Qun Wu , Weiqi Tan , Ligang Zhou , Muhammet Deveci , Dragan Pamucar , Witold Pedrycz
{"title":"An integrated decision support framework for exploring the barriers and potential application scenarios in metaverse hospitality","authors":"Qun Wu , Weiqi Tan , Ligang Zhou , Muhammet Deveci , Dragan Pamucar , Witold Pedrycz","doi":"10.1016/j.jii.2025.100825","DOIUrl":"10.1016/j.jii.2025.100825","url":null,"abstract":"<div><div>The global hospitality industry is undergoing a profound transformation, primarily driven by the internet era within the context of Industry 4.0 and the continuous evolution of the metaverse. The metaverse offers limitless possibilities for creating immersive and personalized accommodation experiences by closely integrating the virtual with the real world. It also provides a new perspective and mindset for guiding the hospitality industry to rethink and redesign service models and business processes. Although the metaverse application in the hospitality industry has already made significant progress, this process still faces numerous barriers, and the specific application scenarios of the metaverse hospitality industry (MHI) remain unclear. This study aims to develop an integrated decision support framework for exploring the barriers and potential application scenarios in metaverse hospitality. First, the interval type-2 fuzzy sets (IT2FSs) is introduced to quantify the complex and uncertain information in the decision-making procedure. Second, the IT2F-BWM with the IT2F weighted averaging (IT2FWA) operator is proposed to calculate the barriers’ weights considering the group opinions. Third, the IT2FWA operator and IT2F-ExpTODIM method are incorporated to prioritize the potential application scenarios in MHI. Finally, a case study on the prioritization of barriers and application scenarios in MHI is utilized to test the effectiveness and practicality of the presented framework. Results show that the technology barrier (0.5217) and the interaction technology (0.2483) have the highest levels among the main and sub-main barrier hierarchies, respectively. The findings of this article may enrich the theories of uncertain decision-making methods and provide instructive suggestions for the operation and management of metaverse hospitality practice.</div></div>","PeriodicalId":55975,"journal":{"name":"Journal of Industrial Information Integration","volume":"45 ","pages":"Article 100825"},"PeriodicalIF":10.4,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143643965","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":"Knowledge-enhanced ontology-to-vector for automated ontology concept enrichment in BIM","authors":"Yinyi Wei, Xiao Li","doi":"10.1016/j.jii.2025.100836","DOIUrl":"10.1016/j.jii.2025.100836","url":null,"abstract":"<div><div>Building Information Modeling (BIM) relies on standardized ontologies like IfcOWL to address interoperability. However, the increasing complexity and diversity of construction information requirements demand automated enrichment of BIM ontologies, which is hindered by several factors, including complexity in ontology structure, scalability limitations, and domain-specific issues. Manual curation and maintenance of ontologies are labor-intensive and time-consuming, particularly as the scope of BIM projects expands. Despite these challenges, the construction industry lacks an effective automated approach for ontology concept enrichment. Thus, this study proposes a knowledge-enhanced ontology-to-vector (Keno2Vec) approach for automated BIM ontology concept enrichment, which can (1) encode ontology elements into meaningful and semantically rich embeddings by employing the BERT model to integrate both ontological information (names and labels) and external knowledge (definitions from authoritative knowledge bases), effectively addressing the domain expression specificity and complexity of BIM ontologies; and (2) provide a flexible framework that supports various downstream tasks of ontology concept enrichment by utilizing the resulting embeddings, thereby improving the task-specific adaptability and variability. Experimental results on datasets derived from the large-scale ifcOWL and two smaller BIM ontologies demonstrate that Keno2Vec significantly outperforms existing ontology embedding approaches in terms of accuracy and adaptability. For example, Keno2Vec achieves F1 scores on ifcOWL of nearly 87 % for subsumption prediction, 60 % for property identification, 95 % for membership recognition, and 100 % and 90 % for category-based and schema-based concept classification, respectively. Additional analysis highlights the potential of Keno2Vec for improving BIM ontology encoding and benefiting downstream applications.</div></div>","PeriodicalId":55975,"journal":{"name":"Journal of Industrial Information Integration","volume":"45 ","pages":"Article 100836"},"PeriodicalIF":10.4,"publicationDate":"2025-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143678081","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}
