Security and privacy are primary concerns in IoT management. Security breaches in IoT resources, such as smart sensors, can leak sensitive data and compromise the privacy of individuals. Effective IoT management requires a comprehensive approach to prioritize access security and data privacy protection. Digital twins create virtual representations of IoT resources. Blockchain adds decentralization, transparency, and reliability to IoT systems. This research integrates digital twins and blockchain to manage access to IoT data streaming. Digital twins are used to encapsulate data access and view configurations. Access is enabled on digital twins, not on IoT resources directly. Trust structures programmed as smart contracts are the ones that manage access to digital twins. Consequently, IoT resources are not exposed to third parties, and access security breaches can be prevented. Blockchain has been used to validate digital twins and store their configuration. The research presented in this paper enables multitenant access and customization of data streaming views and abstracts the complexity of data access management. This approach provides access and configuration security and data privacy protection.
Habib Sadri, İbrahim Yitmen, Lavinia Chiara Tagliabue, Florian Westphal
Digital Twins (DTs), enriched with Artificial Intelligence (AI) and Blockchain technology, promise a revolutionary breakthrough in smart asset management and predictive maintenance in the built environment. This study aims to portray a conceptual framework of Blockchain and AI-based DTs and outline its key characteristics, requirements, and system architecture by composing a functional model using IDEF0. Such an approach is expected to enhance predictive maintenance in building facilities, simplify the management and operation of smart built environments, and ultimately deliver valuable outcomes for facility operators, real estate practitioners, and end-users.
Blockchain technology, as a well-known technology in financial spaces, has many advantages in non-financial industries and supply chains. Two of the main benefits of blockchain technology are smart contracts and distributed decision-making processes. These features can be especially useful in implementing Industry 4.0. Moreover, this technology can increase productivity in supply chains by enhancing transparency, reducing operational costs, and improving monitoring and supervision throughout the lifecycle of products. In this paper, we introduce a blockchain-based architecture for a supply chain in cloud architecture. This approach leads to the more efficient implementation of Industry 4.0 and increases sustainability in the supply chain. In this study, we aim to investigate whether the proposed blockchain-based platform affects sustainability in the supply chain. From a sustainability perspective, we solve the large-scale problem of a cloud-based production–distribution system in centralized and distributed states. The results of the solution indicate a significant improvement in the decentralized state compared to the centralized state and this improvement enhances sustainability in the supply chain. We verify the proposed model by considering an axiomatic design algorithm. In the distributed model, the system cost is reduced by up to 45%, and the solving time is decreased by approximately 51% in pessimistic conditions and by about 87% in optimistic conditions. These improvements directly enhance economic and environmental sustainability, resulting in reduced energy consumption.
Marco Picone, Stefano Mariani, Antonio Virdis, Paolo Castagnetti
The Metaverse has been recently envisioned as the next technological revolution with the idea of building fully immersive virtual worlds where users can interact with each other and with mixed-reality environments and objects. The relationship between the digital and the physical worlds represents a challenging opportunity to foster the idea that virtual experiences and interactions can complement and enhance reality enabling the definition of new use cases and services. In this context, Metaverse’s technologies need to rely on a connected, trustworthy, and highly detailed digital representation of users and objects to build an effective virtual world based on trusted and fresh information from the physical world. The need to decouple responsibilities through a multi-layered vision allows Metaverse’s applications to focus only on their business goal by relying on a cyber-physical layer enabling bi-directional communication with users and devices, accessing trusted information, invoking available actions, and retrieving immutable historical data. In this paper, we analyze and propose the combination of Digital Twins and Blockchain technologies as strategic pillars for bridging the gap between the virtual and the physical worlds and supporting the creation of the Metaverse.
