Journal of Industrial Information Integration最新文献

{"title":"Practical implementation based on histogram of oriented gradient descriptor combined with deep learning: Towards intelligent monitoring of a photovoltaic power plant with robust faults predictions","authors":"Nadji Hadroug ,&nbsp;Amel Sabrine Amari ,&nbsp;Walaa Alayed ,&nbsp;Abdelhamid Iratni ,&nbsp;Ahmed Hafaifa ,&nbsp;Ilhami Colak","doi":"10.1016/j.jii.2024.100760","DOIUrl":"10.1016/j.jii.2024.100760","url":null,"abstract":"<div><div>The increasing complexity of photovoltaic (PV) system monitoring underscores the importance of precise fault detection and energy loss prediction. This paper proposes a deep learning-based framework that integrates multiple advanced techniques to accurately detect, localize, and predict faults in PV panels. A pre-trained Convolutional Neural Network (CNN), based on the AlexNet architecture, processes thermal imaging data for precise fault extraction. This facilitates the classification of faults, contributing to improved decision-making in PV system management.</div><div>To further enhance real-time monitoring, the framework integrates the Histogram of Oriented Gradients (HoG) descriptor with Support Vector Machine (SVM) models, enabling efficient detection and localization of hotspots across the panels. Additionally, the system leverages Long Short-Term Memory (LSTM) networks combined with fuzzy logic to predict panel performance degradation and quantify energy losses caused by detected faults. The learning process relies on the Long-Term Recurrent Convolutional Network (LRCN) to accurately forecast defects by analyzing power efficiency loss rates.</div><div>Experimental results confirm the effectiveness and reliability of the proposed framework. Achieving an accuracy of 95.45%, with a true positive rate of 91.67% and a true negative rate of 100%, the system demonstrates robust fault detection capabilities. These results highlight the framework’s potential to mitigate power losses, ensuring optimal operation of PV systems. This intelligent solution offers a significant advancement in PV system maintenance and monitoring, providing a scalable approach for real-world applications.</div></div>","PeriodicalId":55975,"journal":{"name":"Journal of Industrial Information Integration","volume":"44 ","pages":"Article 100760"},"PeriodicalIF":10.4,"publicationDate":"2024-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142929488","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":"Blockchain-enabled federated learning-based privacy preservation framework for secure IoT in precision agriculture","authors":"Ishu Sharma ,&nbsp;Vikas Khullar","doi":"10.1016/j.jii.2024.100765","DOIUrl":"10.1016/j.jii.2024.100765","url":null,"abstract":"<div><div>The aim of this paper is to establish a secure and privacy preserved IoT communication in precision agriculture. For achieving security and privacy, federated learning system have been deployed on blockchain ecosystem to classify IoT communication attacks in precision agriculture. This paper has utilized recent ‘CICIoT2023’ database to automate identification of prominent cyber-attacks in IoT. Sharing data between devices raised privacy concerns but without sharing data knowledge also getting limited for classification of diverse attacks. So, we have deployed federated learning ecosystem over Ethereum block chain to achieve collaborative learning with privacy preserving communication. In methodology, initially recent dataset about cyber-attacks classification have been collected, pre-processed and distributed for multiple devices. The integration of the Ethereum blockchain with IPFS decentralized file storage for transmitting the learning model from client device to server and vice versa enhances the overall security and trust of the system. Initially basic machine learning algorithms have been employed in standard single machine environment to establish benchmark results. Then a deep neural network has been deployed in blockchain based federated learning environment to analyse the outcome using identical and non-identical data distributions. In results significant outcomes have been achieved in terms of privacy and security with high accuracy, precision, recall, etc., while training deep neural network. This paper has worked for number of subset data classifications to propose and analyze overall view for securing IoT communication from cyber-attacks in precision agriculture.</div></div>","PeriodicalId":55975,"journal":{"name":"Journal of Industrial Information Integration","volume":"44 ","pages":"Article 100765"},"PeriodicalIF":10.4,"publicationDate":"2024-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142929489","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":"Bottom-up green manufacturing strategy in the wire and cable industry: A Z-DEMATEL approach for identifying critical success criteria","authors":"Huai-Wei Lo ,&nbsp;Sheng-Wei Lin","doi":"10.1016/j.jii.2024.100761","DOIUrl":"10.1016/j.jii.2024.100761","url":null,"abstract":"<div><div>Global warming and environmental degradation are prompting enterprises to consider environmentally conscious manufacturing as a strategic imperative. Consequently, the Wire and Cable Industry (W&amp;CI) must urgently transition to Green Manufacturing (GM) to address these environmental challenges and achieve sustainable development. Numerous studies have focused on GM in large-scale