Baotong Chen , Xin Tong , Jiafu Wan , Lei Wang , Xianyin Duan , Zhaohui Wang , Xuhui Xia
{"title":"Knowledge sharing-enabled low-code program for collaborative robots in mix-model assembly","authors":"Baotong Chen , Xin Tong , Jiafu Wan , Lei Wang , Xianyin Duan , Zhaohui Wang , Xuhui Xia","doi":"10.1016/j.jii.2025.100824","DOIUrl":"10.1016/j.jii.2025.100824","url":null,"abstract":"<div><div>Multi-robot collaboration is a crucial execution tool for mixed-model assembly lines. The rapid reconfiguration of the robots with impaired skills to maintain the robustness of the assembly line remains a significant challenge. With a focus on knowledge-driven faster transition technologies for collaborative robots, this paper proposes a Knowledge Sharing-enabled Low-code Program (KSLC) method to address the deficient skill migration and the limited scalability caused by programs written statically in open-loop control. First, considering collaborative robots' functional requirements and environmental constraints, the parameterized action primitive library of assembly skills is developed with properties across multiple perspectives, levels, and granularities. Complex assembly skills are then formally expressed using the Web Ontology Language (OWL). Besides, digraph network model is created to represent action sequences and the corresponding parameters relevant to complex assembly tasks for the execution content. Finally, the DQN algorithm is utilized to learn low-dimensional vectors within the knowledge graph. The GraphSAGE algorithm is employed to facilitate skill search and matching, enabling the effective acquisition and transmission of robot skills. Experimental results demonstrate that the proposed KSLC-enabled collaborative robots achieve 90 % average success rate in the TwoArmPegInHole task, significantly outperforming the traditional experience transfer strategies that only attain 58 % success rate. This finding indicates that KSLC can substantially enhance robot learning efficiency and task performance.</div></div>","PeriodicalId":55975,"journal":{"name":"Journal of Industrial Information Integration","volume":"45 ","pages":"Article 100824"},"PeriodicalIF":10.4,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143643963","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}
Lorenzo Failla , Marco Rossoni , Marco Quirini , Giorgio Colombo
{"title":"Managing lifecycle of product information with an ontology-based knowledge framework","authors":"Lorenzo Failla , Marco Rossoni , Marco Quirini , Giorgio Colombo","doi":"10.1016/j.jii.2025.100820","DOIUrl":"10.1016/j.jii.2025.100820","url":null,"abstract":"<div><div>The effective management of product information within a formalized, digital and interoperable infrastructure remains a significant gap in realizing the full potential of modern Product Lifecycle Management (PLM) implementations in industrial contexts. While the academic paradigm of PLM has been extensively emphasized in the scientific literature for over two decades as a sustainable company strategy, contemporary PLM implementations prove inadequate in handling the extensive volume and variety of information generated throughout a product’s lifecycle. Starting from a comprehensive overview of the evolution of the PLM paradigm and of its inherent implications, the analysis of the PLM implementation of a big player in engineering and manufacturing of turbomachinery products for Oil & Gas and Energy markets is analyzed, allowing to identify existing major general contradictions from an industrial perspective. While it is reaffirmed that the attainment of a neutral, harmonized and universally agreed standardization is nowadays missing and is crucial in the enabling of the PLM paradigm through digital technologies, the present study attempts to demonstrate how a general and agnostic ontology-based framework may straightforwardly fulfill all the identified demands of the PLM paradigm and, therefore, how ontologies play a central role in this field of research by bridging different domains to enable a holistic product conceptualization, lifecycle management, and data interoperability among different digital agents.