This article presents a blockchain reconciliation framework that improves transparency, automation, and trust within the SAP supply chain and finance processes. The implemented system with smart contracts on SAP modules FI, MM, and SD permits real-time verification of supply chain activities and financial transactions, thus minimizing manual matching and third-party verification processes. The framework enables automated three-way matching and updates across modules by storing transaction states in a distributed ledger that captures changes. Based on experiments conducted using SAP simulation data, the accuracy of reconciliations increased by 92%, processing time was cut by 41%, and manual processing steps were reduced by 67%. The results demonstrate the capability of blockchain technology to solve pervasive challenges related data integrity and reconciliation within enterprise ERP systems.
The rise of the industrial metaverse has brought digital twins (DTs) to the forefront. Blockchain-powered non-fungible tokens (NFTs) offer a decentralized approach to creating and owning these cloneable DTs. However, the potential for unauthorized duplication, or counterfeiting, poses a significant threat to the security of NFT-DTs. Existing NFT clone detection methods often rely on static information like metadata and images, which can be easily manipulated. To address these limitations, we propose a novel deep-learning-based solution as a combination of an autoencoder and RNN-based classifier. This solution enables real-time pattern recognition to detect fake NFT-DTs. Additionally, we introduce the concept of dynamic metadata, providing a more reliable way to verify authenticity through AI-integrated smart contracts. By effectively identifying counterfeit DTs, our system contributes to strengthening the security of NFT-based assets in the metaverse.
Aiming to boost production efficiency and reduce human workload, human-centricity has emerged as the core concept of Industry 5.0 (I5.0). However, current works have not established a unified automation and autonomous framework for human-centric smart manufacturing across various real world applications. Addressing this gap, this research introduces an innovative automated framework, ParallelWorkforce, which integrates blockchain intelligence and decentralized autonomous organizations and operations (DAOs) to drive the evolution from digital twins to parallel intelligence. First, this research conducts a comprehensive investigation into smart manufacturing in I5.0, summarizing the ongoing evolution. Next, a detailed exploration of ParallelWorkforce is provided to offer customized strategies for managing different levels of out-of-distribution events, significantly alleviating the workload on biological workers and maximizing the potential of both digital and robotic workers. Finally, the development of ParallelWorkforce across various key applications of smart manufacturing is demonstrated, including autonomous transportation, task assignment, and worker management. This research provides a viable solution for the further development of human-centered smart manufacturing and paves the way for the realization of “6S” goals in I5.0.
Abstract This research explores the contribution of Blockchain Technology and Industry 5.0 in driving sustainability within Bangladeshi Ready-Made Garments (RMG) industry, with a focus on alignment with key Sustainable Development Goals (SDGs). The study employs Interpretive Structural Modeling (ISM) and fuzzy Decision-Making Trial and Evaluation Laboratory (DEMATEL) methods to identify and analyze 14 critical synergies that can drive sustainability. The ISM analysis categorizes the synergies into independent, dependent, and linkage variables, providing insights into their roles and significance within the system. Fuzzy DEMATEL further refines this understanding by evaluating the direct and indirect relationships among the linkage synergies. Key findings reveal the importance of synergies such as reverse logistics and recycling, supply chain collaboration & visibility and ethical practices in driving sustainability. This research contributes by offering a detailed analysis of how the synergy between Blockchain technology and Industry 5.0 can enhance sustainability practices in the RMG industry, providing actionable insights into the technological transformation of supply chain dynamics in support of global sustainability targets.
In all country construction projects include an enormous number of financial transactions and it’s necessary that the contracts between stakeholders should be more advanced in technology. The advance of Blockchain technology has been incontrovertible in recent years and this allowed the contracts to be programmed on Blockchain as smart contracts. The main goal of this paper is to identify and prioritize critical success factors of Smart Contracts in the construction industry. For identifying factors, we used library study and for prioritizing them, field study. To collect data, we designed a DANP questionnaire, from a panel senior managers and engineering experts. The results show that technology maturity is the most important factor in Smart Contract success; security of contracts, support from the engineering community, stakeholders’ consideration, and competition in the building industry were other important factors which took their next levels.
