This paper explores the issues of building digital twins for smart cities, which can be controlled manually or with the assistance of intelligent systems. For these purposes, a specialized logic platform, Delta, is being built, which has such properties as transparency, reliability, and predictability. The Delta platform allows us to represent the digital twins of cities as a network of smart contracts that interact with each other within a unified multi-blockchain system. The inclusion of Delta-learning and Delta-connection modules facilitates knowledge acquisition and utilization for AI-driven process management and sensor integration within smart cities.
Rim Kilani, Ahmed Zouinkhi, Mohamed Naceur Abdelkrim
Internet of Things (IoT) plays a very important and remarkable role in many fields such as smart grids, healthcare, industry, etc. IoT also makes people's lives easier and improves their interactions with each other by using devices and sensors of different sizes that are heterogeneous or homogeneous. As a key part of Industry 4.0, IoT has been widely used in various industrial fields. The integration of Blockchain and IoT technologies in Industry 4.0 plays an important role in improving the performance of systems in Industry. This integration improves classic deterministic interactions between industrial devices to become intelligent interactions. Blockchain is an advanced technology that leads to robust distributed applications. It is a tamperproof, decentralized, immutable and transparent database. In this paper, we present the principle of monetization as a principle of interaction between industrial objects. By integrating Blockchain and smart contract technology, industrial objects can exchange services according to the principle of monetization in a transparent and secure manner.
Artificial Intelligence (AI) algorithms can be employed to enhance the security of the blockchain networks in the era of industry 4.0. Smart contracts, powered by blockchain, can be developed by using the AI capabilities. These contracts can execute themselves based on predefined conditions, automating various processes and reducing the need for intermediaries. Blockchain provides a transparent and immutable ledger for supply chain transactions. AI can be integrated to analyze this data, providing insights into the entire supply chain. This helps in tracking and tracing products, ensuring authenticity, and optimizing the supply chain based on data-driven decisions. AI algorithms can be employed to analyze data from the manufacturing process recorded on the blockchain. This allows for predictive maintenance and quality control, helping to identify and address issues before they result in defects or downtime. AI and blockchain can work together to secure the massive amount of data generated by IoT devices in an Industry 4.0 setting. Blockchain ensures the integrity and immutability of IoT data, while AI can analyze this data for insights and optimization. AI and blockchain can facilitate the creation of decentralized energy grids where AI algorithms optimize energy distribution and blockchain ensures transparent and secure energy trading through smart contracts. AI and blockchain can support decentralized and collaborative manufacturing networks where different entities can securely and efficiently collaborate on production processes. Blockchain enables individuals or organizations to securely monetize their data. AI can help analyze and determine the value of data, ensuring fair compensation in tokenized ecosystems. In this paper, applications of AI-Powered Blockchain Technology in Industry 4.0 is reviewed and discussed and future research works are also suggested. As a result, efficiency, transparency, and security across various industrial processes can be enhanced by analyzing the recent achievements in AI-Powered Blockchain Technology in Industry 4.0.
This article explores the concept of humanâautonomous organizations (HAOs) based on decentralized autonomous organizations (DAOs) and operations as well as human, artificial, natural, and organizational intelligence and their roles in shaping smart societies in the context of Industry 5.0 and Society 5.0. It discusses the potential of AI-generated content and prompt engineering in specific goal-guided manufacture and governance. Additionally, the article introduces the concept of the HAO as a framework for integrating human intelligence to achieve fair, transparent, and accountable decision making within DAOs. The proposed HAO reduces the risk of instability and unreliability in âhuman-in-the-loopâ copilot systems and humanâmachine hybrid systems, leading to more reliable, secure, and flexible systems. It provides insights into the future management of smart societies and the symbiotic relationship between human ingenuity and the suite of emerging new AI technologies.
