Configuring a trustworthy Internet of Things (IoT)–enabled building information modeling (BIM) platform (IBP) is significant for modular construction to ensure transparency, traceability, and immutability throughout its fragmented supply chain management. However, most current IBPs are designed adopting a centralized system architecture, which fails to achieve a decentralized and effective one to ensure a single point of truth in BIM and prevent a single point of failure in IoT networks. To address this challenge, this study introduces permissioned blockchain with IBP and proposes a novel service-oriented system architecture of blockchain-enabled IoT-BIM platform (BIBP) for the data-information-knowledge (DIK)–driven supply chain management in modular construction. First, infrastructure as a service (IaaS) is designed with hardware, core technologies, and protocols to offer accurate data from daily practice to blockchain BIM. Blockchain BIM as a service (BaaS) is then developed within the permissioned blockchain to ease the interoperability of the information, semantics, and meaningful inferences. Furthermore, software as a service (SaaS) is configured with decentralized applications to achieve knowledgeable operations or processes with a crash fault-tolerant consensus mechanism. The demonstrative case study in a modular student residence project evaluates the proposed BIBP system prototype with the performance analysis of storage cost, throughput, latency, privacy, and feedback from stakeholders. The results indicate that BIBP has an effective system architecture with acceptable throughput and latency, can save storage costs to achieve a single point of truth in BIM, and avoid a single point of failure for IoT networks with privacy and security-preserving mechanisms.
Xinlai Liu, Yishuo Jiang, Zicheng Wang, Ray Y. Zhong · 6 authors
The manufacturing industry is experiencing a service-oriented transformation in the digitalisation era. However, many small and middle enterprises (SMEs) still rely on traditional manufacturing patterns in which they can hardly servitise manufacturing resources due to the limited budget and poor digitalisation capability. To servitise manufacturing resources, this paper proposes unified five-layer blockchain-enabled secure digital twin platform architecture, followed by its core enabling components and technologies. Firstly, a service-oriented digital twinning model is developed to transform physical resources into digital services. Secondly, a rule-based off-chain matching mechanism is designed to bridge customers’ orders with manufacturing services. Thirdly, service-oriented architecture (SOA) is adopted as the major methodology to design and develop the whole blockchain platform. Four blockchain frontend services are developed using React.js, whilst the blockchain backend is developed using private Ethereum blockchain and InterPlanetary File System (IPFS). Finally, an experimental case is conducted based on the 3D printing scenario to verify the effectiveness and efficiency of the proposed platform, named imseStudio. The results show that it not only provides an effective solution to digitalise manufacturing resources but also promotes the transformation towards service manufacturing.Highlights Blockchain-enabled secure digital twin platform is developed to servitise manufacturing resourcesService-oriented digital twinning model is developed to transform physical resources into digital servicesRule-based off-chain matching mechanism is built to bridge customers’ orders with 3D printerFour blockchain explorers are developed to facilitate 3D printing services
Digital Transformation in Industry
Blockchain Technology Applications and Security
Additive Manufacturing and 3D Printing Technologies
Purpose Smart manufacturing is the prime gripper for the transformation and upgrading of the manufacturing industry. Smart manufacturing systems (SMSs) largely determine how smart manufacturing evolves in technical and organizational dimensions and how it realizes values in products, production or services. SMSs are growing rapidly and receiving tons of attention from academic research and industrial practice. However, the development of SMSs is still in its fancy, and many issues wait to be identified and solved, such as single point failures, low transparency and ineffective resource sharing. Blockchain, an emerging technology deriving from Bitcoin, is competent to aid SMSs to conquer troubles due to its decentralization, traceability, trackability, disintermediation, auditability and etc. The purpose of this paper is to investigate the blockchain applications in SMSs, seek out the challenges faced by blockchain-enabled SMSs (BSMSs) and provide referable research directions and ideas. Design/methodology/approach A comprehensive literature review as a survey is conducted in this paper. The survey starts by introducing blockchain concepts, followed by the descriptions of a literature review method and the blockchain applications throughout the product life cycle in SMSs. Then, the key issues and challenges confronting BSMSs are discussed and some possible research directions are also proposed. It finally presents qualitative and quantitative descriptions of BSMSs, along with some conclusions and implications. Findings The findings of this paper present a deep understanding about the current status and challenges of blockchain adoption in SMSs. Furthermore, this paper provides a brand new thinking for future research. Originality/value This paper minutely analyzes the impacts that blockchain exerts on SMSs in view of the product life cycle, and proposes using the complexity science thinking to deal with BSMSs qualitatively and quantitatively, including tackling the current major problems BSMSs face. This research can serve as a foundation for future theoretical studies and enterprise practice.
