Blockchain Papers

Pan Liu, Yue Long, Haicao Song, Yandong He

No abstract is available for this record.

Caibo Zhou, Wenyan Song, Lingdi Liu, Zixuan Niu

Smart product-service system (SPSS) is a new business model that integrates smart products and e-services to satisfy customer needs better and improve enterprise competitiveness. In case to reasonably and efficiently manage the products, services, information, and data generated throughout the SPSS lifecycle, it is necessary to conquer the problem of data insecurity and the low-trust between stakeholders. Blockchain can provide solutions because of its characteristics such as decentralized, irreversibility of records and smart contracts, etc. To solve the problem, this paper develops a conceptual framework for smart PSS lifecycle management which consists of four layers: perception layer, business resource layer, blockchain layer, and application layer. Furthermore, this paper introduces the typical improved services at each stage and an illustrative case of smart coffee machine service system. Finally, the paper puts forward the future work combined with limitations. This framework will help stakeholders achieve more secure and efficient SPSS lifecycle management and further enhance enterprise competitiveness.

Daqiang Guo, Shiquan Ling, Hao Li, Di Ao · 7 authors

The booming customized and personalized demands call for new production paradigms that complies with that change. The ubiquitous connection, digitization and sharing in the context of Industry 4.0 present an opportunity for next-generation production paradigm-personalized production, to meet the booming personalized demands with individual needs and preferences. Personalized production refers to a customer-centric production paradigm, where individual needs and preferences are transformed into personalized products and services at an affordable cost, by maximizing the benefit of connection and sharing throughout the product life-cycle. This paper reviews and identifies the evolution of production paradigms. A framework for personalized production based on digital twin, blockchain and additive manufacturing in the context of Industry 4.0 is proposed. Besides, the impact of the implementation of personalized production is discussed from the aspects of customer-centric business model, social and environmental effects and challenges of data ownership. This paper provides helpful guidance and reference for personalized production paradigm.

Nataša Živić

Distributed Ledger Technology (DLT) is seen as a developing technology, which will have a tremendous impact to many aspects of our lives, like social, financial, juristic, security etc. Industry 4.0 covers a wide spectrum of technical and technological issues, whereby DLT plays a significant role. In particular, car industry is facing enormous challenges and changes due to a number of factors like climate changes, new regulations, security and safety challenges of Car-to-Car and Car-to-Infrastructure communications, new hardware and software architecture, new functionalities and new business models. As an answer to all these factors, several disruptive technologies that have come into focus during the last few years, as well as some alternative business models, must be considered as a part of Industry 4.0 and here, particularly, as a part of Car Industry 4.0. In this context, DLT is also seen as one of disruptive technologies. Therefore, this paper analyzes DLT as a part of a Car Industry 4.0 and their main properties. Additionally, few use cases of DLT for automotive industry are presented.

Ali Vatankhah Barenji, Hanyang Guo, Yitong Wang, Zhi Li · 5 authors

No abstract is available for this record.

Jiewu Leng, Guolei Ruan, Pingyu Jiang, Kailin Xu · 7 authors

No abstract is available for this record.

Kevin Wallis, Jan Stodt, Eugen Jastremskoj, Christoph Reich

The digital transformation of companies is expected to increase the digital interconnection between different companies to develop optimized, customized, hybrid business models. These cross-company business models require secure, reliable, and traceable logging and monitoring of contractually agreed information sharing between machine tools, operators, and service providers. This paper discusses how the major requirements for building hybrid business models can be tackled by the blockchain for building a chain of trust and smart contracts for digitized contracts. A machine maintenance use case is used to discuss the readiness of smart contracts for the automation of workflows defined in contracts. Furthermore, it is shown that the number of failures is significantly improved by using these contracts and a blockchain.

Javad Ghofrani, Kirill Loisha, Dirk Reichelt

In the next few years, Blockchain will playa central role in IoT as a technology. It enables the traceability of processes between multiple parties independent of a central instance. Blockchain allows to make the processes more transparent, cheaper, and safer. This research paper was conducted as systematic literature search. Our aim is to understand current state of implementation in context of Blockchain Technology for digital protection of communication in industrial cyber-physical systems. We have extracted 28 primary papers from scientific databases and classified into different categories using visualizations. The results show that the focus in around 14% papers is on solution proposal and implementation of use cases Secure transfer of order data using Ethereum Blockchain, 7% papers applying Hyperledger Fabric and Multichain. The majority of research (around 43%) is focusing on solution development for supply chain and process traceability.

Nawari O. Nawari

No abstract is available for this record.

Xuling Ye, Markus König

No abstract is available for this record.