Carmelo Felicetti, Antonella Guzzo, Giuseppe Manco, Francesco Pasqua · 7 authors
Item identification is an important issue in modern supply chains where product items are traced by means of electronic tags that, despite the advantages they bring in terms of automation, are still subject to counterfeiting attacks such as tag modification, cloning, and re-application. To counter these threats (i) tags must be able to safely demonstrate their identity without giving attackers the ability to clone them or modify their content, and (ii) auxiliary identification techniques should be adopted in the case tags are removed from original items and reapplied to fake ones. Using Physically Unclonable Functions as tag âdigital fingerprintâ has proven to be a viable solution for tag authentication. On the other hand, artificial intelligence has proven its effectiveness in the field of object identification. In this paper we describe a tag architecture immune to cloning and modification attacks, and illustrate how this can be coupled with a product item in a supply chain scenario to confer a stable and durable identity for authentication, in order to identify the items and track them in a distributed ledger framework. We also propose a deep learning approach to perform anti-counterfeiting controls when tag reapplication attacks are in place.
Blockchain Technology Applications and Security
Physical Unclonable Functions (PUFs) and Hardware Security
A âkiller appâ denotes any computer programme or software that is so essential or desirable that it demonstrates the fundamental worth of a larger technology. It is portrayed as virtually indispensable or vastly superior to competing products. Supply chain transparency (SCT) has long been ripe for disruption and in need of such a technological solution. Several applications have appeared on the market - but few have coalesced the complex tasks required for full transparency. To date, there is no âkiller appâ for fashion supply chain transparency. Applications that facilitate SCT including tracking and tracing mechanisms as well as data repository and distributed ledger systems like blockchain are complex and daunting for most fashion businesses. Industry powerplays and lack of trust are blocking the universal adoption of current solutions. This chapter aims to explore how SCT can be adopted by firms and facilitated at scale. We advance current knowledge of digital technology applications for SCT through the theoretical lens of organisational culture to decipher how start-ups are developing technology for adoption by fashion firms. Using a single case study methodology, we analysed one hybrid start-up (fashion and technology firm) that has developed and implemented advanced digital technology initiatives at scale. From our case analysis, we provide insights into the requirements to build a digital ecosystem - one with which most firms are not yet familiar. We discuss key implications for theory and practise, based on our findings.
Additive manufacturing (AM) is a revolutionary technology that has the potential to transform the manufacturing industry and impact the digital economy. while AM presents opportunities for the digital economy, it is important for AM companies to implement strong cybersecurity measures to protect their designs, software, and equipment from attacks. To address these challenges, this paper discusses a rigorous cyber security measure to regularly assess AM-related threats. This paper outlines a new intelligence and information acquisition system (IIAS) that identifies threat-related information and Indicators of Compromise (IOC) in AM. The system consists of three subsystems: a) acquisition of threat information related to AM with an emphasis on integrity violations of design files in the AM ecosystem, b) quantification and prioritisation of threats based on severity metrics, and c) verifies and detects data breaches and exchanges on Hyperledger Fabric. Furthermore, IIAS verifies the integrity of parts related to a ledger, which helps detect violations and analyse various interactions in AM systems. It also provides the basis for achieving an end-to-end audit trail that ensures tamperproof tracking and delivery of AM artefacts within the acceptable risk profile.
Additive Manufacturing and 3D Printing Technologies
Nikolai Kazantsev, Oleksii Petrovskyi, Julian M. MĂŒller
Rapid market changes call for demand-driven collaborations in manufacturing, which trigger supply chain evolution to more distributed supply structures. This paper explores the system dynamics of the largest European aerospace manufacturer's supply chain. We conceptualise a manufacturing ecosystem by observing the impacts of supplier development, digital platforms, smart contracting, and Industry 4.0 on demand-driven collaborations in time. We contribute to the literature on ecosystem strategy, particularly for regulated industries, by disclosing the role of demand-driven collaborations in supporting the ecosystems' growth. We provide manufacturing firms with an open-access tool to exemplify their ecosystem development and produce initial training datasets for AI/ML algorithms, supporting further analytics.
