Journal of Industrial Information Integration最新文献

Advances and innovations in road surface inspection with light detection and ranging technology

IF 10.4 1区计算机科学

Journal of Industrial Information Integration Pub Date : 2025-03-26 DOI: 10.1016/j.jii.2025.100842

Huayang Yu , Yisong Ouyang , Chuanyi Ma , Lizhuang Cui , Feng Guo

{"title":"Advances and innovations in road surface inspection with light detection and ranging technology","authors":"Huayang Yu , Yisong Ouyang , Chuanyi Ma , Lizhuang Cui , Feng Guo","doi":"10.1016/j.jii.2025.100842","DOIUrl":"10.1016/j.jii.2025.100842","url":null,"abstract":"<div><div>Light Detection and Ranging (LiDAR), an advanced non-contact sensing method capable of capturing 3D spatial data with up to millimeter-level precision depending on the ranging method, has been widely used in pavement defect detection and road asset management. This paper provides an overview of LiDAR-based pavement inspection techniques in terms of measurement principles, characterization of acquisition methods, and algorithmic processing of point cloud data. Subsequently, the characteristics of major LiDAR systems, including mobile laser scanning (MLS), terrestrial laser scanning (TLS), and airborne laser scanning (ALS), and their applicability for pavement information inspection are analyzed. MLS emerges as the predominant method due to its superior mobility and measurement precision in retrieving pavement data. Then, traditional and deep learning-based 3D point cloud processing algorithms are compared for pavement information inspection, challenges in achieving high accuracy and efficiency with large datasets are discussed, and future research directions are outlined in this study. Additionally, the paper highlights the practical outcomes achieved with economic LiDAR solutions, whose data densities are one to two orders of magnitude lower than those obtained with powerful and expensive solutions. Furthermore, the potential for integration with other technologies to enhance detection efficiency and precision is discussed.</div></div>","PeriodicalId":55975,"journal":{"name":"Journal of Industrial Information Integration","volume":"45 ","pages":"Article 100842"},"PeriodicalIF":10.4,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143760535","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}

引用次数: 0

Energy-saving distributed flexible job-shop scheduling with fuzzy processing time in IIoT: A novel evolutionary multitasking algorithm

IF 10.4 1区计算机科学

Journal of Industrial Information Integration Pub Date : 2025-03-26 DOI: 10.1016/j.jii.2025.100829

Lu Li, Zhengyi Chai

{"title":"Energy-saving distributed flexible job-shop scheduling with fuzzy processing time in IIoT: A novel evolutionary multitasking algorithm","authors":"Lu Li, Zhengyi Chai","doi":"10.1016/j.jii.2025.100829","DOIUrl":"10.1016/j.jii.2025.100829","url":null,"abstract":"<div><div>With the rapid development of Industrial Internet of Things (IIoT), the complexity of production environment has increased significantly. The flexible job-shop scheduling problem (FJSP) is often framed as a multi-objective optimization issue. However, as the scale and computational demands continue to grow, traditional multi-objective algorithms struggle to identify optimal scheduling policies. To address this challenge, we designed a novel evolutionary multitasking (EMT) framework to handle the complexity of FJSP in IIoT scenarios, considering uncertainty in time constraints through fuzzy processing time. Existing studies do not consider FJSP in IIoT scenario, our study fulfills this research gap. The energy-saving distributed FJSP with fuzzy processing time in IIoT (EFDFJSP) was studied, aiming to simultaneously optimize makespan and energy consumption. The problem was modeled as a multi-task multi-objective EFDFJSP (MMEFDFJSP) for the first time. And we proposed a novel reinforcement learning (RL)-based multi-task multi-objective algorithm with feedback mechanism (EMTRL-FD). Additionally, we proposed a local search (LS) operator selection strategy to efficiently allocate computing resources. Experimental results demonstrate that EMTRL-FD outperforms existing state-of-the-art algorithms in solving EFDFJSP.</div></div>","PeriodicalId":55975,"journal":{"name":"Journal of Industrial Information Integration","volume":"45 ","pages":"Article 100829"},"PeriodicalIF":10.4,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143747783","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}