In this paper we present a framework for automatically coding blockchain based supply chain management systems starting from a Domain Specific Graphical Language (DSGL) interface modeling the typical interactions of the actors of a value chain. For each asset defined in the DSGL, a solidity smart contract is created and for each interaction a specific method is defined. The DSGL allows the specification of the roles of the actors involved in the value chain, and of a set of constraints in order to permit the execution of operations on the assets only to users with specific roles. Besides the smart contracts implementing the supply chain management system, two web based user interfaces are produced by our framework for the management of the supply chain designed through the DSGL: one for the supply chain administrator and the other for the supply chain participant.
Purpose The purpose of this methodology is to categorise the challenges into cause and effect group. The modern scenario of customization, personalization and multi-restrictive working because of pandemics has affected the operations of manufacturing small and medium enterprises (SMEs). In the new normal, the digitalization of manufacturing SMEs can be the path breaker. Modern digitalization includes a mix of technologies such as the industrial internet of things (IIoT), the internet of things, cyber-physical system and big data analytics. This digitalization can help in achieving new design changes, efficient production scheduling, smart manufacturing and unrestricted on-time delivery of quality products. This research paper aims to recognize and analyze the challenges faced while implementing IIoT technologies in manufacturing SMEs and tries to find the possibility of mitigating challenges by blockchain technology. Design/methodology/approach There were ten challenges of IIoT implementation identified from the literature review and experts’ opinions. To collect information from Indian manufacturing SMEs, a survey tool was formed in the form of a questionnaire. On the fundament of responses received from industrial experts, the Decision-Making Trial and Evaluation Laboratory (DEMATEL) technique has been used for categorizing these challenges into cause and effect groups. Further, the authors tried to mitigate observed challenges with the help of blockchain technology. Findings With the implementation of IIoT technologies, the manufacturing processes become conciliatory, effective and traceable in real time. Observation of the current study states that the top effect group challenges such as the security of data and reliability of technologies can be mitigated by enabling blockchain technologies. The authors conclude that blockchain-enabled IIoT technologies will be highly beneficial for the Indian SMEs strategically and practically in the current scenario. Research limitations/implications Methodology of DEMATEL focuses on responses received from experts. The broader approach of survey from manufacturing organizations is compromised due to small sample size in this methodology. Experts approached for survey were from manufacturing SMEs of Delhi National Capital Region only. Broader survey-based techniques may be applied covering different sectors of SMEs in future work. Practical implications Technologies such as blockchain can facilitate advanced security in the application of IIoT and other such practices. While dealing with significant issues and challenges of new technologies, blockchain gives an edge of balance in the current scenario. Its properties of fixity, temper evident and circumvent fraud make this technology ideal for the digitalization of the manufacturing systems in SMEs. Originality/value Digitalization of manufacturing facilities is the need of the hour. Pandemic challenges have highlighted the urgency of it. This research will motivate and guide the manufacturing SMEs in planning strategies and long-term policies in implementing modern technologies and coping up with the pandemic challenges.