The traditional mode of cooperation between enterprises still suffers from major problems, including data privacy leakage, data falsification, and inefficient collaboration in data sharing. These challenges make it difficult for enterprises to ensure that their cooperative suppliers adopt sustainable practices in standards identification and operation processes. This paper proposes a “Value–Standard–Process” collaborative framework for blockchain-based enterprise data governance that helps ensure a high degree of data security, a high reliability of collaborative tasks, and a high transparency of value transformation. First, this paper proposes a new collaborative mode for blockchain-based manufacturing in the sharing economy, including the non-linear dynamic evaluation and value balancing mechanism of data with multiple attributes, a trusted data governance mechanism for blockchain-based manufacturing, and a smart contract generation mechanism for value-driven collaboration. Second, this paper explains these three components and the implementation of the overall framework. Third, this paper verifies the applicability and achievability of the proposed framework through experiments. Establishing the value-driven multi-level blockchain-based collaboration mode facilitates the effective flow of production factors and promotes trust in the digital economy of sustainability.
Mohammed Alsadi, Junaid Arshad, Jahid Ali, Alousseynou Prince · 5 authors
Supply chain networks are complex structures which introduce significant challenges regarding transparency in production and traceability of components, making product certification non-trivial. Visibility within quality assurance processes is critical to this and is particularly important for autonomous & driver-less vehicles which rely on correct operation of individual parts (in the absence of human intervention) to achieve safety of such vehicles. Failure to ascertain quality assurance of parts can result in rogue behaviour among driver-less vehicles which can result in a risk to human lives. In this paper, a blockchain-based approach - TruCert, is proposed which achieves trustworthy product certification through enhanced visibility within tier 1 and beyond for complex automotive supply chains. Leveraging blockchain technology, TruCert’s potential to improve product quality assurance is demonstrated whilst also strengthening supply chain resilience to combat risks and uncertainties. Utilising the use-case of autonomous connected vehicles manufacturing, design and development of TruCert solution is presented including detailed system design, data model, and smart contracts & oracle implementations. TruCert enables trustworthy part certification across supply chain beyond tier 1 whilst achieving interoperability with heterogeneous systems across suppliers and other stakeholders. Outcomes of evaluation with respect to cost, performance, and security are also presented which highlight the effectiveness of the approach whilst identifying directions for future work.
Occupational stress among health workers is a pervasive issue that affects individual well-being, patient care quality, and healthcare systems' sustainability. Current time-tracking solutions are mostly employer-driven, neglecting the unique requirements of health workers. In turn, we propose an open and decentralized worker-centered solution that leverages machine intelligence for occupational health and safety monitoring. Its robust technological stack, including blockchain technology and machine learning, ensures compliance with legal frameworks for data protection and working time regulations, while a decentralized autonomous organization bolsters distributed governance. To tackle implementation challenges, we employ a scalable, interoperable, and modular architecture while engaging diverse stakeholders through open beta testing and pilot programs. By bridging an unaddressed technological gap in healthcare, this approach offers a unique opportunity to incentivize user adoption and align stakeholders' interests. We aim to empower health workers to take control of their time, valorize their work, and safeguard their health while enhancing the care of their patients.
Intelligent manufacturing under Industry 4.0 assimilates sophisticated technologies and artificial intelligence for sustainable production and outcomes. Blockchain paradigms are coined with Industry 4.0 for concurrent and well-monitored flawless production. This article introduces Sustainable Production concerned with External Demands (SP-ED). This method is more specific about energy production and the distribution for flawless and outage-less supply. First, the energy demand is identified for internal and external users based on which sustainability is planned. Secondly, Ethereum blockchain monitoring for a similar production and demand satisfaction is coupled with the production system. From two perspectives, the monitoring and condition satisfaction processes are validated using federated learning (FL). The perspectives include demand distribution and production sustainability. In the demand distribution, the condition of meeting the actual requirement is validated. Contrarily, the flaws in internal and external supply due to production are identified in sustainability. The failing conditions in both perspectives are handled using blockchain records. The blockchain records reduce flaws in the new production by modifying the production plan according to the federated learning verifications. Therefore, the sustainability for internal and external demands is met through FL and blockchain integration.