引用次数: 0

A comparative fuzzy strategic assessment framework for space mission selection at NASA

IF 10.4 1区计算机科学

Journal of Industrial Information Integration Pub Date : 2025-03-25 DOI: 10.1016/j.jii.2025.100840

Madjid Tavana , Andreas Dellnitz , Morteza Yazdani

{"title":"A comparative fuzzy strategic assessment framework for space mission selection at NASA","authors":"Madjid Tavana , Andreas Dellnitz , Morteza Yazdani","doi":"10.1016/j.jii.2025.100840","DOIUrl":"10.1016/j.jii.2025.100840","url":null,"abstract":"<div><div>Strategic decision-making in space mission selection is inherently complex, requiring a balance of multiple, often conflicting, quantitative and qualitative factors under uncertainty. This paper introduces a novel fuzzy analytical framework that extends the Strategic Assessment Model (SAM) by incorporating trapezoidal fuzzy numbers to evaluate mission alternatives systematically. By addressing the uncertainty inherent in space exploration planning, this model provides a structured approach to assessing internal, transactional, and contextual factors—marking the first application of such techniques in NASA's mission selection process. The framework's application to Mars, lunar, and solar system exploration missions demonstrates its ability to provide robust and data-driven insights. The findings reveal that solar system exploration consistently emerges as the most resilient option, achieving a superior Mission Selection Score across diverse scenarios. Comprehensive sensitivity analysis further underscores the framework's reliability, showing that solar system exploration remains the optimal choice in approximately 90 % of cases despite variations in uncertainty levels. This research significantly advances the field of strategic space mission assessment by offering a rigorous, adaptable decision-support tool for decision-makers. It enhances NASA's capability to navigate the complexities of mission planning, ensuring optimal allocation of resources in an era of increasing privatization and international collaboration in space exploration. The proposed fuzzy SAM approach establishes a new benchmark for multi-criteria decision-making under uncertainty, paving the way for future applications in space policy, mission prioritization, and beyond.</div></div>","PeriodicalId":55975,"journal":{"name":"Journal of Industrial Information Integration","volume":"45 ","pages":"Article 100840"},"PeriodicalIF":10.4,"publicationDate":"2025-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143738726","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}

引用次数: 0

Enhancing semantic search using ontologies: A hybrid information retrieval approach for industrial text

IF 10.4 1区计算机科学

Journal of Industrial Information Integration Pub Date : 2025-03-22 DOI: 10.1016/j.jii.2025.100835

Syed Meesam Raza Naqvi , Mohammad Ghufran , Christophe Varnier , Jean-Marc Nicod , Noureddine Zerhouni

{"title":"Enhancing semantic search using ontologies: A hybrid information retrieval approach for industrial text","authors":"Syed Meesam Raza Naqvi , Mohammad Ghufran , Christophe Varnier , Jean-Marc Nicod , Noureddine Zerhouni","doi":"10.1016/j.jii.2025.100835","DOIUrl":"10.1016/j.jii.2025.100835","url":null,"abstract":"<div><div>Despite the increased focus on data in Industry 4.0, textual data has received little attention in the production and engineering management literature. Data sources such as maintenance records and machine documentation usually are not used to help maintenance decision-making. Available studies mainly focus on categorizing maintenance records or extracting meta-data, such as time of failure, maintenance cost, etc. One of the main reasons behind this underutilization is the complexity and unstructured nature of the industrial text. In this study, we propose a novel hybrid information retrieval approach for industrial text using multi-modal learning. Maintenance operators can use the proposed system to query maintenance records and find similar solutions to a given problem. The proposed system utilizes heterogeneous (multi-modal) data, a combination of maintenance records, and machine ontology to enhance semantic search results. We used the state-of-the-art Large Language Models (LLMs); BERT (Bidirectional Encoder Representations from Transformers) for textual similarity. For similarity among ontology labels, we used a modified version of Wu-Palmer’s similarity. A hybrid weighted similarity is proposed, incorporating text and ontology similarities to enhance semantic search results. The proposed approach was validated using an open-source dataset of real maintenance records from excavators collected over ten years from different mining sites. A retrieval comparison using only text and multi-modal data is performed to estimate the proposed system’s effectiveness. Quantitative and qualitative analysis of results indicates a performance improvement of 8% using the proposed hybrid similarity approach compared to only text-based retrieval. To the best of our knowledge, this is the first study to combine LLMs and machine ontology for semantic search in maintenance records.</div></div>","PeriodicalId":55975,"journal":{"name":"Journal of Industrial Information Integration","volume":"45 ","pages":"Article 100835"},"PeriodicalIF":10.4,"publicationDate":"2025-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143677755","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}