</div></div>","PeriodicalId":55975,"journal":{"name":"Journal of Industrial Information Integration","volume":"45 ","pages":"Article 100820"},"PeriodicalIF":10.4,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143611047","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":"Data center multidimensional management strategy based on descending neighborhood DBSCAN algorithm in unsupervised learning","authors":"Bin Liang, Junqing Bai","doi":"10.1016/j.jii.2025.100830","DOIUrl":"10.1016/j.jii.2025.100830","url":null,"abstract":"<div><div>Cloud users rent virtual machines (VMs) with varying parameters tailored to their unique business requirements. These diverse VM parameters add complexity to data center (DC) management strategies. Among the crucial parameters are CPU and memory, which must be optimized to ensure efficient physical resource utilization and decreased DC energy consumption. This article proposes three algorithms to manage and optimize VMs. Firstly, the density-based spatial clustering of applications with noise (DBSCAN) algorithm is enhanced, leading to the introduction of the descending neighborhood DBSCAN (DNDBSCAN) algorithm. This algorithm facilitates the clustering of physical machines (PMs). Secondly, the cluster center nearest classification algorithm (CCN) is proposed, leveraging VM attributes and the remaining capacity of the cluster center to classify the VMs for deployment. Additionally, the avoid hot spot time correlation algorithm (AHTC) is introduced to handle VM mapping, deploying VMs on the most time-relevant PMs while mitigating hot spots. Lastly, these three algorithms are integrated into a DC multidimensional management strategy based on the DNDBSCAN algorithm within the framework of unsupervised learning (DND). When compared to other algorithms, the DND algorithm demonstrates significant improvement in PM balanced utilization and reduction of DC energy consumption. The average balanced utilization of PM of the DND algorithm is 86 %, which is an average improvement of 11 % compared to the comparative algorithm. The average total energy consumption of the DND algorithm is 124 kW•h, which is an average reduction of 41 % compared to the comparative algorithm.</div></div>","PeriodicalId":55975,"journal":{"name":"Journal of Industrial Information Integration","volume":"45 ","pages":"Article 100830"},"PeriodicalIF":10.4,"publicationDate":"2025-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143611046","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":"Structural equation modeling of data usage factors in the construction sector: A comprehensive validation of micro level data usage factors","authors":"Murali Krishna Chenchu , Kirti Ruikar , Kumar Neeraj Jha","doi":"10.1016/j.jii.2025.100828","DOIUrl":"10.1016/j.jii.2025.100828","url":null,"abstract":"<div><div>The construction industry's digitalization produces a large volume of data from sources like Building Information Modeling (BIM), IoT sensors, drones, real-time project monitoring, and resource tracking. However, only 1-2 % of this data is effectively utilized due to limitations in processing, analysis, and integration across platforms. These limitations are influenced by micro-level factors like syntactics (structure), empirics (accessibility), and semantics (meaning). Current literature highlights a gap in understanding the impact of these micro-level factors on data usability (pragmatics). This study explores the micro-level factors affecting the usability of highway infrastructure data. A survey was conducted among 105 highway stakeholders, and the data was analyzed using covariance-based structural equation modeling (CB-SEM). The findings show that structured data significantly improves both accessibility and interpretability, positively influencing real-world decision-making. Interestingly, the clarity of data (semantics) has a lesser direct impact on its practical use compared to structure and accessibility. The study's originality lies in its focus on the under-researched highway construction sector. It offers practical recommendations for project managers to prioritize data structure and accessibility, improving efficiency by reducing delays and optimizing resource allocation. Globally, these strategies can be applied to large infrastructure projects. The study also highlights the social implications of improving transparency and accountability in public infrastructure projects through better data-driven decision-making.</div></div>","PeriodicalId":55975,"journal":{"name":"Journal of Industrial Information Integration","volume":"45 ","pages":"Article 100828"},"PeriodicalIF":10.4,"publicationDate":"2025-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143620755","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}
Bandar Alzahrani , Haitham Bahaitham , Ahmad Elshennawy