This paper introduces the background, concept and definition of the Industry Commons. It initiates a discussion on the positioning of the Industry Commons Ecosystem (ICE) with respect to current research directions in advanced manufacturing and production systems that shape advances in engineering and technology, novel business models and innovation breakthroughs. The potential value of data sharing across industrial domains is estimated at over $100 billion, particularly in view of optimising manufacturing processes. Data sharing across domains however faces a series of well-documented challenges associated with the lack of semantic interoperability and related standards, management of trust and sustainability. Solving bottlenecks in data sharing requires a systemic approach to data management, which can account for all aspects of data use, levels of application, attribution and dynamic exchanges. In this paper we propose a high-level ecosystem approach that integrates societal values with digital affordances of industry’s cognitive-assisted processes, remote interfacing, hybrid applications and large-scale value networks. Early development of an Ontology Commons EcoSystem (OCES) is presented as the key enabling framework for Industry Commons interoperability and a series of enabling frameworks form the basis of future research directions in Trusted Data Sharing and Closed-Loop Lifecycle Management for greater sustainability.Abbreviations: AI – Artificial Intelligence; AIOTI – Alliance of Internet-of-Things Innovation; ALM – Asset Lifecycle Management; ALO – Application-Level Ontology; AP – Application Protocol; API – Application Programming Interface; B2B – Business-to-Business; B2C – Business-to-Customer; CDE – Cross-Domain Ecosystem; CDEI – Cross-Domain Ecosystem Interoperability; CL2M – Closed-Loop Lifecycle Management; CNO – Collaborative Networked Organisations; CPS – Cyber-Physical Systems; CSR – Corporate Social Responsibility; DLO – Domain-Level Ontology; DLT – Distributed Ledger Technology; EM – Enterprise Modelling; FAIR – Findable, Accessible, Interoperable and Reusable; GUI – Graphical User Interface; ICE, Industry Commons Ecosystem; IOF – Industrial Ontology Foundry; IP – Intellectual Property; IPR – Intellectual Property Rights; ISN – Intertwined Supply Network; MIR – Music Information Retrieval; MLO – Middle-Level Ontology; MO – Meta-Ontology; OCES – Ontology Commons EcoSystem; PI – Physical Internet; PLM – Product Lifecycle Management; ROI – Return-on-Investment; SC – Supply Chain; SCM – Supply Chain Management; SOS – System-of-Systems; TDS – Trusted Data Sharing; TLO – Top-Level Ontology; TRO – Top Reference Ontology; TUI – Tangible User Interface.
Manimuthu Arunmozhi, V. G. Venkatesh, Yangyan Shi, V. Raja Sreedharan · 5 authors
With smart sensors and embedded drivers, today’s automotive industry has taken a giant leap in emerging technologies like Machine learning, Artificial intelligence, and the Internet of things and started to build data-driven decision-making strategies to compete in global smart manufacturing. This paper proposes a novel design framework that uses Federated learning-Artificial intelligence (FAI) for decision-making and Smart Contract (SC) policies for process execution and control in a completely automated smart automobile manufacturing industry. The proposed design introduces a novel element called Trust Threshold Limit (TTL) that helps moderate the excess usage of embedded equipment, tools, energy, and cost functions, limiting wastages in the manufacturing processes. This research highlights the use cases of AI in decentralised Blockchain with smart contracts, the company’s trading policies, and its advantages for effectively handling market risk assessments during socio-economic crisis. The developed model supported by real-time cases incorporated cost functions, delivery time and energy evaluations. Results spotlight the use of FAI in decision accuracy for the developed smart contract-based Automobile Assembly Model (AAM), thereby qualitatively limiting the threshold level of cost, energy and other control functions in procurement assembly and manufacturing. Customisation and graphical user interface with cloud integration are some challenges of this model.