引用次数: 0

STEP: A structured prompt optimization method for SCADA system tag generation using LLMs

IF 10.4 1区计算机科学

Journal of Industrial Information Integration Pub Date : 2025-03-21 DOI: 10.1016/j.jii.2025.100832

Fuyu Ma , Dong Li , Yu Liu , Dapeng Lan , Zhibo Pang

{"title":"STEP: A structured prompt optimization method for SCADA system tag generation using LLMs","authors":"Fuyu Ma , Dong Li , Yu Liu , Dapeng Lan , Zhibo Pang","doi":"10.1016/j.jii.2025.100832","DOIUrl":"10.1016/j.jii.2025.100832","url":null,"abstract":"<div><div>In the domain of industrial control, supervisory control and data acquisition (SCADA) systems are essential for real-time monitoring and efficient data acquisition. However, as industrial systems grow in scale and complexity, conventional tag configuration methods face challenges in balancing precision and operational efficiency. Addressing these challenges requires innovative solutions. The rapid evolution of generative artificial intelligence, particularly large language models (LLMs), offers a transformative approach. This study introduces a structured prompt optimization strategy, termed structured tag engineering prompt (STEP), to increase the ability of LLMs to generate high-quality tag files. To validate the STEP method, we assessed five mainstream LLMs on basic tag generation tasks via the CodeBERTScore and pass@k metrics. The results revealed that performance of all models has been improved, thus validating the effectiveness of the proposed optimization method. On the basis of these findings, a tag generation framework grounded in the STEP method was developed and validated through case studies and practical industrial scenarios. These validations confirmed the STEP method’s applicability, demonstrating its value and potential to advance prompt engineering for SCADA systems. In summary, this study contributes to the automation and intelligence of industrial control systems while providing unique insights through the application of LLMs combined with prompt engineering in addressing complex industrial tasks.</div></div>","PeriodicalId":55975,"journal":{"name":"Journal of Industrial Information Integration","volume":"45 ","pages":"Article 100832"},"PeriodicalIF":10.4,"publicationDate":"2025-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143760536","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}

引用次数: 0

Bridging the gap between Industry 4.0 and manufacturing SMEs: A framework for an end-to-end Total Manufacturing Quality 4.0’s implementation and adoption

IF 10.4 1区计算机科学

Journal of Industrial Information Integration Pub Date : 2025-03-21 DOI: 10.1016/j.jii.2025.100833