Real-time and vision-based quality control for industrial processes has drawn great interest from both scientists and practitioners, particularly following the transition to Zero Defect Manufacturing (ZDM) and Industry 4.0. Despite considerable progress, most ZDM approaches focus on the accuracy of the inspection process, often neglecting critical factors for application in the shop floor. On one hand, near real-time methods are needed for early defect detection and containment. On the other hand, data scarcity is an issue causing AI methods to overfit. Another concern is the accountability of AI results, since even if an AI pipeline is successfully deployed, its predictions are not verifiable in the long term. In this work, we explore a real-time solution based on lightweight Deep Residual Networks and Blockchain technology to address these issues. Concretely, we propose a two-phase training strategy to boost the performance of baseline classifiers while maintaining low inference times. The performance of the proposed methodology is presented in two different industrial use cases with strict timing requirements, one concerning battery assembly line and the other antenna manufacturing. We validate the proposed method for defect detection and compare the results with common training strategies demonstrating an improvement of 3% and 10% in F1-score and accuracy on the two cases respectively, while lowering inference time by 2.2× compared to existing light architectures. Contributing to the accountability of AI results, we present an IoT framework using Blockchain deployed in Private Ethereum.
Information security has more demand for digital technology. Every industry transfers its data through computer networks for legal communication. The Internet of Things (IoT), sensor-based, is one of the most current advanced tools that can handle appropriate measures to control data operations across manufacturing industries. The demand for predictive machine reliability and quality drives the development of intelligent manufacturing technologies. To this goal, a variety of machine learning algorithms are being studied. Data protection and monitoring is also another concern that is a critical component of the organization. To overcome these issues, the proposed method uses Blockchain Technology (BCT) and Machine Learning to secure the information operations and manage a dataset. Significant data approaches were employed to organize and evaluate the obtained dataset. BCT allows collecting sensor user access data, whereas ML classifiers distinguish between normal and malicious behavior to detect attacks. DoS, DDoS, intrusion, a man in the middle (MitM), brute force, cross-site scripting (XSS), and searching are the attacks detected by BCT. Furthermore, the hybrid prediction technique assessed the fault detection prediction component. The program's quality control was set using non-linear machine learning techniques that represented the complicated world and determined the actual positive rate of the standard control methodology used by the platform. The experimental result shows that the proposed method outperforms empirical metrics such as accuracy, precision, recall, and response time. The proposed method efficiently provides security between innovative manufacturing transactions.
Technology is an important tool in the armory of state-of-the-art innovations, in terms of both digital expansions and disruptions. With blockchain technology gaining momentum, different industries are emphasizing experimentation with it. Nowadays, organizations are emphasizing towards agile and leaner supply chains with end-to-end prominence via the incorporation of this latest technology, thereby boosting services across the world. The revolutionary features of blockchain technology are paving the way for greater opportunities for supply chain businesses. The technology has the potential to become a supply chain data utility and repository that offers benefits to all its users, such as unique market information that would be otherwise unavailable from any other source. This paper contemplates the need for blockchain technology in the supply chain and its contribution to enhancing the overall efficiency and demand planning processes of businesses. It discusses the latest market trends and factors driving the need for the incorporation of blockchain in the supply chain sector and the future scenario. Different use cases of the technology, market challenges in the implementation of the technology, and the solutions offered by different companies to address such problems have also been discussed.
Feruz K. Elmay, Mohammad Madine, Khaled Salah, Raja Jayaraman
The distribution, traceability, and management of shipping container logistics require secure data flow and trusted transactions. Digital Twins (DTs) can realize these features by offering shipping tracking and traceability, process flow and status monitoring, and management of the physical containers all in a remote manner. However, the data of a DT itself is typically stored, controlled, and managed by a centralized entity, which is often the original creator of the physical container. Having a centralized entity can cause mistrust. The centralized entity may alter, tamper, or delete the digital twin data. To overcome this problem, this paper proposes trusted sharing and management of DTs for shipping containers by using Non-Fungible Tokens (NFTs). NFTs are digital tokens that hold unique data stored, controlled, and managed in a decentralized and immutable blockchain ledger. We extend in this paper the use of NFTs to tokenize shipping container DTs and their metadata. The proposed solution uses NFTs and Ethereum blockchain smart contracts to offer decentralization, security, transparency, traceability, and immutability to the data and processes involved in the creation, storage, and management of DTs of shipping containers. To demonstrate our solution, we create a DT of a shipping container using Microsoft Azure Digital Twins services and showed how to tokenize it using NFT. We assess the system using various test cases to evaluate its main functionalities. Furthermore, we analyze the cost of transactions and the security of the smart contracts code. We have made the code of our smart contracts publicly available on GitHub.