Implementing digital transformation in higher education is now required for effective adaptation to rapid technological advances. Utilizing Enterprise Architecture (EA) with blockchain technology is a recommended strategic approach for implementing digital transformation. The college first ascertains the University's digital transformation requirements and goals, which include data management, security, operational efficiency, and transparency. In addition, formulating a strategic plan to determine the optimal integration of blockchain technology within the college's architectural framework, including the judicious selection of the most suitable blockchain platform, is essential. In addition, developing a company's architecture must prioritize seamless integration with existing systems while upholding data security and consistency principles. Consideration should be given to the significance of training and awareness building among faculty and students. In addition, the implementation process must be conducted in phases with consistent monitoring and evaluation. The success of this project is contingent upon the formation of partnerships and collaborations with blockchain technology companies, as well as a thorough understanding of the applicable regulatory framework. By adopting this methodology, the University can increase operational efficiency, bolster data security measures, and improve the educational experience. This research aims to increase efficiency, data security, transparency, and educational innovation in universities using Blockchain Technology and University Enterprise Architecture.
Rui Qin, Juanjuan Li, Xiaolong Liang, FeiâYue Wang
This paper presents Management-Oriented Operating Systems (M2OS) that leverages the power of parallel intelligence theory, Decentralized Autonomous Organizations (DAOs) and foundation models to revolutionize the manner of management in Cyber-Physical-Social Systems (CPSS). The parallel architecture on M2OS is proposed, including the parallel interactive actual M2OS and artificial M2OS. Among them, the artificial M2OSs provide digital infrastructures for organizations to operate, collaborate, and make decisions in the virtual space, and conduct computational experiments to evaluate management decisions and predict future states of the actual M2OS. Through parallel execution and closed-loop feedback between the artificial and actual M2OSs, the management and control, experimentation and evaluation, as well as learning and training of the actual M2OS can be realized. Moreover, the functional layers of M2OS, including the infrastructure layer, data layer, scenario layer, modeling layer, decision layer, and application layer, are discussed. These layers work together to support the intelligent, autonomous, collaborative, and adaptive nature of the M2OS, and facilitate data-driven decision-making, optimize business operations, and empower managers with real-time actionable insights. The proposed M2OS paradigm has great potential to transform the management paradigm and opens up new possibilities for intelligent and collaborative decision-making.
Blockchain is a form of digital distributed ledger, referring to databases decentralized across numerous users, facilitating peer-to-peer transactions by eliminating or reducing the need for intermediaries to conduct, validate, or authenticate them.It is characterized by transparency, data immutability and traceability, and consensus processes validating cryptographic signatures.The architecture, engineering, construction, and operations (AECO) industry is increasingly interested in blockchain.Lean construction (LC), a value-focused production management concept, has long been challenging conventional project management practices in AECO.Lack of conversation, however, surrounds whether and how blockchain can (or should) impact LC developments -and vice versa.And if that impact exists -is it significant enough to create value for the related stakeholders?This article offers a conceptual synergistic framework of interactions between blockchain and LC, which can facilitate an understanding on whether there is value in their combined use.A systematic literature review and analysis serve as the foundation of this research.The findings show that LC can be facilitated by blockchain through trust building for relational procurement, data recording for some key activities (e.g.offsite construction, Last Planner System), and streamlining some non-value activities (e.g.payments).In return, blockchain can gain relevance for project management practices when it is defined and implemented in a LC framework.Also, LC can help improve blockchain-related workflows and decision making.
To address the construction industryâs fragmented resources and to facilitate its service-oriented transformation, a new service paradigm of a construction service trading platform (CSTP) enables the sharing and trading of distributed construction services. However, the current platform with centralized management cannot provide an online trading environment with information security and transaction transparency without the involvement of a trusted third party. Existing approaches to selecting services for complex tasks also ignore security and transparency, even though these are critical to the platform. This study selected services for complex tasks securely and transparently, and made three contributions. First, an innovative blockchain-based construction service trading platform (B-CSTP) is proposed, which can provide a secure and transparent trading environment. Second, smart contractâbased task decomposition and service composition (TDSC) was established, in which three main functions were designed to implement the service selection approach for the complex task. Third, an Ethereum-based system was established to demonstrate the proposed B-CSTP and smart contracts for TDSC. A survey of construction professionals was established to evaluate the framework of the proposed B-CSTP, and experiments were conducted to evaluate the designed functions of the smart contract for TDSC. The results show that the proposed B-CSTP and the designed function of smart contracts are feasible. The survey reveals that 80% and 70% of survey participants had positive attitudes toward its security and transparency, respectively. Furthermore, the experiment results show that the design functions of smart contracts were effective and reasonable in selecting services. This study contributes to the new service paradigm and the problem of selecting services by combining blockchain and smart contract technology. This study expands the application scenarios for blockchain in CSTP and makes significant advances in using smart contracts for TDSC.
