Journal of Industrial Information Integration最新文献

{"title":"Multi-criteria group decision-making with spherical fuzzy rough numbers for biomedical materials in hip prosthesis","authors":"Muhammad Akram ,&nbsp;Maheen Sultan ,&nbsp;Cengiz Kahraman","doi":"10.1016/j.jii.2024.100766","DOIUrl":"10.1016/j.jii.2024.100766","url":null,"abstract":"<div><div>Biomedical materials play a crucial role in modern medicine, helping restore and enhance function after injury or illness. These materials, whether natural or synthetic, are used in clinical applications to support, reinforce, or replace damaged tissues or biological functions. This study focuses on the effectiveness and advancements of biomedical materials in hip replacement surgery, offering various solutions for the recovery of different hip injuries. To compute biocompatibility and biodegradability of biomedical materials in hip prosthesis, this research paper develops a multi-criteria group decision making technique to encompass all aspects of an issue under consideration within a decision-making team’s governance. The suggested multi-criteria decision making outranking technique combined with spherical fuzzy rough approach excels in a unique way by encapsulating the capabilities to handle pseudo criteria and compare the considered options by referring to the indifference, strong and weak preference relation. Moreover, the proposed outranking technique effectively employs spherical fuzzy rough numbers to minimize subjective bias while addressing varying degrees of uncertainty. The practical implication of the proposed technique is addressed by considering the case study of material selection in hip prosthesis. Finally, the validity of the proposed technique is confirmed by comparing it with existing methods, and the selection of the same best alternative across all techniques reinforces its credibility.</div></div>","PeriodicalId":55975,"journal":{"name":"Journal of Industrial Information Integration","volume":"44 ","pages":"Article 100766"},"PeriodicalIF":10.4,"publicationDate":"2025-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142968076","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An industrial dataspace for automotive supply chain: Secure data sharing based on data association relationship","authors":"Yuqiao Liao,&nbsp;Xianguang Kong,&nbsp;Lei Yin,&nbsp;Yunpeng Gao,&nbsp;Xinghua Dong","doi":"10.1016/j.jii.2025.100778","DOIUrl":"10.1016/j.jii.2025.100778","url":null,"abstract":"<div><div>The automotive supply chain (ASC) is a complex system involving every aspect of automobile manufacturing, from which the data obtained features such as massive volume, diverse types, and complex relationships. Traditional data management methods no longer meet the demands of handling heterogeneous data from multiple sources or ensuring secure cross-domain data sharing in the ASC, which leads to the isolation of information. Therefore, this paper proposes a data management method based on Industrial Dataspace (IDS), constructs a dataspace architecture for the automotive supply chain (DS-ASC). On this basis, proposes a method for data relationship mining and trusted data sharing that considers implicit associations among ASC members. The improved BiLSTM model promotes the understanding of data, and the improved DPoS algorithm reduces the risk of data leakage. Our method is validated in the practical application of a supply chain master enterprise, and the experiments show that the method proposed in this paper is able to effectively improve the accuracy of mining data association relationship. Meanwhile, it is able to prevent single-point attacks, and ensure the security of data sharing.</div></div>","PeriodicalId":55975,"journal":{"name":"Journal of Industrial Information Integration","volume":"44 ","pages":"Article 100778"},"PeriodicalIF":10.4,"publicationDate":"2025-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142968092","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Method towards collaborative cloud and edge computing via RBC for joint communication and computation resource allocation","authors":"Ruiling Gao ,&nbsp;Wenzhong Zhang ,&nbsp;Wenyi Mao ,&nbsp;Jinjing Tan ,&nbsp;Jin Zhang ,&nbsp;Haiyun Huang ,&nbsp;Wen'an Tan ,&nbsp;Feiyue Huang","doi":"10.1016/j.jii.2025.100776","DOIUrl":"10.1016/j.jii.2025.100776","url":null,"abstract":"<div><div>With the extensive adoption of cloud and edge computing in intelligent manufacturing systems driven by the Industrial Internet of Things (IIoT) and Artificial Intelligence, enhancing the efficiency of cloud-edge collaboration under constrained communication and computational resources has emerged as a prominent research focus. We develop the GRALB model, which is based on Role-Based Collaboration (RBC) in cooperative services, to comprehensively manage the offloading strategy of terminal user tasks between edge nodes and the cloud to solve the joint communication and computing resource allocation problem in intelligent manufacturing systems. First, we jointly model the end-to-end latency and energy consumption based on the physical scenario of cloud-edge collaboration. Then, we extend the GRA model based on E-CARGO and propose the GRALB model with load balancing, which formally models the original joint communication and computing resource allocation problem as an equivalent cooperative service model and provides a proof of algorithm convergence. Finally, we design an x-ILP solution to support the verification and integrated application of the proposed model. Simulation results further confirm our theoretical analysis and show that the proposed collaborative cloud and edge computing solution significantly improves the overall system performance.