Background: The use of blockchain technology for tracking and tracing (T&T) in supply chains is the subject of lively debate in scientific literature. However, distributed ledger technology (DLT) does not have to have the characteristic blockchain structure and often performs better without such a structure. Generalized DLT for T&T in supply chains has rarely been discussed in the existing literature. Methods: This article presents an exploratory case study research of eight companies to identify the main goals, and problems that the companies have when they engage in T&T. This practical perspective is complemented by a theoretical systems thinking perspective. Based on these two foundations, we discuss the usefulness of blockchain technology and, more generally, DLT for T&T in supply chains. Results: Based on our analysis, DLT is only necessary in special cases, e.g., when the owners of the data have an interest in deleting the data, but the data stakeholders do not. In the other cases examined, DLT competes with other technologies, such as conventional, centralized databases in combination with digital signatures. Furthermore, it became evident that DLT can only be useful for supply chain tracing. The technological features of DLT do not provide any benefit for supply chain tracking, i.e., the timely communication of the status of a physical good. Conclusions: Distributed ledgers often have a disadvantage in that they are very complex and, therefore, expensive. DLT should preferably only be used when it is technologically necessary or the simplest/cheapest choice, which is probably not all that often. Finally, the usefulness of distributed ledger technology and its integrated smart contract technology is highly dependent on how easy it is to link the real physical world to a digital record/contract in an error-free and tamper-proof way. Currently, such a definite link exists only in very few cases and is often impossible.
Blockchain can be used to store data safely while ensuring data transparency in quality control of advanced manufacturing. A smart contract running on blockchain can prevent data from being tampered with, along with specifying data transmission rules efficiently and securely. This paper proposes a smart contract system for manufacturing quality control that encompasses machine learning to solve dynamic multi-objective combinatorial optimization problem in production. The proposed system was experimented in various production scenarios. Experimental results showed that the system can effectively restore data through smart contracts when the data were artificially tampered with. In addition, the machine learning algorithm can improve the efficiency of the productions and achieve the combined optimization of multiple objectives.
Purpose In the era of digitalisation, blockchain has the potential to fundamentally change the architecture, engineering and construction (AEC) industry's workflow, trust and procurement environments. However, few studies have investigated blockchain adoption barriers in the AEC industry in detail. Therefore, the study aims to provide a comprehensive understanding of these barriers and their interdependent relationships in the context of the AEC industry. Design/methodology/approach Based on a review of the literature, industry reports and expert feedback, 11 barriers towards adopting the blockchain were identified. Then, the authors investigated the interdependencies amongst the factors by adopting a two-stage integrated interpretive structural modelling (ISM) and decision-making trial and evaluation laboratory (DEMATEL) method. Findings The findings show that the lack of information technology infrastructure (BC4) and legal and regulatory uncertainty (BC11) are the most prominent barriers towards blockchain adoption in the AEC industry. Practical implications The research contributes in providing a clearer understanding of related barriers and potential solutions for practitioners in this area. Subsequently, the identification of adoption barriers can enable an important knowledge foundation and suggest possible solutions for adopting blockchain techniques successfully and effectively in the AEC industry. Originality/value The study lays an essential research foundation for the effective adoption and use of blockchain in the AEC industry.
Mohammed Ali Berawi, Teuku Yuri M. Zagloel, Muhammad Naufal Ariq, Mustika Sari
Players in the building and construction industry have progressively adopted building Information Modelling (BIM) to improve the efficiency of building information management through its rich digital building models used at all building life cycle stages. However, there are still several constraints in the BIM collaboration process and data management regarding data security, accountability, and transparency. On the other hand, blockchain, a distributed ledger technology, is considered a solution to address those constraints. Therefore, this paper aims to integrate blockchain technology into the BIM workflow, focusing on the smart building planning process that holds most data generation of the activities in the whole construction project. To obtain the objectives of this study, literature review, benchmarking study, and expert interviews were conducted in two stages, firstly to identify the characteristics and components of a smart building and then to develop further the blockchain-based framework for smart building planning in the BIM model. By developing the framework that utilizes Ethereum blockchain and InterPlanetary File System (IPFS) peer-to-peer storage in Revit BIM client, the results of this study showed that the integration of blockchain in BIM workflow provides an improved platform in terms of data security, accountability, transparency, in which digital signature can be created, and authorization for the models is provided for the planning process of a smart building.