Purpose Made-in-India tyres are rapidly integrating into global supply chains due to a globally coordinated regulatory environment and aspiring for value creation and contribution to circularity. However, it is not clear what are the constituent components of emerging technologies like blockchain that can facilitate value creation and how they are associated. Therefore, this study intends to explore the elements of blockchain technology and how they create value to bring circularity to a tyre supply chain. Design/methodology/approach This study employed a survey-based quantitative methodology to test the theoretical framework of blockchain-enabled circular supply chains using non-parametric regression analysis. A total of 307 responses from India-based supply chain professionals’ data were collected from September 2022 to January 2023 to perform non-parametric regression analysis. Findings The results indicated that blockchain could improve visibility and accessibility by having value-creation capabilities of data collection, monitoring, processing and analysis to facilitate the circular tyre supply chain which focuses on recycling, reusing, reducing and rethinking initiatives. Further, accessibility contributes more than visibility to creating value toward a blockchain-enabled tyre circular supply chain. Originality/value First, this study employs a grounded theory-driven approach in identifying and testing a framework through hierarchical regression. This study identifies the role of blockchain technology in unfolding visibility and accessibility towards value creation, enhancing circularity in the supply chains in complex and critical industries such as tyres in India and across the globe.
Chalima Dimitra Nassar Kyriakidou, Iakovos Pittaras, Athanasia Maria Papathanasiou, George Xylomenos · 5 authors
Despite its rapid growth, the Internet of Things (IoT) still faces significant challenges related to interoperability, transparency and security. To address these issues, we propose the utilization of smart contract-based Digital Twins (DTs) "hosted" in the Hyperledger Fabric blockchain network, while leveraging the Web of Things paradigm for interoperability. Thus, our solution includes several notable features, such as decentralization, auditability and security. However, implementing DTs using Distributed Ledger Technologies (DLTs) introduces certain overheads. In this paper, we assess the feasibility and evaluate the performance of smart contract-based DTs using a set of Key Performance Indicators (KPIs). Our results demonstrate that, although DLT-induced overheads, such as latency, are present, they remain manageable for IoT use cases.
Purpose This study aims to propose a cloud platform architecture considering information sharing based on blockchain to realize the security and convenience of enterprise information sharing in the automotive supply chain. Design/methodology/approach A bilateral matching model considering enterprises information contribution stimulates information sharing and improves the efficiency and quality of supply and demand matching. Three smart contracts are used to complete the information sharing process and match supply and demand in the automotive supply chain. Findings The system is tested on the local Ganache private chain, and the decentralized web page is designed based on the architecture prototype. Originality/value Solve the problem of information island in automobile supply chain.
Larissa Krämer, Patrick Stuckmann-Blumenstein, Pascal Kaiser, Michael Henke · 6 authors
Enhancing transparency in production processes, especially in shared manufacturing, relies heavily on sharing data. Information asymmetries and coordination problems between parties with conflicting interests pose a challenge in this multi-stakeholder interaction. Blockchain technology with smart contracting can be a solution due to its immutable data and decentralised data storage features. Designing and executing blockchain in industrial applications is a highly intricate task that requires extensive testing, expertise, and proficiency. This paper is the first to propose a holistic simulation model for evaluating the impact of smart contracting on shared manufacturing, including a novel approach to simulated smart contracting in time-lapse for Ethereum-based networks. The introduced model guides the design and implementation process of blockchain applications in shared manufacturing to address this challenge. A systematic literature review establishes ten design process requirements and ten smart contract functions. The implementation is developed based on the design benchmarks of three Ethereum-based frameworks to investigate the simulation model's respective feasibility and scalability. The simulation model validation demonstrates our approach's suitability for simulating smart contracting in shared manufacturing within a hybrid production. It enables fast and scalable simulations, offering an innovative approach to extensively testing blockchain applications before their introduction to ongoing industrial operations.
The food industry offers diverse supply chains with multiple locations for manufacturers, dealers, and customers. The techniques of distribution and transaction used in online food trade are currently unclear. This problem, along with participants' unwillingness to offer information and lack of confidence, presents significant issues for the global food supply chain industry. The goal of this project is to build a blockchain-based Food Supply Chain (FSC) architecture that will enable the tracking of food from the farm to the customer transparently and safely. The suggested method encourages openness and wellinformed decision-making by tracking participant interactions, triggering events, and logging transactions using Ethereum smart contracts. Smart contracts also control how vendors and customers communicate, for example, by keeping track of and alerting customers about the condition of Internet of Things (IoT) containers used in food supply chains. To improve transparency and immutability, the suggested framework might be expanded to include other supply chain industries in the future.