enterprises, particularly within the context of Green Supply Chain Management (GSCM). However, most perspectives are top-down, with few studies examining GM strategies from a bottom-up approach, especially regarding the supply chain's crucial role in addressing manufacturers’ pressing needs. This study employs a modified Z-DEMATEL (Z number-based Decision Making and Trial Evaluation Laboratory) technique to evaluate and determine strategic dimensions and criteria. The Z-number enhances conventional fuzzy numbers, increasing the reliability of expert evaluations and reflecting the confidence of the evaluation environment under uncertainty. The findings indicate that “managerial support,” “corporate image,” “legal compliance,” “green design”, and “liability risk” are the top five important criteria for GM. On other hand, the modified Z-DEMATEL technique demonstrates that an Influential Network Relation Map (INRM) provides decision-makers with a quick understanding of the causality between criteria, offering insights into GM strategy. By evaluating different manufacturing practices in the wire and cable industry using a hybrid MCDM model, companies can identify improvement opportunities and make informed decisions about the most sustainable practices from a holistic perspective.</div></div>","PeriodicalId":55975,"journal":{"name":"Journal of Industrial Information Integration","volume":"44 ","pages":"Article 100761"},"PeriodicalIF":10.4,"publicationDate":"2024-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142929490","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":"Digital twin-enabled multi-robot system for collaborative assembly of unorganized parts","authors":"Kyaw Htet Oo,&nbsp;Pisut Koomsap,&nbsp;Duangthida Hussadintorn Na Ayutthaya","doi":"10.1016/j.jii.2024.100764","DOIUrl":"10.1016/j.jii.2024.100764","url":null,"abstract":"<div><div>Agility and flexibility in production are essential to meet the challenge of the demand surge for diverse personalized products that come in small volumes. Automatic assembly is one critical process at stake due to the inherent complexity of the number of parts, their shapes, and the randomness of their initial orientations and positions upon arrival at the station. This research introduces a digital twin framework with an information integration layer designed to enhance the flexibility and efficiency of multi-robot operating systems by collaborating with operator skills, addressing the demand for personalized production. The digital twin model allows operators to remotely implant their skills to oversee the assembly process and to control and train the multi-robot operations through an immersive virtual reality interface upon the arrival of new orders without disrupting the current operations of the physical system. The virtual world allows simulations of the algorithms for collision-free movement and task optimization among multiple robots. Besides, image processing techniques are employed to identify parts arriving in random orientations at the station, providing flexibility during the physical assembly phase. According to the investigation, integrating virtual reality and real-time control challenges data processing and requires robust networking and computational resources. This study contributes to multi-robot operations by providing a scalable and adaptable solution by collaborating with operator skills that enhance both the planning and execution phases of complex assembly processes to new product specifications and changes in design. The methodology presented is foreseen to apply to other manufacturing processes.</div></div>","PeriodicalId":55975,"journal":{"name":"Journal of Industrial Information Integration","volume":"44 ","pages":"Article 100764"},"PeriodicalIF":10.4,"publicationDate":"2024-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142889007","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":"Two non-linear programming models for the multi-stage multi-cycle smart production system with autonomation and remanufacturing in same and different cycles to reduce wastes","authors":"Biswajit Sarkar ,&nbsp;Andreas Se Ho Kugele ,&nbsp;Mitali Sarkar","doi":"10.1016/j.jii.2024.100749","DOIUrl":"10.1016/j.jii.2024.100749","url":null,"abstract":"<div><div>Multi-stage production systems produce a severe amount of defective items as a result of an irregular quota of defectiveness. It is very important to remanufacture those imperfect pieces that are wasted and try to keep the model as reality close as possible. Two different models are developed in this study: a smart production system with numerous stages and with only one cycle and a smart production system with numerous stages and numerous cycles. The essential objective of this study is to scale down the overall waste and lower the final total cost in both models at the same time by optimizing the planned batch size, investments in each stage, and the production rate based on the demand. The remanufacturing of the defective products occurs in two ways. While the remanufacturing process in the smart multi-stage production system with a single cycle occurs within the cycle, the reworking in the case of a smart multi-stage production system with numerous cycles occurs in different cycles. Numerical examples are conducted and compared to illustrate the model quantitatively. It is found that in both scenarios of both models, the total cost is minimized.