Aijun Liu, Taoning Liu, Jian Mou, Ruiyao Wang

This study assesses supplier selection at the beginning of project management to establish an evaluation system corresponding to blockchain tracing anti-counterfeiting platforms (BTAP). First, this paper determines 20 evaluation criteria from the four dimensions of platform overview, core technology, application support, and operations management. On this basis, multi-criteria decision making (MCDM) based on customer needs is proposed, which consists of three main steps. First, quality function deployment (QFD) and the best and worst method (BWM) are used to evaluate the four dimensions of the BTAP and specific evaluation criteria from the perspective of customers to obtain the criteria weight. Then, this method uses the extended Vlse Kriterjumska Optimizacija I Kompromisno Resenje (VIKOR) approach to sort the alternatives. Finally, the improved decision making trial and evaluation laboratory (DEMATEL) method is used to analyse the relationships between the 20 criteria in the four dimensions. The feasibility and effectiveness of this method are verified by an example. According to the sensitivity analysis and comparative analysis, the results show that this method can evaluate blockchain anti-counterfeiting enterprises. The main conclusions are as follows: the core technology is the most important factor influencing the choice of a BTAP project, and the role of application support in evaluation cannot be ignored.

Özden Tozanlı, Elif Kongar, Surendra M. Gupta

Manufacturing and supply chain operations are on the cusp of an era with the emergence of groundbreaking technologies. Among these, the digital twin technology is characterized as a paradigm shift in managing production and supply networks since it facilitates a high degree of surveillance and a communication platform between humans, machines, and parts. Digital twins can play a critical role in facilitating faster decision making in product trade-ins by nearly eliminating the uncertainty in the conditions of returned end-of-life products. This paper demonstrates the potential effects of digital twins in trade-in policymaking through a simulated product-recovery system through blockchain technology. A discrete event simulation model is developed from the manufacturer’s viewpoint to obtain a data-driven trade-in pricing policy in a fully transparent platform. The model maps and mimics the behavior of the product-recovery activities based on predictive indicators. Following this, Taguchi’s Orthogonal Array design is implemented as a design-of-experiment study to test the system’s behavior under varying experimental conditions. A logistics regression model is applied to the simulated data to acquire optimal trade-in acquisition prices for returned end-of-life products based on the insights gained from the system.

Maximilian Klöckner, Stefan Kurpjuweit, Chander Velu, Stephan M. Wagner

OverviewBlockchain combined with 3D printing offers businesses untapped opportunities. Blockchain can help businesses overcome intellectual property and data security barriers, allowing them to take advantage of emerging 3D printing business models. Specifically, blockchain can facilitate local manufacturing and may lay the groundwork for new business models such as secure design marketplaces and shared factories. Businesses could also improve their value proposition by offering additional services around a printed part, improving value delivery, and offering less costly and more customized products that involve fewer risks. Blockchain could transform the way firms create, deliver, and capture value in 3D printing ecosystems.

Giulia Pattini, Giuseppe Martino Di Giuda, Lavinia Chiara Tagliabue

The proposed research aims at illustrating how Blockchain technology can support the contract execution optimizing and assuring a transparent information flow during the phases of the construction process. The traditional approach, chased in the industry, is indeed more hierarchical than networked, resulting in a high fragmentation of contracts and the break of companies in numerous tiers. This context prevents effective collaboration, hindering the achievement of the project objectives. The recent digital transition, guided by Building Information Modeling (BIM), has promised the creation of a shared environment for the information created and exchanged during the entire process, in favor of collaboration and reduction of critical issues typical related to the sector. Despite the initial promises, the use of BIM has shown problems related to trust and transparency of information, not encouraging participants to collaborate in meeting common goals. For these reasons, the study aims to investigate the potential of Blockchain technology in the management of the information flow to ensure transparency and stability of the process. The research proposes four frameworks showing how Blockchain can be integrated with the construction contract to support the execution of each phase, highlighting the improvement of information sharing, traceability of each activity or service and support for collaboration.

Chao Zhang, Guanghui Zhou, Han Li, Yan Cao

Configuring intelligent manufacturing systems (IMSs) is significant for manufacturing enterprises to take a step toward Industry 4.0. However, most current IMS is configured based on the Industrial Internet of Things (IIoT) with a centralized architecture, which results in poor flexibility to handle manufacturing disturbances and limits capacity to support security solutions. To solve the above issues, this article combines IIoT with the permissioned blockchain and proposes a novel manufacturing blockchain of things (MBCoT) architecture for the configuration of a secure, traceable, and decentralized IMS. Then, hardware infrastructures and software-defined components of MBCoT are designed to provide an insight into the industrial implementation of IMS. Furthermore, the consensus-oriented transaction logic of MBCoT is presented based on a crash fault-tolerant protocol, which empowers MBCoT with a strong but resource-efficient encryption mechanism to support the autonomous manufacturing process. Finally, the implementation of an MBCoT prototype system and its application examples justify that the proposed approach is practical and sound. The evaluation experiment demonstrates that MBCoT equips IMS with a secure, traceable, stable, and decentralized operating environment while achieving competitive throughput and latency performance.