</div></div>","PeriodicalId":55975,"journal":{"name":"Journal of Industrial Information Integration","volume":"44 ","pages":"Article 100776"},"PeriodicalIF":10.4,"publicationDate":"2025-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142968094","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Context-aware cognitive augmented reality assembly: Past, present, and future","authors":"Wei Fang ,&nbsp;Lixi Chen ,&nbsp;Lei Han ,&nbsp;Ji Ding","doi":"10.1016/j.jii.2025.100780","DOIUrl":"10.1016/j.jii.2025.100780","url":null,"abstract":"<div><div>Since the inception of Augmented Reality (AR) nearly three decades ago, numerous studies have demonstrated its potential to provide intuitive instructions for manual tasks within the manufacturing sector. This includes operations such as manual assembly, which can be executed with high efficiency and a focus on error-avoidance. Despite this, to the best of our knowledge, there has been no comprehensive review of the cognitive AR assembly method from a holistic perspective. This includes aspects such as context awareness, visual instructions, environment interaction, human factor considerations, and the impact on real-world AR assembly deployment. These factors are particularly relevant to current human-centric manufacturing practices in Industry 5.0. Since 2012, the release of Google Glass and advancements in artificial intelligence (AI) have significantly expanded actual AR deployments. Consequently, this review takes 2012 as the starting point for the literature collection. The objective of this article is to provide an overview of the context-aware cognitive AR (CA-CAR) assembly works published between 2012 and 2023. We aim to identify and classify the necessary context modules for CA-CAR assembly, and analyze potential technical barriers to their shop floor adaptation. It should be noted that this work offers both a historical perspective and a comprehensive map of the current research landscape surrounding the development of CA-CAR assembly applications. Furthermore, we discuss recent research trends and open problems in the field of CA-CAR assembly, along with potential future research directions.</div></div>","PeriodicalId":55975,"journal":{"name":"Journal of Industrial Information Integration","volume":"44 ","pages":"Article 100780"},"PeriodicalIF":10.4,"publicationDate":"2025-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142968093","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integrated blockchain and Digital Twin framework for sustainable building energy management","authors":"Fouad Khalifa ,&nbsp;Mohamed Marzouk","doi":"10.1016/j.jii.2024.100747","DOIUrl":"10.1016/j.jii.2024.100747","url":null,"abstract":"<div><div>The building sector remains a major contributor to increasing energy consumption and emissions. Meanwhile, the energy system is becoming more complex due to the transition to clean energy sources. Current tools and policies struggle to manage this complexity, as the existing infrastructure was not designed for such large dynamic distributed energy resources. This creates an urgent need to adopt emerging technologies for enhancing building energy management systems. The objective of this research is to develop a framework that integrates Blockchain and Digital Twin technologies to provide an efficient and trusted energy management platform that supports smart cities communities and to effectively contribute to enhancing the progress of UN Sustainability Development Goals (SDGs), specifically SDG11 and SDG13. The proposed framework comprises four main elements: Blockchain platform, Digital Twin platform, Application Program Interfaces (APIs), and Building Energy Model. Blockchain platform automates energy billing by utilizing digital currency and smart contracts with pre-set pricing tiers and feed in tariffs. Digital Twin platform provides interactive communication and visualization with physical assets. APIs enables seamless interconnectivity between both platforms. The Building Energy Model acts as a prediction tool, and the simulation results are fed to Digital Twin platform to alert system participants in case actual consumption deviates from optimum values. The viability of the proposed framework is demonstrated using a case study of a residential apartment.