Ardavan Babaei, Erfan Babaee Tırkolaee, Sadia Samar Ali
The utilisation of blockchain technology has gained significant traction within contemporary supply chains owing to its ability to enhance transparency, security, and traceability. Manufacturing plants, as pivotal components of the supply chain, stand to benefit from improved tracking and transparency of goods movement, real-time visibility, quality control processes, and adherence to industry standards through blockchain implementation. Nonetheless, without a comprehensive assessment of manufacturing plants’ readiness to embrace blockchain technology, the anticipated benefits may give way to unforeseen challenges. In this study, a novel network framework is offered to evaluate manufacturing plants’ readiness for adopting distributed ledger technology, specifically blockchain, under varying levels of ambiguity, including high (fuzzy) and low (scenario) ambiguity. This framework is distinguished by its ability to address uncertainty in evaluations, incorporating both scenario-based and fuzzy programming approaches. Furthermore, the framework treats evaluation criteria as interconnected entities, fostering a network perspective rather than a black-box approach. The proposed framework is then validated through a case study involving five manufacturing plants and twenty-four evaluation criteria. Our findings underscore the pivotal role of uncertainty considerations in ranking manufacturing plants, with the fifth plant emerging as the frontrunner across both fuzzy and scenario-based assessments in most instances.
The traditional landscape of vehicle lifecycle management systems has several issues, including widespread fraud, opaque processes, and limited accessibility. As a result, there is a need for a paradigm change toward modernized vehicle management techniques, which is connected with the emergence of Intelligent Transport Systems (ITS). This work is a novel solution in the shape of a Blockchain-Assisted Vehicle State Tracking System that is claimed to transform how automobiles are identified, registered, tracked, and controlled inside an Intelligent Transport System. The proposed model offers a secure, auditable ledger for tracking vehicle states. Incorporating federated learning-based predictive maintenance ensures timely servicing while protecting the privacy of user data. This paper explores the intricate architecture and promising capabilities to not only address the shortcomings of existing frameworks but also promote the evolution towards a seamlessly integrated, technologically driven ecosystem for vehicle management and Intelligent Transport Systems.
Mohamed Moetez Abdelhamid, Layth Sliman, Raoudha Ben Djemaa
Purpose: The integration of AI with blockchain technology is investigated in this study to address challenges in IoT-based supply chains, specifically focusing on latency, scalability, and data consistency. Background: Despite the potential of blockchain technology, its application in supply chains is hindered by significant limitations such as latency and scalability, which negatively impact data consistency and system reliability. Traditional solutions such as sharding, pruning, and off-chain storage introduce technical complexities and reduce transparency. Methods: This research proposes an AI-enabled blockchain solution, ABISChain, designed to enhance the performance of supply chains. The system utilizes beliefs, desires, and intentions (BDI) agents to manage and prune blockchain data, thus optimizing the blockchain’s performance. A particle swarm optimization method is employed to determine the most efficient dataset for pruning across the network. Results: The AI-driven ABISChain platform demonstrates improved scalability, data consistency, and security, making it a viable solution for supply chain management. Conclusions: The findings provide valuable insights for supply chain managers and technology developers, offering a robust solution that combines AI and blockchain to overcome existing challenges in IoT-based supply chains.
K. S. Chandrasekaran, V. Mahalakshmi, M. R. Anantha Padmanaban
Over the past ten years, blockchain technology has significantly captured interest in various application fields. Originally devised for the Bitcoin peer-to-peer cryptocurrency network, extensive research now explores integrating blockchain with various other service domains. The technology is celebrated for its decentralized structure, robust security, immutability, and transparency. In blockchain systems, consensus algorithms play a crucial role in establishing unanimous agreement among participants within a distributed computing environment, facilitating the addition of new blocks to the blockchain network. The effectiveness and security of the network largely hinge on the performance of these consensus algorithms. However, existing consensus algorithms face challenges with throughput, latency, and communication complexity. To address these issues, an enhanced consensus algorithm known as Intuitive Random Selection based Byzantine Fault Tolerant (BFTIRS) is introduced. This algorithm optimizes the consensus process by selecting a subset of nodes, thereby reducing network complexity and enhancing efficiency without sacrificing security. To tackle scalability issues in blockchains, a hierarchical BFTIRS algorithm that incorporates sharding is developed. This approach segments network participants into local and global consensus groups, each conducting the consensus process independently. Performance evaluations of this algorithm show improvements in both efficiency and security over existing solutions.
The paper presents a novel framework for implementing decentralized algorithms based on non-fungible tokens (NFTs) for digital twin management in aviation, with a focus on component lifecycle tracking. The proposed approach uses NFTs to create unique, immutable digital representations of physical aviation components capturing real-time records of a component’s entire lifecycle, from manufacture to retirement. This paper outlines detailed workflows for key processes, including part tracking, maintenance records, certification and compliance, supply chain management, flight logs, ownership and leasing, technical documentation, and quality assurance. This paper introduces a class of algorithms designed to manage the complex relationships between physical components, their digital twins, and associated NFTs. A unified model is presented to demonstrate how NFTs are created and updated across various stages of a component’s lifecycle, ensuring data integrity, regulatory compliance, and operational efficiency. This paper also discusses the architecture of the proposed system, exploring the relationships between data sources, digital twins, blockchain, NFTs, and other critical components. It further examines the main challenges of the NFT-based approach and outlines future research directions.