Mahmud Hasan, Binil Starly

No abstract is available for this record.

Joachim Stanke, Martin Unterberg, Daniel Trauth, Thomas Bergs

Abstract Networking and digitization in manufacturing enable novel methods of data-driven analysis and optimization of processes through cross-process data availability. The creation of digital twins plays an important role in this. However, not all data relevant for a digital twin can be measured directly in the process. Therefore, methods are needed that enable the modelling of quantities that are difficult or impossible to measure directly in the process, such as the finite element method. In many companies, however, neither the know-how nor the necessary IT infrastructure for finite element simulations is available. External commissioning processes are also not suitable for achieving the goals of higher productivity and agility pursued with the digitization and networking of manufacturing processes. In this contribution, an architecture is presented that enables the fully automated use of finite element simulation as a service. The architecture is developed using the case study of fine blanking. First, the requirements of the architecture to be created are determined. Important characteristics of the architecture should be scalability as well as interfaces and means of payment suitable for machine communication. In addition, ensuring data integrity is an important requirement when creating the digital twin. Based on the identified requirements, an architecture is then presented that meets these requirements by using cloud computing and distributed ledger technologies and interfaces that can directly process measurement signals from the process and communicate with the architecture. Finally, the capability of the architecture is tested, possible applications and limitations are discussed, and future extensions are considered.

Maria Usova, Sergey Chuprov, Ilya I. Viksnin

Nowadays Smart Factory concept becomes a reality. We meet the greatest challenge of implementing autonomous manufacturing processes such as an organization of robots interaction in the framework of cyber-physical systems. This issue seems to be one of the most important, as it is considered as the basis of fully automated systems and provides mechanisms for self-organization and decentralized control. In this paper, we describe Informational Space and messages interaction models as the way for robots communication, considered under the Smart Factory environment. The main contributions of the work are the developed models and a software simulator of an adaptive production model, that responds to changing customer personalized needs. The performed case study showed that the developed software simulator, based on the presented theoretical models, can successfully imitate the autonomous production process.

Johan Wenngren, Martin Lundgren, Åsa Ericson, Johan Lugnet

The following topics are dealt with: production engineering computing; industrial robots; industrial manipulators; robot programming; computerised numerical control; control engineering computing; intelligent robots; human-robot interaction; factory automation; maximum power point trackers.

Manuel Sánchez

Because of the digital revolution, also known as Industry 3.0, the boundaries between the physical and digital worlds are shrinking to give life to a more interconnected and smart factories. These factories allow employees, machines, processes, and products to interact oriented to provide a better organization of all the productive means, empowering the entire company itself to achieve higher levels of efficiency and productivity. These technologies are profoundly transforming our society, allowing customizing everything in detail, reducing goods and services costs, transforming worker's and job’s conditions for safety and security, among others. In that sense, Industry 3.0 acted as a catalyst that promoted new production mechanisms, which originated a new industrial revolution known as Industry 4.0. The concept of Industry 4.0, is used to designate the new generation of connected, robotics, and intelligent factories. Fundamentally, the vision of Industry 4.0 is to give smart capabilities to the production and physical operations to create a more holistic and better-connected ecosystem. One crucial aspect to consider, regarding the idea of the Industry 4.0 concept, is related to integrability and interoperability of the actors involved in manufacturing processes. It means that people, things, processes, and data have to be able not only to make decisions for themselves and to carry out their work in a more autonomous way (independence) but, also, the self-management of the whole factory (need to promote integrability and interoperability). The previous statement implies that the production processes’ actors should be able to autonomously negotiate in order to reach agreements linked to achieve both individual and collective production goals. In that sense, Industry 4.0 represents not only a new way to produce goods and services but also a crucial integration challenge of the actors involved in the manufacturing processes that need connection, communication, coordination, cooperation, and collaboration (denoted as 5C) capabilities that allow them to comply with the vision of Industry 4.0. Principally, this thesis aims at empowering processes management for Industry 4.0, proposing a stack of five levels, denoted as 5C. The 5C stack levels represent a way to deal with integration and interoperability challenges so that they can be solved incrementally at each level. From this perspective, we must start solving connection and communication issues as a first step to promote more elaborated organization processes like coordination, cooperation, and collaboration. Mainly, the 5C denote the elements needed to allow autonomous integration and interoperability of actors in Industry 4.0. From this point of view, in this thesis project, we present a first contribution that is oriented to deal with the integration challenges regarding the Industry 4.0 context at the level of connection and communication. This solution is based in a Multi-agent system in which the physical elements of the system are characterized virtually as agents. Notably, the use of Multi-agent systems allows creating an intelligent environment dotted with characteristics of autonomy, decentralization, self-organization, self-direction, standardized protocol, and other properties of Multi-agent systems. Moreover, the proposed solution allows actors to extend their limited capabilities with service deployed through the Internet, as an intent to automatize, optimize, and in more mature stages, transform any environment into a fully integrated, automated, and intelligent environment. Consequently, the proposed architecture will be evaluated and compared to previous researches in this field. In the second place, we will solve some integration challenges of Industry 4.0 at the level of coordination, cooperation, and collaboration. In this case, we design a framework for autonomous integration of actors in Industry 4.0, to allow them to autonomously coordinate, cooperate, and collaborate. This framework uses technologies like the Internet of Everything, Everything mining, and Autonomic computing. Next, we design some autonomic cycles of data analytics tasks, oriented to enable autonomous coordination in manufacturing processes. Fundamentally, these data analytics tasks create the knowledge bases needed in a production environment to support self-planning, self-manage, self-supervising, self-healing, etc. to the manufacturing process. Finally, we implement an autonomous cycle of data analytics tasks for self-supervising, using several Everything-mining techniques over data sources corresponding to a real manufacturing process. It defines a self-value-driven supervisory system, according to the classification made by Xu et al. (2017), that can process and verify the functionalities and applicability of our framework in manufacturing processes. Moreover, the self-supervising system developed in this thesis project is compared to other research works.