Cross-border e-commerce, involving international product transactions via online and mobile platforms, is growing at a dramatic rate around the globe. One of the main concerns of brand firms is preventing counterfeit products from being sold under their names on e-commerce platforms. Counterfeit goods not only create economic losses to both the supply and demand sides, but also undermine efforts to improve sustainability. Proliferating counterfeits harm the brands of supply firms and trust in selling e-commerce platforms. In addition, they discourage participants in the supply chain from investing in social and environmental sustainability. If end-customers have access to detailed and comprehensive product information with a traceability system that can help overcome information uncertainty and asymmetry, losses can be prevented. The result of the pilot test has shown that securely shared in-depth product information among supply chain stakeholders from the supply side to end-customers can help prevent counterfeit goods from proliferating further by enabling consumers to determine the authenticity of products and report forgeries before paying.
Lik‐Hang Lee, Tristan Braud, Pengyuan Zhou, Lin Wang · 9 authors
Since the popularisation of the Internet in the 1990s, the cyberspace has kept evolving. We have created various computer-mediated virtual environments, including social networks, video conferencing, virtual 3D worlds (e.g., VR Chat), augmented reality applications (e.g., Pokémon Go), and Non-Fungible Token Games (e.g., Upland). Such virtual environments, albeit non-perpetual and unconnected, have brought us various degrees of digital transformation. The term “metaverse” has been coined to facilitate further digital transformation in every aspect of our physical lives. At the core of the metaverse stands the vision of an immersive Internet as a gigantic, unified, persistent, and shared realm. While the metaverse may seem futuristic, catalyzed by emerging technologies such as Extended Reality, 5G, and Artificial Intelligence, the digital “big bang” of our cyberspace is not far away. This survey presents the first effort to offer a comprehensive framework that examines the latest metaverse development under the dimensions of state-of-the-art technologies and metaverse ecosystems and illustrates the possibility of the digital “big bang”. It is essential to highlight that the metaverse encompasses diverse technologies and ecosystems, calling it an interdisciplinary and emerging field. Its primary objective is to provide users with satisfactory and interactive experiences. First, technologies are the enablers that drive the transition from the current Internet to the metaverse. We thus examine eight enabling technologies rigorously – Extended Reality, User Interactivity (Human-Computer Interaction), Artificial Intelligence, Blockchain, Computer Vision, IoT and Robotics, Edge and Cloud computing, and Future Mobile Networks. In terms of applications, the metaverse ecosystem allows human users to live and play within a self-sustaining, persistent, and shared realm. Therefore, we discuss six user-centric factors – Avatar, Content Creation, Virtual Economy, Social Acceptability, Security and Privacy, and Trust and Accountability. Finally, we propose a concrete research agenda for developing the metaverse.
The Enterprise Global Risk Management (EGRM) framework views risk management as composed of four elements: hierarchical level of management, risk management policy, planned actions and orientation of the risk management process. It was proposed as the next step in the evolution of Enterprise Risk Management (ERM) and Enterprise Integrated Risk Management (EIRM) by including the risks of Industry 4.0. Blockchains are an essential and very fast-growing technology. The purpose of this paper is to demonstrate how the EGRM framework, through the idea of including Industry 4.0 risks, could be used for decision making of risk management in organizations/enterprises that deploying blockchains. To achieve it, the quasi-multicriteria algorithm SIGMA is used for evaluation of optimal elements of the EGRM framework by different criteria for risk tolerance. It is proposed a reverse interpretation of the worst-case solutions as recommendation for preliminary guideline for risk management recourse allocation between these elements of EGRM. The presented results support the assumption that EGRM framework is applicable as an additional interpretive tool for risk management decision-making in blockchain deployment. The framework could be considered as promising tool for ex-ante guidelines for allocating resources (financial or other) of enterprises/organizations among the elements of the EGRM.