the cryptocurrency and municipal waste management sectors in the context of big data. The findings are significant for the estimation of the technological development of digitalized and non-digitalized sectors.
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 paper proposes a functional safety and information security protection mechanism based on blockchain technology. The design of the basic level and integration level blockchain structure of CPS distributed architecture and related functional safety and information security measures are introduced. An effective communication judgment mechanism based on functional safety error threshold is proposed, which is stored and judged by smart contract. And a refund transaction with a clock is proposed to ensure the effective execution of the functional safety error threshold mechanism. The article takes cyber physical machine tool system as an example to describe the SIL judgment method of CPS physical equipment and functional safety loop and combines SIL with fault diagnosis and risk protection. Finally, the rationality of our proposed mechanism is proved by information security, functional security, real-time and maintainability.
Cloud Manufacturing is a manufacturing paradigm that focuses on collaboration and resource utilization. Until recently, little research has been done to combine the perspectives of cloud manufacturing and digital platform ecosystems. In the cloud manufacturing paradigm, the cloud coordinator takes up the dual role of a matchmaker and a platform owner, though, so it is interesting to research how any power dominance of the platform owner can be avoided. To do so, three dimensions of platform governance suggested by Tiwana 2014 – pricing policies, decision rights, and control – were considered in this contribution to recommend a fair value distribution mechanism for platform ecosystems in cloud manufacturing. Requirements for such a solution are formulated in this contribution and design patterns satisfying these requirements are derived. We propose using tokens administrated by distributed ledger technologies and smart contracts to enable a special split revenue scheme that satisfies the
The Industrial Internet of Things (IIoT) plays an important role in the development of smart factories. However, the existing IIoT systems are prone to suffering from single points of failure and unable to provide stable service. Meanwhile, with the increase of node scale and network quantity, the maintenance cost presents to be higher. Such a disadvantage can be effectively compensated by the features such as security, privacy, non-tamperability and distributed deployment supported by the blockchain. In this paper, first, an intelligent manufacturing security model based on blockchain was proposed. Due to the high power consumption and low throughput of the traditional blockchain, IoT devices with limited power consumption can not work independently. Therefore, in this paper, a new Merkle Patricia tree (MPT) was adopted to extend the blockchain structure and provide fast query of node status. Second, since the MPT does not support concurrent operation and the data operation performance deteriorates with high data volume, a lock-free concurrent and cache-based Merkle Patricia tree was proposed (CMPT) to support lock-free concurrent data operation, which can improve the data operation efficiency in multi-core system. The experimental results indicate that, compared with the original MPT, the CMPT proposed in this paper effectively reduced the time complexity of data insertion and data query and improved the speed of block construction and data query.
Blockchain can be defined as distributed ledger technology that can securely and permanently record transactions between parties. The blockchain uses a shared database among many parties, the blockchain can eliminate the need for intermediaries who need to act as trusted third parties to validate, r
Nick Große, David Leisen, Tan Gürpinar, Robert Schulze Forsthövel · 6 authors
In the course of the digital transformation, organizations are not only facing increasing volatility of the markets, but also increasing customer requirements and thus an increasing complexity in production and logistics systems. Therefore, production plants need to become more flexible by transforming conventional production systems to Cyber-physical Production Systems (CPPS). CPPS allow organizations to dynamically react to fluctuations in demand and markets and to introduce new product lines quickly and effectively. The challenge in implementing CPPS is to handle and store relevant data streams between Cyber-physical objects in a secure but transparent way. As CPPS involve a high level of decentralization, the data storage can either be combined with centralized IT-solutions like a Cloud or utilize decentralized IT-technologies like Edge Computing or Distributed Ledger Technologies (DLT) like Blockchains. The paper addresses the suitability of centralized and decentralized technologies in terms of dealing with data streams in the fields of CPPS. For this purpose, based on a paper exploration, appropriate evaluation criteria are derived, followed by a comparison of exemplary centralized and decentralized technologies. The outcome is a qualitative evaluation of the supplement of each technology regarding its suitability of dealing with data streams.
Open access
Economic and Technological Systems Analysis
Digital Transformation in Industry
Advanced Research in Systems and Signal Processing