</div></div>","PeriodicalId":55975,"journal":{"name":"Journal of Industrial Information Integration","volume":"43 ","pages":"Article 100747"},"PeriodicalIF":10.4,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142825349","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A blockchain-enabled horizontal federated learning system for fuzzy invasion detection in maintaining space security","authors":"Y.P. Tsang ,&nbsp;C.H. Wu ,&nbsp;W.H. Ip ,&nbsp;K.L. Yung","doi":"10.1016/j.jii.2024.100745","DOIUrl":"10.1016/j.jii.2024.100745","url":null,"abstract":"<div><div>Recent advances in Industry 4.0 technologies drive robotic objects' decentralisation and autonomous intelligence, raising emerging space security concerns, specifically invasion detection. Existing physical detection methods, such as vision-based and radar-based techniques, are ineffective in detecting small-scale objects moving at low speeds. Therefore, it is worth investigating and leveraging the power of artificial intelligence to discover invasion patterns through space data analytics. Additionally, fuzzy modelling is needed for invasion detection to enhance the capability of handling data uncertainty and adaptability to evolving invasion patterns. This study proposes a Blockchain-Enabled Federated Fuzzy Invasion Detection System (BFFIDS) to address these challenges and establish real-time invasion detection capabilities for edge devices in the low earth orbit. The entire model training process is performed over the blockchain and horizontal federated learning scheme, securely reaching consensus in model updates. The system's effectiveness is examined through case analyses on a publicly available dataset. The results indicate that the proposed system can effectively maintain the desired invasion detection performance, with an average Area Under Curve (AUC) value of 0.99 across experimental runs. Utilising the blockchain-based federated learning process, the total size of transmitted data is reduced by 89.5 %, supporting the development of lightweight invasion detection applications. A closed-loop mechanism for continuously updating the space invasion detection model is established to achieve high space security.</div></div>","PeriodicalId":55975,"journal":{"name":"Journal of Industrial Information Integration","volume":"43 ","pages":"Article 100745"},"PeriodicalIF":10.4,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142873926","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Implementation and evaluation of a smart machine monitoring system under industry 4.0 concept","authors":"Jagmeet Singh ,&nbsp;Amandeep Singh ,&nbsp;Harwinder Singh ,&nbsp;Philippe Doyon-Poulin","doi":"10.1016/j.jii.2024.100746","DOIUrl":"10.1016/j.jii.2024.100746","url":null,"abstract":"<div><div>Production planning and control (PPC) is essential in industrial manufacturing, ensuring efficient resource allocation and process management. Industry 4.0 introduces advanced technologies like cyber physical systems (CPS), artificial intelligence (AI), and internet of things (IoT) to effectively manage and monitor manufacturing operations. However, integrating these technologies into existing machinery, particularly for small and medium-sized enterprises (SMEs), poses challenges due to complexity and cost. The present study addresses this gap by designing and implementing a Smart Machine Monitoring System (SMMS) compatible with existing machinery such as computer numerical control and special purpose machines. The SMMS integrates IoT-based systems with AI algorithms to enhance machine tool utilization through effective planning, scheduling, and real-time monitoring. Through a nine-month case study in the shackle bolt manufacturing section, it was tested and compared to an Enterprise Resource Planning (ERP)-based system to assess its performance. Results showed significant improvements in production output, machine utilization rates, labor efficiency, and overall manufacturing costs. In conclusion, this study contributes to the body of knowledge on practical Industry 4.0 implementations for SMEs, offering insights into cost-effective solutions for enhancing operational efficiency and resource utilization in manufacturing environments.</div></div>","PeriodicalId":55975,"journal":{"name":"Journal of Industrial Information Integration","volume":"43 ","pages":"Article 100746"},"PeriodicalIF":10.4,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142790052","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integrated end-to-end multilingual method for low-resource agglutinative languages using Cyrillic scripts","authors":"Akbayan Bekarystankyzy ,&nbsp;Abdul Razaque ,&nbsp;Orken Mamyrbayev","doi":"10.1016/j.jii.2024.100750","DOIUrl":"10.1016/j.jii.2024.100750","url":null,"abstract":"<div><div>Millions of individuals across the world use automatic speech recognition (ASR) systems every day to dictate messages, operate gadgets, begin searches, and enable data entry in tiny devices. The engagement in these circumstances is determined by the accuracy of the voice transcriptions and the system's response. A second barrier to natural engagement for multilingual users is the monolingual nature of many ASR systems, which limit users to a single predefined language. A substantial amount of transcribed audio data must be used to train an ASR model to obtain one that is trustworthy and accurate. The absence of this data type affects a large number of languages, particularly agglutinative languages. Much research has been conducted using various strategies to improve models for low-resource languages. This study presents an integrated end-to-end multi-language ASR (EMASR) architecture that allows users to choose from a variety of spoken language combinations. The proposed EMASR presents an integrated design to support low-resource agglutinative languages by fusing the features of the multi-identifier module, voice fusion module, and recurrent neural network module. The proposed EMSAR identifies Turkic agglutinative languages (Kazakh, Bashkir, Kyrgyz, Saha, and Tatar) to enable multilingual training through the use of Connectionist Temporal Classification (CTC) and an attention mechanism that includes a language model (LM). The cognate word, sentence construction principles, and an alphabet are all present in these languages (Cyrillic). We use recent advancements in language identification to obtain recognition accuracy and latency characteristics. Experiment results reveal that multilingual training produces superior results than monolingual training in all languages tested. The Kazakh language obtained a spectacular result: word error rate (WER) was reduced to half and character error rate (CER) was reduced to one-third, demonstrating that this strategy may be beneficial for critically low-resource languages.