Jiekang Haw, Tanni Alam Dola, Swee Leong Sing, Edgar Yong Sheng Tan · 5 authors
Abstract This article first describes a typical additive manufacturing (AM) process chain, which involves the transaction of digital information to manufacture physical products. The digitized nature of AM exposes the technology to increased vulnerabilities, posing a hurdle to its mass adoption. The article presents motivation for using blockchain, which is a decentralized, immutable ledger that is shared on a peer-to-peer network. The article presents the advantages of blockchain integration to AM supply chains. These involve aspects of data security, supply chain and logistics, finance, value creation, and scope expansion. The article also presents the opportunities and challenges of blockchain technology.
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.
In Industry 5.0 vision, machines are empowered with the interaction capability to autonomously make local decisions and coordinate with each other as well as humans. However, how to form a group consensus on the rapid self-organizing of the manufacturing process is critical for achieving manufacturing resilience under disturbances and disruptions. Based on our formerly developed system ManuChain (Leng et al., 2020), this article proposes a blockchained smart contract system (BSCS), named ManuChain II, as the digital twin of a decentralized autonomous manufacturing system for achieving resilience in Industry 5.0. A blockchain-secured multiagent system architecture together with a product data model is established to form the BSCS. The BSCS could prevent tampering with data and enhance the transparency of the product manufacturing process. In BSCS, two types of blockchained smart contracts (SCs) are established with a bi-level interplay computing architecture. The lower-level contracts perform the predefined and learned patterns of task coordination for achieving resilience under internal disruptions. The upper-level contracts are incorporated with communication-efficient decentralized deep-learning algorithms for the learning, updating, transferring, and sharing of coordination patterns used in the autonomous decision in lower-level SCs, thereby achieving the continuous improvement of the system’s decentralized autonomous intelligence. Via incorporating the decentralized deep learning algorithms into blockchained SCs, this study reveals a new way to realize the self-organizing intelligence of the manufacturing system for enhancing resilience toward Industry 5.0.
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.
Industrial Control Systems (ICS) have specific data requirements in terms of Quality of Service (QoS). Lost or delayed critical data, such as control signals, can damage widespread production, such as machine performance. The problem is compounded in the next-generation Industry 4.0, where the operations will be even less human-dependent, involving multiple organizations. Moreover, the communication aspects across multistakeholders require a disaggregated approach contrary to the current closed ICS architecture.This paper presents a framework for decentralization of ICS called Operations and Control Networks (OCN) in which ‘contracts’ are the basic units of abstraction to exchange information with trust and precision between different actors. In the lower layers, High-Precision Communication (HPC) contracts execute control functions with requested service level guarantees in the network. A high-level trusted delegation of tasks is executed as smart contracts using Distributed Ledger Technology (DLT) to enable multi-stakeholder auditability and accountability.
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.
Ge Wang, Rui Qin, Juanjuan Li, Fei–Yue Wang · 6 authors
This article proposes a novel parallel management mode based on decentralized autonomous organizations (DAOs) for enterprises by utilizing the artificial systems, computational experiments, parallel execution (ACP) approach, parallel intelligence theory, and blockchain technologies, to realize the distributed management of an enterprise. The artificial enterprise DAO (EnDAO) corresponding to the actual enterprise is constructed, and they constitute a parallel system via virtual–real interaction and parallel execution. Through the non-fungible token (NFT)-based incentive mechanism, metaverse-based virtual learning and training, as well as DAO-based distributed management and decision-making, the management and control of the actual enterprise as well as its employees can be carried out. By virtue of the virtual–real interactions of three types of employees, as well as the virtual–real feedback of three closed loops in the parallel systems, DAO-based parallel management for enterprises can realize descriptive intelligence, predictive intelligence, and prescriptive intelligence. On this basis, this article takes the recruitment-oriented key performance indicator (KPI) management of a startup technology enterprise as the case to introduce the operation processes and illustrate the superiorities of the proposed DAO-based enterprise parallel management mode.
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.
The study focuses on the utilization of Blockchain and Cloud based technologies in the automotive supply chain in India. It is based on a questionnaire-based survey conducted through a Google Form based questionnaire over 75 company executives of automobile sector having any idea on Blockchain. Among the participants, 73% was Male& 27% was Female. 32% Executives with Job experience 2-5 years, 27% with 5-10 years and 41% with More than 10 years. In terms of working profile, 41% Production Manager, 17% Tech Manager and 32% Supply Manager were there.The study uses a 5-point Likert scale questionnaire to assess the three broad parameters: Blockchain Technology Adoption (BTA), Supply Chain Integration (SC1) with Internal Integration, Customer Integration and Supplier Integration as sub-items and Sustainable Supply Chain Performance (SSCP). It has found that the company executives perceive that the blockchain is well integratedin the supply chain from both supplier and customer's perspective and also perceive that the blockchain is well integrated in the supply chain from both supplier and customer's perspective. organizationsalso has the capability of achieving sustainability in embracing Blockchain Technology. Not only in the mainstream production process, but also in the supply chain encompassing the suppliers and transporters, the usage of blockchain technology is widespread acknowledged. The Customer services also embrace Cloud-based Blockchain services to a greater extent. It has been observed that the adoption of blockchain and cloud technologies improve supply chain sustainability and coordination among different units in supply chain. However, the blockchain-based customer services such as vehicle monitoring, theft prevention, insurance scrutiny need to be focused more as the automotive sector in India is inclined to the Blockchain Technology towards the backward linkages up the supply chain rather than the forward linkages downward. The cloud integration in the blockchain network do enhances the performance and utilities in the automobile sector. Still, it needs to be more sophisticated and gain industry-wide acceptance.
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