In the European Union (EU), there are two distinct periods regarding the regulation of crypto assets, related services and crypto assets service providers. The distinction is based on the existence or lack of specific regulation of crypto assets. From a different perspective, a distinction can also be made between the regulatory environment before and after the implementation of the Markets in Crypto Assets regulation (MiCA/MiCAR). The former period can be characterized as the EU regulatory wild west of crypto assets, where the crypto sector was regulated, but only partially, by amending existing legislation. The second era of crypto-relevant EU regulation is the development of a specific regulatory framework striving for consistent legal cover of the whole crypto sector. In this paper, without aiming to be exhaustive, the MiCA's specific regulatory framework applying to the crypto asset market is described. The aim of this paper is to provide a summary overview of the state or lack of provisions in the MiCA regarding non-fungible tokens.
Héctor Cañas, Josefa Mula, Francisco Campuzano Bolarín
Industry 4.0 (I4.0) technologies generate new opportunities for developing smart models, algorithms and tools to support supply chain (SC) production planning and control (PPC), or smart PPC (SPPC 4.0). Paired with opportunities, challenges arise in integrating sustainability and resilience in SC network design (SCND) according under I4.0. The main novelty of this paper is to propose two multi-objective models that integrate strategical and tactical PPC decisions into a sustainable-resilient SC under I4.0 towards SPPC 4.0. Sustainability is incorporated in terms of reducing costs and CO2 emissions, and a job creation factor. Resilience is incorporated in terms of contracting support suppliers. To solve the multi-objective models, the augmented epsilon constraint method (AUGMECON) was used. This algorithm minimises a target objective function while it treats the others as constraints. Our experiments indicate that AUGMECON is sensitive to the choice of epsilon values. Furthermore, a synthetic data generation tool called SR1-SR2_SynthDataGenerator was developed. This tool generates input datasets to validate and evaluate our models against benchmarks. A stochastic model (SR2) is also proposed that, with small datasets, takes 8.39 seconds to solve. The proposed models can be useful for industries that seek sustainable and resilient SCs to adapt to changing environments.
Kathirvel Ayyaswamy, Naren Kathirvel, C. P. Maheswaran
The development of numerous cryptocurrencies, dApp monetization, smart personal contracts, decentralized finance apps (Defi), and non-fungible tokens (NFTs) preceded general adoption of the blockchain concept. Blockchain technology (BT) is digital money that increases in value every hour by a factor of bigger than its previous worth. Even though blockchain's widespread appeal has been confined to its role in the development of Bitcoin and other cryptocurrencies, a number of other applications are currently being developed steadily. This demonstrates the promise of decentralized technology and the undeniable influence of blockchain on business across many industries. Because of these built-in characteristics, blockchain is now used in a number of sectors, including real estate, finance, agriculture field, healthcare sector, education institutions, design and manufacturing unit, and retail shopping. The chapter provides a thorough explanation of the various use cases and areas of BT.
3D Printing in Biomedical Research
Additive Manufacturing and 3D Printing Technologies
Current autonomous building research primarily focuses on energy efficiency and automation. While traditional artificial intelligence has advanced autonomous building research, it often relies on predefined rules and struggles to adapt to complex, evolving building operations. Moreover, the centralized organizational structures of facilities management hinder transparency in decision-making, limiting true building autonomy. Research on decentralized governance and adaptive building infrastructure, which could overcome these challenges, remains relatively unexplored. This paper addresses these limitations by introducing a novel Decentralized Autonomous Building Cyber-Physical System framework that integrates Decentralized Autonomous Organizations, Large Language Models, and digital twins to create a smart, self-managed, operational, and financially autonomous building infrastructure. This study develops a full-stack decentralized application to facilitate decentralized governance of building infrastructure. An LLM-based artificial intelligence assistant is developed to provide intuitive human-building interaction for blockchain and building operation management-related tasks and enable autonomous building operation. Six real-world scenarios were tested to evaluate the autonomous building system's workability, including building revenue and expense management, AI-assisted facility control, and autonomous adjustment of building systems. Results indicate that the prototype successfully executes these operations, confirming the framework's suitability for developing building infrastructure with decentralized governance and autonomous operation.