Badreddine Tanane , Mohand-Lounes Bentaha , Baudouin Dafflon , Néjib Moalla

{"title":"Bridging the gap between Industry 4.0 and manufacturing SMEs: A framework for an end-to-end Total Manufacturing Quality 4.0’s implementation and adoption","authors":"Badreddine Tanane , Mohand-Lounes Bentaha , Baudouin Dafflon , Néjib Moalla","doi":"10.1016/j.jii.2025.100833","DOIUrl":"10.1016/j.jii.2025.100833","url":null,"abstract":"<div><div>Manufacturing is one of the industrial sectors taking benefit from the 4th industrial revolution and bringing existing production capacities closer to the ”factory of the future”. Quality, as a main concern in manufacturing, is also to benefit from this change of paradigm by introducing new key enabling technologies such as Internet of Things (IoT) and Artificial Intelligence (AI) into quality management, earning it the label of Quality 4.0 (Q4.0). The implementation of these paradigms is still gathering research efforts as it is arduous to design and realize effective end-to-end Decision Support Systems (DSSs) for Q4.0, with several dimensions to consider when integrating digitalization with quality. This is an even more challenging task when it comes to SMEs’ efforts to implement these concepts, given the particularities of these entities. This paper presents an approach to design a Total Manufacturing Quality 4.0 (TMQ 4.0) DSS by combining Sensor Network (SN) data and historical data in an end-to-end framework. Furthermore, the paper presents the validation of the approach through a case study application in a metal-cutting high-precision manufacturing SME. It shows promising Q4.0 estimations with regular Machine Learning (ML) algorithms (kNN, Random Forest, Logistic Regression, XGboost, feed-forward Deep Neural Network) when the steps of tending to data quality, data augmentation, and end-to-end design and implementation are applied. By providing building blocks for an end-to-end Q4.0 DSS design and implementation in an integrated quality control application, this approach aims at supporting end-users in the in-process quality control of their manufacturing operations.</div></div>","PeriodicalId":55975,"journal":{"name":"Journal of Industrial Information Integration","volume":"45 ","pages":"Article 100833"},"PeriodicalIF":10.4,"publicationDate":"2025-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143678047","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}

引用次数: 0

Advancing software security: DCodeBERT for automatic vulnerability detection and repair

IF 10.4 1区计算机科学

Journal of Industrial Information Integration Pub Date : 2025-03-21 DOI: 10.1016/j.jii.2025.100834

Ahmed Bensaoud, Jugal Kalita

引用次数: 0

On the disagreement problem in Human-in-the-Loop federated machine learning

IF 10.4 1区计算机科学

Journal of Industrial Information Integration Pub Date : 2025-03-19 DOI: 10.1016/j.jii.2025.100827

Matthias Huelser , Heimo Mueller , Natalia Díaz-Rodríguez , Andreas Holzinger

{"title":"On the disagreement problem in Human-in-the-Loop federated machine learning","authors":"Matthias Huelser , Heimo Mueller , Natalia Díaz-Rodríguez , Andreas Holzinger","doi":"10.1016/j.jii.2025.100827","DOIUrl":"10.1016/j.jii.2025.100827","url":null,"abstract":"<div><div>The popularity of Artificial Intelligence (AI) has risen sharply in recent years, revolutionizing applications in most sectors with unprecedented functionalities. Milestones and achievements like ChatGPT demonstrate not only the impressive capabilities of AI, but also how accessible such technologies have become in recent times. However, the success of AI applications depends heavily on the underlying information integration processes. Among the most important processes are the training of the AI model at the core of the application and the collection and pre-processing of training data. In particular, the task of collecting high-quality training data can be very costly and resource-intensive, as in many cases large amounts of data have to be annotated manually. Human annotators must have extensive expertise for certain tasks in order to provide high-quality training data. In this paper, we present a framework to maximize the efficiency of human experts in a Machine Learning (ML) scenario, with the aim of optimizing the use of human expertise in active learning. This is done by constantly measuring the quality of human experts’ input, as well as by involving human annotators only when needed. We showcase the benefits of our proposed framework by applying it to a problem in image classification, proving its usefulness to reduce the cost of annotating training data. The source code of the framework is publicly available at <span><span>https://github.com/human-centered-ai-lab/app-HITL-annotator</span><svg><path></path></svg></span>.</div></div>","PeriodicalId":55975,"journal":{"name":"Journal of Industrial Information Integration","volume":"45 ","pages":"Article 100827"},"PeriodicalIF":10.4,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143677757","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}

引用次数: 0

Evaluating digital transformation readiness in prefabricated construction supply chains: A multi-level model and fairness-aware optimization approach