</div></div>","PeriodicalId":55975,"journal":{"name":"Journal of Industrial Information Integration","volume":"43 ","pages":"Article 100750"},"PeriodicalIF":10.4,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142825334","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Maize precision seeding scheme based on multi-sensor information fusion","authors":"Chunji Xie ,&nbsp;Li Yang ,&nbsp;Xiantao He ,&nbsp;Tao Cui ,&nbsp;Dongxing Zhang ,&nbsp;Hongsheng Li ,&nbsp;Tianpu Xiao ,&nbsp;Haoyu Wang","doi":"10.1016/j.jii.2024.100758","DOIUrl":"10.1016/j.jii.2024.100758","url":null,"abstract":"<div><div>Seeding plays a crucial role in agricultural production. The traditional mechanized seeding suffers from inefficiencies, low precision, and lack of control, which makes it inadequate for the high demands of the modern precision agriculture, such as the high speed, high precision, and real-time control. Therefore, this study proposes a precision seeding scheme based on multi-sensor information fusion. The system uses a Controller Area Network bus to collect and analyze data from multiple sensors for accurately controlling the seeding and fertilization mechanisms and real-time monitoring the operational conditions. In addition, the structural design, functional development, and field testing of the proposed seeding scheme are analyzed. A dual-speed measurement method, which employs an encoder and a Global Navigation Satellite System receiver, is then used to develop the motor drive model. The test results show that the maximum average error in motor speed does not exceed 1.5 %. The system can accurately alarm for seeding and fertilization faults reaching a 100 % success rate, with no missed or false alarms. The incorporated novel features include a field headland switch and a one-click pre-seeding function. During the lifting and lowering of the seeder, the motor stop and start success rate also reach 100 %, with a system response time &lt;0.7 s. The pre-seeding time can be arbitrarily set, which allows to avoid the issue of no seeds falling at the start of the seeder. Moreover, the wind pressure measurement of the system has an average relative error of 0.83 %. The long-term operation tests show no faults, and all the functions remain normal. Furthermore, the field test results show an average qualified seeding rate of 94.81 % and an average seed spacing variation coefficient of 14.1 %, which demonstrates the high accuracy and stability of the system.</div></div>","PeriodicalId":55975,"journal":{"name":"Journal of Industrial Information Integration","volume":"43 ","pages":"Article 100758"},"PeriodicalIF":10.4,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142825348","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A comprehensive analysis of multi-strategic RIME algorithm for UAV path planning in varied terrains","authors":"Tao Gu ,&nbsp;Yajuan Zhang ,&nbsp;Limin Wang ,&nbsp;Yufei Zhang ,&nbsp;Muhammet Deveci ,&nbsp;Xin Wen","doi":"10.1016/j.jii.2024.100742","DOIUrl":"10.1016/j.jii.2024.100742","url":null,"abstract":"<div><div>Optimizing industrial information integration is fundamental to harnessing the potential of Industry 4.0, driving data-informed decisions that enhance operational efficiency, reduce costs, and improve competitiveness in modern industrial environments. Effective unmanned aerial vehicle (UAV) path planning is crucial within this optimization framework, supporting timely and reliable data collection and transmission for smarter decision-making. This study proposes an enhanced RIME (IRIME) algorithm for three-dimensional UAV path planning in complex urban environments, formulated as a multiconstraint optimization problem aimed at discovering optimal flight paths in intricate configuration spaces. IRIME integrates three strategic innovations into the RIME algorithm: a frost crystal diffusion mechanism for improved initial population diversity, a high-altitude condensation strategy to enhance global exploration, and a lattice weaving strategy to avoid premature convergence. Evaluated on the CEC2017 test set and six realistic urban scenarios, IRIME achieves an 86.21 % win rate across 100 functions. In scenarios 4–6, IRIME uniquely identifies the globally optimal paths, outperforming other algorithms that are limited to locally optimal solutions. We believe these findings demonstrate IRIME's capacity to address complex path-planning challenges, laying a robust foundation for its future application to broader industrial optimization tasks.</div></div>","PeriodicalId":55975,"journal":{"name":"Journal of Industrial Information Integration","volume":"43 ","pages":"Article 100742"},"PeriodicalIF":10.4,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142873928","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}