Businesses are keen to implement new technologies like virtual reality, artificial intelligence (AI), augmented reality, big data, etc. as they see profitable business applications. The supply chain and the larger business community have been paying attention to Metaverse as one of the technology disruptions. The metaverse is being enhanced by several variables, including mobile-based always-on access and virtual currency linkage with reality. Additionally, the growth of the Metaverse and Non-Fungible Tokens (NFT) has taken the metaverse to a new level. This paper performs a comprehensive analysis of the metaverse's attributes, uses, and prospects in global supply chains. The current metaverse-focused study discloses the state of the research and outlines future research goals by reviewing and analysing recent articles that reveal metaverse uses across multiple supply chain activities. It has been demonstrated that the metaverse has several features that help businesses improve supply chain efficiency and customer engagement, including increased visibility into operations, facilities, inventory, and capacity. These characteristics fuelling the metaverse's application in supply chain management and logistics operations. The study further found that metaverse-related research has been extremely growing in the areas of healthcare, retail, and infrastructure, while there is still scope for study in the field of supply chain security and traceability. Finally, it is emphasized that metaverse-related research in logistics, supply chain operations, and agriculture supply chains has the potential to be explored.
The purpose of this study is to evaluate how Blockchain Technology (BCT) can support the implementation of Lean Automation. We conducted a systematic literature review to understand how BCT is being implemented in the supply chain management (SCM) domain and to evaluate how this technology can be used to reduce inefficiencies in supply chains. Firstly, we developed a holistic taxonomy of wastes to identify the most common non-value activities. Then, both inductive and deductive content analyses were performed, the latter being coded using the taxonomy. Our findings identified the most common BCT-based application themes in SCM and ways that this technology can be used to support future implementation of Blockchain-enabled Lean Automation (B-eLA). Additionally, we proposed a future research agenda. The study provides important contributions at the intersection between BCT, lean production, and Industry 4.0 within the context of SCM and seeks to exploit BCT’s potential to improve businesses’ efficiency, effectiveness and productivity.
Blockchain-related studies that focus on solving AECO (Architecture, Engineering, Construction and Operation) digital management environment issues, such as data protection and data ownership, show the projected benefits of Blockchain-based digital construction environments. However, adopting such technology will require a holistic approach to ensure it does not result in data redundancy, leading to digital system inefficiencies. This article studies the Blockchain construction synergies from the infrastructure point of view to understand its future in construction. The article visualises Blockchain infrastructure elements and fits them within the construction project’s digital environment. A novel framework for Blockchain orchestration and implementation and a blueprint for developing Blockchain applications for construction are presented. The proposed blueprint is then used to develop a Blockchain application using Hyperledger Firefly. The article builds on the previous literature and Blockchain applications on the Ethereum public Blockchain. The expected benefit of such a framework is providing a practical perspective on the implementation side of Blockchain in construction.
Barbara Balon, Krzysztof Kalinowski, Iwona Paprocka
This article presents the architecture of integration of blockchain technology (BCT) and the Internet of Things with the planning of production processes. The authors proposed a shared concept of a distributed machine database based on BCT. As part of the work, a network of connections for the exchange of production resources was created using nodes communicating in a decentralized system, which at the same time serves as an integration of the virtual and real environment. Particular attention was focused on developing an algorithm for the efficient division of production tasks between all interested network users. BCT is used to conclude smart contracts and transactions and ensure the security of exchanged production data within shared ledgers. The proposed concept is a solution enabling a modern approach to the interdisciplinary management of production resources while maintaining the highest cybersecurity standards.