Shengjing Sun, Xiaochen Zheng, Javier Villalba-Díez, Joaquín Ordieres‐Meré

Information-intensive transformation is vital to realize the Industry 4.0 paradigm, where processes, systems, and people are in a connected environment. Current factories must combine different sources of knowledge with different technological layers. Taking into account data interconnection and information transparency, it is necessary to enhance the existing frameworks. This paper proposes an extension to an existing framework, which enables access to knowledge about the different data sources available, including data from operators. To develop the interoperability principle, a specific proposal to provide a (public and encrypted) data management solution to ensure information transparency is presented, which enables semantic data treatment and provides an appropriate context to allow data fusion. This proposal is designed also considering the Privacy by Design option. As a proof of application case, an implementation was carried out regarding the logistics of the delivery of industrial components in the construction sector, where different stakeholders may benefit from shared knowledge under the proposed architecture.

Prince Waqas Khan, Yung-Cheol Byun, Namje Park

Agriculture and livestock play a vital role in social and economic stability. Food safety and transparency in the food supply chain are a significant concern for many people. Internet of Things (IoT) and blockchain are gaining attention due to their success in versatile applications. They generate a large amount of data that can be optimized and used efficiently by advanced deep learning (ADL) techniques. The importance of such innovations from the viewpoint of supply chain management is significant in different processes such as for broadened visibility, provenance, digitalization, disintermediation, and smart contracts. This article takes the secure IoT-blockchain data of Industry 4.0 in the food sector as a research object. Using ADL techniques, we propose a hybrid model based on recurrent neural networks (RNN). Therefore, we used long short-term memory (LSTM) and gated recurrent units (GRU) as a prediction model and genetic algorithm (GA) optimization jointly to optimize the parameters of the hybrid model. We select the optimal training parameters by GA and finally cascade LSTM with GRU. We evaluated the performance of the proposed system for a different number of users. This paper aims to help supply chain practitioners to take advantage of the state-of-the-art technologies; it will also help the industry to make policies according to the predictions of ADL.

Nuthalapati Sudha, Raju Ramakrishna Gondkar

The paper provides a modified framework for Agile software development with the insertion of Blockchain in its framework. The existing work using Blockchain as a technology in Agile Software development is limited. The Blockchain technology was first used for developing crypto currency. The technology uses decentralized and distributed ledger concept. Agile technology being a key method of software development has been used for software developments that have little understanding of the software requirements and places where the requirements change very frequently. It is often seen that in the industry it becomes difficult to track the changes and ownership of suggestions in the agile team is a major concern. Considering the number of stake holders and the rapidity of changes in the development process, blockchain is analyzed as a method of tracking and following the responsibility needed in development. The fact that not much work exists in this area encourages us to take up this research.

Nursena Bayğın, Mehmet Bayğın, Mehmet Karaköse

Today, thanks to the developing technology, mass production technology is progressing very fast. With these systems, which aim to meet the increasing customer demands correctly, effectively and efficiently, it is aimed to produce customer-specific products. In this method called mass customization, customers can customize the product they demand and create it according to their personal tastes. In this study, the mass customization concept, which is one of the current production technologies, is modeled by using blockchain. In the proposed system, a blockchain-based smart contract was created to bring together the parties and establish a healthy communication. In addition, it is aimed to produce more effective products with the proposed method. By providing a simulation environment for the products to be produced, it is presented to the users' information and a feedback system is created. Thus, a consensus-based production model is being built.