IF 10.4 1区计算机科学

Journal of Industrial Information Integration Pub Date : 2025-03-19 DOI: 10.1016/j.jii.2025.100831

Zhen-Song Chen , Kou-Dan Chen , Kannan Govindan , Maxwell Fordjour Antwi-Afari

{"title":"Evaluating digital transformation readiness in prefabricated construction supply chains: A multi-level model and fairness-aware optimization approach","authors":"Zhen-Song Chen , Kou-Dan Chen , Kannan Govindan , Maxwell Fordjour Antwi-Afari","doi":"10.1016/j.jii.2025.100831","DOIUrl":"10.1016/j.jii.2025.100831","url":null,"abstract":"<div><div>Prefabricated construction is revolutionizing the industry by promoting efficiency and sustainability through off-site manufacturing and on-site assembly. Despite its potential, the digital transformation of prefabricated construction supply chains (PCSCs) has not kept pace with Industry 4.0 advancements, resulting in fragmented information and operational inefficiencies. Even more, limited attention has been paid to establishing both a well-structured readiness model for PCSC digital transformation and an actionable assessment framework. This study addresses this gap by developing a comprehensive, multi-level readiness model tailored specifically for PCSCs, encompassing dimensions of technology, strategy, partnership, and personnel. To accurately evaluate digital transformation readiness, we propose a fairness-aware bi-objective optimization model that aggregates probabilistic expert opinions while considering individual behavioral factors related to fairness concerns. The model was applied in a case study of a PCSC project, demonstrating its feasibility and effectiveness. Results validated the model’s capability to provide a robust readiness assessment, identifying critical areas for improvement and offering actionable insights for stakeholders. This research fills a critical gap in the literature by providing practical guidance for PCSCs embarking on their digital transformation journey. The proposed framework serves as a valuable tool for organizations seeking to transition to digital supply chains by addressing both technical and managerial aspects of digital transformation.</div></div>","PeriodicalId":55975,"journal":{"name":"Journal of Industrial Information Integration","volume":"45 ","pages":"Article 100831"},"PeriodicalIF":10.4,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143704000","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}

引用次数: 0

Interconnected Industry 4.0 technologies: Identifying current network value and integration opportunities

IF 10.4 1区计算机科学

Journal of Industrial Information Integration Pub Date : 2025-03-19 DOI: 10.1016/j.jii.2025.100838

Vincenzo Varriale, Antonello Cammarano, Francesca Michelino, Mauro Caputo

{"title":"Interconnected Industry 4.0 technologies: Identifying current network value and integration opportunities","authors":"Vincenzo Varriale, Antonello Cammarano, Francesca Michelino, Mauro Caputo","doi":"10.1016/j.jii.2025.100838","DOIUrl":"10.1016/j.jii.2025.100838","url":null,"abstract":"<div><div>The basic principle of Industry 4.0 (I4.0) is the integration of digital systems and technologies to achieve complete automation and optimization. Despite the importance of integrating and interconnecting technologies according to I4.0 principles, the literature has mainly focused on the 'standalone' value of individual technologies while neglecting their potential network value. Given the high complexity of evaluating technologies in an integrated system, this study goes beyond the limitations of the 'standalone' analysis of I4.0 technologies. Specifically, the study proposes a methodology that identifies I4.0 technologies that play a central role in an integrated and interconnected network of technologies. By analyzing the literature, 5,271 business practices were collected in which I4.0 technologies are integrated to achieve specific impacts. Then, this paper employed social network analysis to explore the value of each I4.0 technology in a technology network. Using specific centrality indicators, current enabling, and central technologies were identified in an interconnected and integrated system following I4.0 principles. Finally, using the methodology of brokerage roles, the study reveals the I4.0 technologies, considered as 'drivers', that could have the greatest potential to unlock new future interconnection opportunities.</div></div>","PeriodicalId":55975,"journal":{"name":"Journal of Industrial Information Integration","volume":"45 ","pages":"Article 100838"},"PeriodicalIF":10.4,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143677756","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}

引用次数: 0