</div></div>","PeriodicalId":55975,"journal":{"name":"Journal of Industrial Information Integration","volume":"44 ","pages":"Article 100749"},"PeriodicalIF":10.4,"publicationDate":"2024-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143159068","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":"Resilience enhancers and barriers analysis for Industry 4.0 in supply chains using grey influence analysis (GINA)","authors":"Madhuri Chouhan ,&nbsp;R Rajesh ,&nbsp;Rajendra Sahu","doi":"10.1016/j.jii.2024.100735","DOIUrl":"10.1016/j.jii.2024.100735","url":null,"abstract":"<div><div>This study investigates the impact of Industry 4.0 (I4.0) enabling technologies in enhancing the resilience of supply chain systems and the barriers to adopting Industry 4.0 in the supply chains. We use the novel grey influence analysis (GINA) to examine the influence relations among supply chain resilience enhancers and barriers. The study has identified seven enhancers and nine barriers to adopting I4.0 that can improve supply chain resilience. While analyzing the enhancers, the research findings indicate that <em>visibility</em> and <em>coordination</em> in the supply chain are the major enhancers. For barriers, based on the overall influence score, <em>financial constraints, lack of skills and expertise,</em> and <em>inaccessibility of new technology</em> have ranked <em>first, second</em>, and <em>third</em>, respectively. The identified barriers to adopting I4.0 indicate that reducing financial constraints could facilitate the implementation of Industry 4.0 technologies. This study is among the initial investigations to analyze the supply chain resilience enhancers and barriers together for adoption of Industry 4.0. The findings of this study can assist decision-makers and practitioners in overcoming the identified barriers, thereby focusing on the important enhancers of resilience for facilitating the effective adoption of Industry 4.0 in supply chains.</div></div>","PeriodicalId":55975,"journal":{"name":"Journal of Industrial Information Integration","volume":"43 ","pages":"Article 100735"},"PeriodicalIF":10.4,"publicationDate":"2024-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142757767","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":"Interoperability levels and challenges of digital twins in cyber–physical systems","authors":"Sarthak Acharya,&nbsp;Arif Ali Khan,&nbsp;Tero Päivärinta","doi":"10.1016/j.jii.2024.100714","DOIUrl":"10.1016/j.jii.2024.100714","url":null,"abstract":"<div><h3>Context:</h3><div>Industry 4.0/5.0 has brought together technologies like Internet of Things (IoTs), Industrial IoT (IIoT), Cyber–Physical Systems (CPS), Edge Computing, big data analytics, communication technologies (4G/5G/6G) and Digital Twins (DTs), aiming for more intelligent, interconnected systems. However, their real-time efficiency hinges on how well these components integrate and interact. This paper examines the interoperability levels and challenges of integrating Digital Twins within edge-enabled Cyber–Physical Systems.</div></div><div><h3>Objective:</h3><div>Our research explores the existing methods and frameworks for integrating multiple digital twins into a CPS setup. This study focuses on two key research objectives. The first is delineating interoperability levels within DT deployments in CPS setups. The second examines various interoperability challenges in integrating DTs in the context of CPS.</div></div><div><h3>Method:</h3><div>A literature survey is conducted on the existing scholarly literature, industrial use cases, and reports.</div></div><div><h3>Results:</h3><div>We identified 77 interoperability challenges and proposed an interoperability framework for DTs, involving six levels i.e. <em>technical, syntactic, semantic, pragmatic, dynamic</em> and <em>organizational</em>. We further categorized all the 77 challenges into 33 subthemes and mapped them across the 6 levels.</div></div><div><h3>Conclusions:</h3><div>The findings synthesize these challenges into a framework, offering a structured lens through which practitioners can view the adoption and effective use of interconnected DTs in CPS. This contribution is paving the way for future research and development endeavors, aiming to explore fully integrated, efficient, and intelligent CPS within the realm of Industry 4.0/5.0.</div></div>","PeriodicalId":55975,"journal":{"name":"Journal of Industrial Information Integration","volume":"42 ","pages":"Article 100714"},"PeriodicalIF":10.4,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142573308","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}

{"title":"Advance deep learning for soil type classification in space informatics","authors":"Brij B. Gupta ,&nbsp;Akshat Gaurav ,&nbsp;Varsha Arya ,&nbsp;Razaz Waheeb Attar","doi":"10.1016/j.jii.2024.100712","DOIUrl":"10.1016/j.jii.2024.100712","url":null,"abstract":"<div><div>Accurate soil type categorization is very important for resource management in space exploration. Using a complete system including a space station, rovers, and a deep learning framework, this study proposes an advanced deep learning model for soil type categorization in space informatics. Gathering and preprocessing multispectral and hyperspectral soil data, the rovers send it to the space station for in-depth study. Our model had a test accuracy of about 80%. For space informatics, the suggested method guarantees strong and accurate soil categorization, therefore enabling efficient decision-making.