The integration of blockchain and digital twins (DT) for better building-lifecycle data management has recently received much attention from researchers in the field. In this respect, the adoption of enabling technologies such as artificial intelligence (AI) and machine learning (ML), the Internet of Things (IoT), cloud and edge computing, Big Data analytics, etc., has also been investigated in an abundance of studies. The present review inspects the recent studies to shed light on the foremost among those enabling technologies and their scope, challenges, and integration potential. To this end, 86 scientific papers, recognized and retrieved from the Scopus and Web of Science databases, were reviewed and a thorough bibliometric analysis was performed on them. The obtained results demonstrate the nascency of the research in this field and the necessity of further implementation of practical methods to discover and prove the real potential of these technologies and their fusion. It was also found that the integration of these technologies can be beneficial for addressing the implementation challenges they face individually. In the end, an abstract descriptive model is presented to provide a better understanding of how the technologies can become integrated into a unified system for smartening the built environment.
This paper proposes a framework to automate the generation of traceable and protected documentation of complex assembly processes. The final assembly in aviation, automotive, and appliances industries is a rigorous process that has limited capabilities of full traceability associated with: (1) the parts installed, (2) their fabrication processes, and (3) the assembly work. This is also the case for each of its sub-assemblies. The thousands of parts forming a hierarchy of sub-assemblies that are dynamically accumulated to compose the final assembly make full traceability a challenging feat that is almost unsurmountable. Such full traceability along the entire supply chain requires considerable cost and effort since it must be based on documentation of most assembled parts, assembly tasks, and inspection tasks that compose the full assembled product. In addition, security measures are needed to prevent hostile hacking and unauthorized approach to the assembly documentation throughout the entire supply chain. The related documentation and repeated verifications require considerable effort and have many chances for human errors. So, automating these processes has great value. This article expounds a framework that harnesses blockchain and smart-contract technology to offer automated traceable and protected documentation of the assembly process. For this purpose, we expand the concept of a Bill-Of-Assembly (BOA) to incorporate data from the bill of materials (BOM), the associated assembly activities, the associated activities’ specification parameters and materials, and the associated assembly resources (machines and/or operators). The paper defines the operation of the BOA with blockchain and smart-contract technology, for attaining full traceability, safety, and security, for the entire assembled product. Future research could extend the proposed approach to facilitate the usage of the BOA data structure in constructing a digital twin of the entire simulated system.
Abdullah Ayub Khan, Asif Ali Laghari, Peng Li, Mazhar Ali Dootio · 5 authors
Due to digitalization, small and medium-sized enterprises (SMEs) have significantly enhanced their efficiency and productivity in the past few years. The process to automate SME transaction execution is getting highly multifaceted as the number of stakeholders of SMEs is connecting, accessing, exchanging, adding, and changing the transactional executions. The balanced lifecycle of SMEs requires partnership exchanges, financial management, manufacturing, and productivity stabilities, along with privacy and security. Interoperability platform issue is another critical challenging aspect while designing and managing a secure distributed Peer-to-Peer industrial development environment for SMEs. However, till now, it is hard to maintain operations of SMEs' integrity, transparency, reliability, provenance, availability, and trustworthiness between two different enterprises due to the current nature of centralized server-based infrastructure. This paper bridges these problems and proposes a novel and secure framework with a standardized process hierarchy/lifecycle for distributed SMEs using collaborative techniques of blockchain, the internet of things (IoT), and artificial intelligence (AI) with machine learning (ML). A blockchain with IoT-enabled permissionless network structure is designed called "B-SMEs" that provides solutions to cross-chain platforms. In this, B-SMEs address the lightweight stakeholder authentication problems as well. For that purpose, three different chain codes are deployed. It handles participating SMEs' registration, day-to-day information management and exchange between nodes, and analysis of partnership exchange-related transaction details before being preserved on the blockchain immutable storage. Whereas AI-enabled ML-based artificial neural networks are utilized, the aim is to handle and optimize day-to-day numbers of SME transactions; so that the proposed B-SMEs consume fewer resources in terms of computational power, network bandwidth, and preservation-related issues during the complete process of SMEs service deliverance. The simulation results present highlight the benefits of B-SMEs, increases the rate of ledger management and optimization while exchanging information between different chains, which is up to 17.3%, and reduces the consumption of the system's computational resources down to 9.13%. Thus, only 14.11% and 7.9% of B-SME's transactions use network bandwidth and storage capabilities compared to the current mechanism of SMEs, respectively.