Process automation and mass customisation requirements of modern manufacturing systems are driven by artificial intelligence (AI). As AI derives decisions from data, securing the data against tampering is crucial to prevent ensuing operational risks. Additionally, manufacturing systems necessitate collaboration, transparency, and trust among participants while preserving a competitive advantage. Thus, we position blockchain, an enabler of transparent and secure operations, as a security solution for AI-assisted manufacturing systems. In this conceptual viewpoint paper, we present a framework to integrate blockchain in AI-assisted manufacturing systems. We highlight the special needs of manufacturing BCs over generic BCs. We delineate the ways in which manufacturing can be a beneficiary of the synergy between AI and BC. We discuss how BC and AI can accelerate early-phase product design, collaboration, and manufacturing processes and secure supply chains against counterfeit products and for ethical consumerism. Lastly, we identify the needs of modern manufacturing systems and cite a few examples of organisational failures to underscore the importance of security while delineating the significant challenges in adopting blockchain-based solutions in the manufacturing industry.
Giampaolo Bovenzi, Giuseppe Aceto, Valerio Persico, Antonio PescapĂš
Solutions based on Blockchain (BC) technologies are gaining more and more attention in the context of Industry 4.0 (I4.0). While the research community has provided significant effort in either BC or I4.0 research domains, the complex implications of the adoption of BC technologies in this specific context are not analyzed in depth. This is a serious drawback because of the multiple and heterogeneous interactions between participants in the production network. In fact, researchers and practitioners involved in planning and deployment of I4.0 solutions may still face questions related to the needs solved by BC, the I4.0-related adoption scenarios explored, and the Key Performance Indicators to assess the effectiveness of these technologies. In this paper, we survey the existing literature to identify shared definitions and drivers that lead to the adoption of BC technologies in I4.0. Then, we analyze several practical use casesâunder the umbrella (smart) contexts of Factory, Healthcare, and Energyâhighlighting the need for comprehensive analysis including not only functional and architectural characteristics but also performance. We collect a number of Key Performance Indicators and organize the dozen aliases and variants, explaining their relationships and pointing at the relevant studies. Finally, we discuss limitations, challenges and future directions related to BC application to I4.0, and the role of performance analysis in this research.
Quality management (QM) of additive manufacturing (AM) processes is currently immature in terms of transparency, traceability and security. In particular, quality-relevant documents are not documented and communicated in a traceable and transparent manner, which often leads to quality deficiencies. However, combining AM with blockchain technology can enable a solution that maps the AM value chain digitally, transparently, traceably and securely in a part record. In this work, a quality assurance (QA) concept for the metal-based material extrusion (MEX) process is developed that enables a digital representation of the value chain in the form of an AM part record. The decentralized solution presented in this work uses an architecture consisting of a web application for data acquisition, a decentralized storage solution for storing larger amounts of data, a smart contract for capturing manufacturing events and the Ethereum blockchain for transparent, secure and traceable storage of blockchain data. The AM part record enables traceable and constantly available digital documentation of quality information. The cost-effectiveness of the solution is also shown in a demonstration study. The research results highlight the benefits of a blockchain-based AM part record for digital manufacturing documentation and represent an efficient alternative or extension to existing QM and QA solutions in AM.