{"title":"A validated framework for assessing the maturity level of implementing quality 4.0 in higher education institutions","authors":"Bandar Alzahrani , Haitham Bahaitham , Ahmad Elshennawy","doi":"10.1016/j.jii.2025.100823","DOIUrl":"10.1016/j.jii.2025.100823","url":null,"abstract":"<div><div>Quality 4.0, a modern approach to quality management, applies Industry 4.0 principles to enhance product and service quality. By utilizing data-driven techniques like predictive analytics, machine learning, and artificial intelligence, Quality 4.0 aims to improve traditional quality management systems. Higher education institutions (HEIs) can benefit from Quality 4.0 by employing data-driven decision-making, automation, and analytics to identify process and service improvement areas. This study introduces a framework to evaluate the maturity level of HEIs in their transition to Quality 4.0, focusing on the process, people, and technology dimensions outlined in the LNS Research Quality 4.0 model. A survey consisting of 95 practices categorized into eleven Quality 4.0 axes was developed to assess the current level of HEI transformation efforts and pinpoint their strengths and weaknesses. Consequently, the participating HEIs were classified into one of the five maturity levels defined by the Quality 4.0 Maturity Scale (Q4.0-MS). The framework's validity was established by evaluating the maturity of Quality 4.0 implementation in a group of Saudi HEIs. The Friedman test was conducted to statistically confirm the framework's ability to differentiate between the observed maturity levels of Quality 4.0 adoption among the study participants. The results revealed the validity of the developed framework by assessing the maturity level of Quality 4.0 adoption within the participating HEIs. Particularly, the results showed that all 26 Saudi HEIs achieved scores ranging from the second to the fifth levels of the Q4.0-MS, indicating varying levels of Quality 4.0 adoption, from initial stages of building foundations to advanced implementation. This comprehensive understanding of Quality 4.0 implementation in the participating Saudi HEIs can be extended to other higher education institutions globally, as the framework's validity has been confirmed.</div></div>","PeriodicalId":55975,"journal":{"name":"Journal of Industrial Information Integration","volume":"45 ","pages":"Article 100823"},"PeriodicalIF":10.4,"publicationDate":"2025-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143636335","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 integrated weighted multi-criteria decision making method using Z-number and its application in failure modes and effect analysis","authors":"Muhammad Akram , Inayat Ullah , Tofigh Allahviranloo , Mohammadreza Shahriari","doi":"10.1016/j.jii.2025.100805","DOIUrl":"10.1016/j.jii.2025.100805","url":null,"abstract":"<div><div>In this study, a new technique of <span><math><mi>Z</mi></math></span>-number preference ranking by similarity to the ideal solution is proposed for estimating risk in failure mode and effects analysis. The method ranks all identified faults using subjective and objective weights of risk factors. The subjective weights are calculated by the <span><math><mi>Z</mi></math></span>-number analytical hierarchy process, and the objective weights are calculated using the <span><math><mi>Z</mi></math></span>-number Shannon entropy measure. The combination of the subjective and objective weights of the risk factors is used to prioritize the failure modes. Firstly, the expert team is asked to rate the failure modes concerning the risk factors in linguistic terms consisting of two parts, possibility and reliability. The experts’ evaluation is then converted into <span><math><mi>Z</mi></math></span>-numbers, treating the two components as triangular fuzzy numbers. This method also incorporates the experts’ weights to aggregate the individual ratings by the average method. The method ranks the failure modes by calculating the distance of each failure mode from the <span><math><mi>Z</mi></math></span>-number positive ideal solution and <span><math><mi>Z</mi></math></span>-number negative ideal solution. The proposed methodology is illustrated through a flowchart. The strategy is further explained by applying it to a case study of the operation of a crane in a steel mill. Furthermore, the validity and effectiveness of the proposed technique are verified by presenting a comparative analysis of outcomes with the existing techniques. Finally, the sensitivity of the proposed study is also tested and explained by using various diagrams. In the proposed strategy, conversion of <span><math><mi>Z</mi></math></span>-numbers into fuzzy numbers is avoided, which means there is little loss of information as compared to the existing techniques, which, in turn, lead to optimal decisions.