Mauro Isaja, Phu H. Nguyen, Arda Göknil, Sagar Sen · 14 authors
There is a current wave of a new generation of digital solutions based on intelligent systems, hybrid digital twins and AI-driven optimization tools to assure quality in smart factories. Such digital solutions heavily depend on quality-related information within the supply chain business ecosystem to drive zero-waste value chains. To empower zero-waste value chain strategies with meaningful, reliable, and trustful data, there must be a solution for end-to-end industrial data traceability, trust, and security across multiple process chains or even inter-organizational supply chains. In this paper, we first present Product, Process, and Data quality services to drive zero-waste value chain strategies. Following this, we present the Trusted Framework (TF), which is a key enabler for the secure and effective sharing of quality-related information within the supply chain business ecosystem, and thus for quality optimization actions towards zero-defect manufacturing. The TF specification includes the data model and format of the Process/Product/Data (PPD) Quality Hallmark, the OpenAPI exposed to factory system and a comprehensive Identity Management layer, for secure horizontal- and vertical quality data integration. The PPD hallmark and the TF already address some of the industrial needs to have a trusted approach to share quality data between the different stakeholders of the production chain to empower zero-waste value chain strategies.
Open access
Blockchain Technology Applications and Security
Digital Transformation in Industry
Physical Unclonable Functions (PUFs) and Hardware Security
Dimitris Mourtzis, John Angelopoulos, Nikos Panopoulos
Blockchain can be realized as a distributed and decentralized database, also known as a “distributed ledger,” that is shared among the nodes of a computer network. Blockchain is a form of democratized and distributed database for storing information electronically in a digital format. Under the framework of Industry 4.0, the digitization and digitalization of manufacturing and production systems and networks have been focused, thus Big Data sets are a necessity for any manufacturing activity. Big Data sets are becoming a useful resource as well as a byproduct of the activities/processes taking place. However, there is an imminent risk of cyberattacks. The contribution of blockchain technology to intelligent manufacturing can be summarized as (i) data validity protection, (ii) inter- and intra-organizational communication organization, and (iii) efficiency improvement of manufacturing processes. Furthermore, the need for increased cybersecurity is magnified as the world is heading towards a super smart and intelligent societal model, also known as “Society 5.0,” and the industrial metaverse will become the new reality in manufacturing. Blockchain is a cutting-edge, secure information technology that promotes business and industrial innovation. However, blockchain technologies are bound by existing limitations regarding scalability, flexibility, and cybersecurity. Therefore, in this literature review, the implications of blockchain technology for addressing the emerging cybersecurity barriers toward safe and intelligent manufacturing in Industry 5.0 as a subset of Society 5.0 are presented.
Benjamin Hellenborn, Oscar Eliasson, İbrahim Yitmen, Habib Sadri
Purpose The purpose of this study is to identify the key data categories and characteristics defined by asset information requirements (AIR) and how this affects the development and maintenance of an asset information model (AIM) for a blockchain-based digital twin (DT). Design/methodology/approach A mixed-method approach involving qualitative and quantitative analysis was used to gather empirical data through semistructured interviews and a digital questionnaire survey with an emphasis on AIR for blockchain-based DTs from a data-driven predictive analytics perspective. Findings Based on the analysis of results three key data categories were identified, core data, static operation and maintenance (OM) data, and dynamic OM data, along with the data characteristics required to perform data-driven predictive analytics through artificial intelligence (AI) in a blockchain-based DT platform. The findings also include how the creation and maintenance of an AIM is affected in this context. Practical implications The key data categories and characteristics specified through AIR to support predictive data-driven analytics through AI in a blockchain-based DT will contribute to the development and maintenance of an AIM. Originality/value The research explores the process of defining, delivering and maintaining the AIM and the potential use of blockchain technology (BCT) as a facilitator for data trust, integrity and security.