Open access
Additive Manufacturing and 3D Printing Technologies
Nana Akua Adu-Amankwa, Farzad Pour Rahimian, Nashwan Dawood, Chansik Park
This paper reviews the potential applications of Digital Twins (DT) and Blockchain (BC) technologies throughout the building lifecycle phases by conducting a double-stranded systematic review of papers on the possible use of DT and BC. The results revealed the increasing interest in DT and BC and their potential use in all building lifecycle phases; however, studies focused mainly on the construction phase. The findings also revealed unique features of DT and BC, potentially supporting the proposal for their collaborative implementation to enhance building lifecycle management. This review's findings positioned the argument for more research on integrating DT and BC to augment building lifecycle management and the need to explore their relevance or role when transitioning from construction to post-construction. This paper elucidates readers on the potential role of DT and BC while developing a built asset and suggests directions for future research.
The supply chain sector operates in a complex environment and faces various challenges, including fluctuations in demand, disruptions, and the requirement of adhering to regulations. The emergence of groundbreaking technologies such as blockchain, AI, and IoT is driving significant changes in the industry, resulting in improved efficiency, transparency, and security measures. This research paper has used the case-study method to develop to present a dynamic risk management framework that integrates blockchain technology and artificial intelligence. By building a distributed, decentralised ledger that records transactions safely and openly, blockchain technology can be incorporated into the supply chain sector. This framework comprises a risk association tree, smart contracts, and a risk item ledger, offering notable benefits such as enhanced risk management capabilities, operational efficiency, transparency, and potential for collaboration. However, it is essential to note that implementing this framework may involve complexity, necessitate modifications to existing processes, and introduce new risk elements.
Walaa AlKhader, Raja Jayaraman, Khaled Salah, Andrei Sleptchenko · 6 authors
Purpose Quality 4.0 (Q4.0) leverages new emerging technologies to achieve operational excellence and enhance performance. Implementing Q4.0 in digital manufacturing can bring about reliable, flexible and decentralized manufacturing. Emerging technologies such as Non-Fungible Tokens (NFTs), Blockchain and Interplanetary File Storage (IPFS) can all be utilized to realize Q4.0 in digital manufacturing. NFTs, for instance, can provide traceability and property ownership management and protection. Blockchain provides secure and verifiable transactions in a manner that is trusted, immutable and tamper-proof. This research paper aims to explore the concept of Q4.0 within digital manufacturing systems and provide a novel solution based on Blockchain and NFTs for implementing Q4.0 in digital manufacturing. Design/methodology/approach This study reviews the relevant literature and presents a detailed system architecture, along with a sequence diagram that demonstrates the interactions between the various participants. To implement a prototype of the authors' system, the authors next develop multiple Ethereum smart contracts and test the algorithms designed. Then, the efficacy of the proposed system is validated through an evaluation of its cost-effectiveness and security parameters. Finally, this research provides other potential applications and scenarios across diverse industries. Findings The proposed solution's smart contracts governing the transactions among the participants were implemented successfully. Furthermore, the authors' analysis indicates that the authors' solution is cost-effective and resilient against commonly known security attacks. Research limitations/implications This study represents a pioneering endeavor in the exploration of the potential applications of NFTs and blockchain in the attainment of a comprehensive quality framework (Q4.0) in digital manufacturing. Presently, the body of research on quality control or assurance in digital manufacturing is limited in scope, primarily focusing on the products and production processes themselves. However, this study examines the other vital elements, including management, leadership and intra- and inter-organizational relationships, which are essential for manufacturers to achieve superior performance and optimal manufacturing outcomes. Practical implications To facilitate the achievement of Q4.0 and empower manufacturers to attain outstanding quality and gain significant competitive advantages, the authors propose the integration of Blockchain and NFTs into the digital manufacturing framework, with all related processes aligned with an organization's strategic and leadership objectives. Originality/value This study represents a pioneering endeavor in the exploration of the potential applications of NFTs and blockchain in the attainment of a comprehensive quality framework (Quality 4.0) in digital manufacturing. Presently, the body of research on quality control or assurance in digital manufacturing is limited in scope, primarily focusing on the products and production processes themselves. However, this study examines the other vital elements, including management, leadership and intra- and inter-organizational relationships, which are essential for manufacturers to achieve superior performance and optimal manufacturing outcomes.