</div></div>","PeriodicalId":55975,"journal":{"name":"Journal of Industrial Information Integration","volume":"45 ","pages":"Article 100805"},"PeriodicalIF":10.4,"publicationDate":"2025-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143601135","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":"Systematic review of mobile robots applications in smart cities with future directions","authors":"Ravinesh Chand , Bibhya Sharma , Sandeep Ameet Kumar","doi":"10.1016/j.jii.2025.100821","DOIUrl":"10.1016/j.jii.2025.100821","url":null,"abstract":"<div><div>Smart cities can create a connected and efficient urban environment by integrating advanced technologies with mobile robots. Mobile robots play a significant role in various smart city applications, ranging from transportation and logistics to surveillance and maintenance tasks, and have the potential to revolutionize the way people live and work in smart cities. Ensuring the efficient, greener and safe operation of these robots is crucial for the success and sustainability of smart city operations. However, several challenges must be addressed, such as safe autonomous navigation, motion control and security. This systematic literature review explores the current state of knowledge and emerging trends in autonomous motion control of personal and assistive mobile robots from 2015 to 2023, as well as the challenges and opportunities for possible application in smart city environments. In particular, it investigates the navigational approaches for future application of mobile robotic systems in the essential smart city components of personal transportation, assistive technologies and road and highway robots. Additionally, it contributes to the ongoing research about integrating mobile robotics into smart city applications and highlights future research directions. Researchers can incorporate insights from this review into their development plans for industrial integration by designing infrastructure that accommodates and leverages mobile robots for numerous smart city operations, including transportation, waste management and surveillance.</div></div>","PeriodicalId":55975,"journal":{"name":"Journal of Industrial Information Integration","volume":"45 ","pages":"Article 100821"},"PeriodicalIF":10.4,"publicationDate":"2025-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143611045","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 hybrid constraint programming and cross-entropy approach for balancing U-Shaped disassembly line with flexible workstations and spatial constraints","authors":"Yu Zhang , Zeqiang Zhang , Feng Chu , Saïd Mammar","doi":"10.1016/j.jii.2025.100817","DOIUrl":"10.1016/j.jii.2025.100817","url":null,"abstract":"<div><div>Disassembly lines are an effective means for the large-scale, industrialized recycling of end-of-life products. Among these, U-shaped disassembly lines are particularly noted for their combination of flexibility and production efficiency. This study addresses the U-shaped disassembly line balancing problem, considering the coexistence of separate stations and spatial limitations within workstations. A mixed-integer nonlinear programming model and a constraint programming model are developed to accurately capture this complex problem. Additionally, a novel hybrid constraint programming with a goal-driven cross-entropy optimization algorithm (CP–GDCE) is introduced. This algorithm combines a multi-objective cross-entropy grouping framework, a constraint programming-based heuristic initialization, a multi-point crossover recombination mechanism, and large neighborhood search techniques, significantly enhancing solution efficiency and accuracy. Extensive benchmarking and experimental validation indicate that the CP–GDCE not only excels in addressing the specific problem of this study but also demonstrates superiority in classic disassembly line balancing issues. In 21 test cases, the CP–GDCE achieved superior hypervolume and inverted generational distance values compared to 11 benchmark algorithms. A practical application using a printer disassembly example shows that the proposed U-shaped configuration is highly flexible and efficient, compatible with both traditional U-shaped and straight disassembly lines. This configuration significantly reduces the total length of the disassembly line, improving space utilization and highlighting its practical potential and advantages.</div></div>","PeriodicalId":55975,"journal":{"name":"Journal of Industrial Information Integration","volume":"45 ","pages":"Article 100817"},"PeriodicalIF":10.4,"publicationDate":"2025-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143578892","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}