</div></div>","PeriodicalId":55975,"journal":{"name":"Journal of Industrial Information Integration","volume":"42 ","pages":"Article 100712"},"PeriodicalIF":10.4,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142573310","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":"In-space cybernetical intelligence perspective on informatics, manufacturing and integrated control for the space exploration industry","authors":"Kelvin K.L. Wong,&nbsp;Kavimbi Chipusu,&nbsp;Muhammad Awais Ashraf,&nbsp;Andrew W.H. Ip,&nbsp;Chris W.J. Zhang","doi":"10.1016/j.jii.2024.100724","DOIUrl":"10.1016/j.jii.2024.100724","url":null,"abstract":"<div><div>The integration of cybernetic principles into space technology has led to a significant shift in spacecraft guidance systems and space station operations. This scholarly work provides a comprehensive analysis of the profound impact that cybernetics has had on space technology, particularly focusing on the development and implementation of closed-loop control systems. Building on foundational contributions to cybernetics, this paper offers a detailed analysis of the complex interplay between control mechanisms, behavioral dynamics, and information management in space informatics. The essential role of cybernetic control systems is highlighted through their critical function in enabling precise spacecraft maneuvers, as demonstrated by the guidance systems used in Apollo lunar missions during the crucial descent and landing phases. In modern space station programs, cybernetic intelligence operates much like a neural network, processing data in real-time and coordinating the various elements of the station's infrastructure. This cybernetic system excels in a wide range of tasks, from space docking maneuvers to waste management, thereby safeguarding astronaut welfare and ensuring mission success. Information serves as the cornerstone of problem analysis and processing, providing a holistic understanding of information flow within complex systems. The study concludes by highlighting the application of a cybernetically intelligent neural network in developing adaptive learning systems for nonlinear and intricate industrial processes. Ultimately, this paper underscores the transformative role of cybernetics in shaping the future of space exploration, emphasizing the seamless integration of control, information, and behavior in space technology to advance our understanding of celestial systems while enhancing the efficiency and safety of space missions.</div></div>","PeriodicalId":55975,"journal":{"name":"Journal of Industrial Information Integration","volume":"42 ","pages":"Article 100724"},"PeriodicalIF":10.4,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142573313","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":"Interval-valued q-rung orthopair fuzzy complex proportional assessment-based approach and its application for evaluating the factors of blockchain technology in various domains","authors":"Rashmi Pathak ,&nbsp;Badal Soni ,&nbsp;Naresh Babu Muppalaneni ,&nbsp;Muhammet Deveci","doi":"10.1016/j.jii.2024.100718","DOIUrl":"10.1016/j.jii.2024.100718","url":null,"abstract":"<div><div>Blockchain technology (BT) is a digitally decentralized, distributed and public ledger, which considers a secure and viable solution for storing and accessing the record transactions in a public or private peer-to-peer network and assures a smart world of automation of complex services. This paper aims to evaluate the factors persuading the BT adoption and also to assess the possible application areas for the adoption of BT. Implementation of the BT process considers multiple criteria and alternatives with uncertain information; therefore, it can be considered as an uncertain multi-criteria decision-making problem. In this context, a hybrid approach is proposed based on the criteria interaction through inter-criteria correlation (CRITIC) and the complex proportional assessment (COPRAS) methods with interval-valued q-rung orthopair fuzzy set (IVq-ROFS) named as the “IVq-ROF-CRITIC<img>COPRAS” framework. In this approach, the significance values of the factors are computed through novel score function-based CRITIC model, whereas the CRITIC-based COPRAS model is employed to rank different domains/application areas for the adoption of BT under IVq-ROFSs environment. In this regard, a novel score function is introduced with its desirable characteristics. Further, the developed model is executed on a case study of BT adoption considering 14 factors, which confirms the efficiency and applicability of introduced approach. Based on the results, the healthcare BT alternative is most appropriate among the others. To evaluate its permanence, sensitivity analysis with regard to various ratings of decision strategic coefficient is presented under IVq-ROFS context. The strength of the developed approach is emphasized by comparing it with some of the former models under the context of IVq-ROFSs. The proposed extension of the COPRAS approach can be utilized to solve other complex group decision-making problems with uncertainties.</div></div>","PeriodicalId":55975,"journal":{"name":"Journal of Industrial Information Integration","volume":"42 ","pages":"Article 100718"},"PeriodicalIF":10.4,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142653178","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}