Journal of Industrial Information Integration最新文献

{"title":"Quantum financing system: A survey on quantum algorithms, potential scenarios and open research issues","authors":"Yang Lu,&nbsp;Jiaxian Yang","doi":"10.1016/j.jii.2024.100663","DOIUrl":"10.1016/j.jii.2024.100663","url":null,"abstract":"<div><p>Quantum financing system is a foreseeable future of finance, which will demonstrate more agile, accurate, and secured performance. Financial markets and related activities are changing dynamically, and quantum computing is one of the emerging technologies responding to financial developments. We attempt to outline a theoretical framework to illustrate a quantum financing system, including quantum financing algorithms, quantum financing circuits, and potential financial scenarios. Since quantum computer is still in the early stage, challenges and future directions are also discussed from a technological and operational perspective. This study provides a resource for researchers, practitioners and policymakers interested in empowering quantum computing to revolutionize financial services and systems. The research is one of the foundational studies that describe future ecology of quantum financing system.</p></div>","PeriodicalId":55975,"journal":{"name":"Journal of Industrial Information Integration","volume":"41 ","pages":"Article 100663"},"PeriodicalIF":10.4,"publicationDate":"2024-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141708798","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":"Combined deep-learning optimization predictive models for determining carbon dioxide solubility in ionic liquids","authors":"Shadfar Davoodi ,&nbsp;Hung Vo Thanh ,&nbsp;David A. Wood ,&nbsp;Mohammad Mehrad ,&nbsp;Mohammad Reza Hajsaeedi ,&nbsp;Valeriy S. Rukavishnikov","doi":"10.1016/j.jii.2024.100662","DOIUrl":"10.1016/j.jii.2024.100662","url":null,"abstract":"<div><p>This study explores the development of predictive models for carbon dioxide (CO₂) solubility in ionic liquids based on a compiled dataset of 10,116 experimentally measured data points involving four input variables: pressure (P), temperature (T), cation type, and anion type. The deep-learning (DL) predictive models evaluated are standalone and hybrid versions of convolutional neural network (CNN) and long short-term memory (LSTM) algorithms with cuckoo optimization algorithm (COA) and gradient-based optimization (GBO). The laboratory-measured data was separated into training and test categories, and each category was normalized separately to improve the performance of the deep learning algorithms. The Mahalanobis distance-based quantile method was utilized to identify any outliers in the training data. Once identified, the outlier data points were eliminated from the training dataset. The control parameters of the deep learning algorithms were optimized using COA to enhance their efficiency, and the algorithms were hybridized with optimization algorithms to further improve their performance. The resulting models were analyzed to assess their accuracy, degree of overfitting, and the importance of input features. The study found that using 80% of the data for training and 20% for testing results in more accurate and generalizable models. Using the outlier detection method on the training data led to 307 data points being eliminated as outliers. Developing CO₂-solubility predictive model showed that, the CNN<img>COA model had the lowest RMSE and highest R² among the developed models, indicating high generalizability for data unseen by the trained model. The analysis revealed that using optimization algorithms increased the CO₂-solubility prediction performance of DL algorithms and reduced overfitting. T and cation type were the most and least important input features, respectively. Simultaneous changes in cation and anion type on CO₂-solubility predictions displayed no systematic pattern. For increases in T, CO₂ solubility typically decreased, whereas for increases in P CO₂ solubility always increased but at variable rates. The results of this study can be used to develop accurate and generalizable CO₂-solubility predictive models for various applications.</p></div>","PeriodicalId":55975,"journal":{"name":"Journal of Industrial Information Integration","volume":"41 ","pages":"Article 100662"},"PeriodicalIF":10.4,"publicationDate":"2024-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141639257","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":"Group decision making method for third-party logistics management: An interval rough cloud optimization model","authors":"Musavarah Sarwar ,&nbsp;Muhammad Akram ,&nbsp;Wajeeha Gulzar ,&nbsp;Muhammet Deveci","doi":"10.1016/j.jii.2024.100658","DOIUrl":"10.1016/j.jii.2024.100658","url":null,"abstract":"<div><p>Group decision making in third-party logistics service selection plays an essential role for improving service quality, increasing efficiency and reducing the net cost. Fuzzy and uncertain linguistic variables are commonly used to represent experts‘rankings in optimization problems. To recognize the limits of human cognition and subjectivity of human evaluations, several optimization approaches have been studied to select remanufacturing alternatives in decision making processes, however these methods have certain deficiencies such as lacking manipulation tools of diverse information, randomness, use of predefined parameters increasing uncertainty, interpersonal relations among evaluation criteria. The integration of interval numbers, rough approximations, and cloud model theory plays a significant role to model incomplete and inadequate information occurring in decision making problems. This research paper focuses on the integration of dual interval rough integrated cloud model with best-worst optimization technique, Multi-Attributive Border Approximation area Comparison (MABAC) and Weighted Aggregated Sum Product Assessment (WASPAS) approaches. A novel min–max optimization model based dual interval rough integrated cloud values is designed to compute the weight coefficients and consistency ratio for each criteria. The consistency of proposed optimization model is checked using a consistency ratio test. Secondly, the alternatives are ranked using the proposed DIRI cloud based MABAC and WASPAS approaches using interval clouds based weighted sum and weighted product coefficients, approximation area values and distance formulae. The significance of the proposed model is highlighted with a case study of third-party logistics service management of an electronic firm. The rationality and out-performance of the proposed methodology is studied by a comparative analysis with existing approaches and detailed sensitivity analysis on different variations of criteria weights and parameter.</p></div>","PeriodicalId":55975,"journal":{"name":"Journal of Industrial Information Integration","volume":"41 ","pages":"Article 100658"},"PeriodicalIF":10.4,"publicationDate":"2024-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141622302","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 Cost-effective approach for quality control in PLA-based material extrusion 3D printing using 3D scanning","authors":"Andrea Montalti,&nbsp;Patrich Ferretti,&nbsp;Gian Maria Santi","doi":"10.1016/j.jii.2024.100660","DOIUrl":"10.1016/j.jii.2024.100660","url":null,"abstract":"<div><p>In this article, our aim is to underscore the importance of verifying that components produced through material extrusion additive manufacturing exhibit geometric and dimensional conformity with the STL (Standard Tessellation Language) model. Currently, the business world is heavily investing in additive technologies, but it is crucial to obtain feedback on the accuracy of the printed component without excessive economic expenditure. For this reason, we have opted to utilize a mid-range 3D scanner (Revopoint Mini with an accuracy of 0.02 mm) to investigate any disparities in print results using PLA material. Each model has been scanned and compared with the initial mesh to qualitatively and quantitatively assess the present errors. The analysis has revealed that the majority of features can be effectively controlled, while the remaining ones either fall within the tool's precision or necessitate a higher-quality scan. Particularly in the analysed case, flat surfaces, profiles of complex geometries, and holes have demonstrated dimensional and geometric controllability. However, details of reduced dimensions or those difficult to reach by the scanner do not allow for adequate comparison due to excessive standard deviation in the error. The analysed layer heights do not exhibit a significant impact on component accuracy.</p></div>","PeriodicalId":55975,"journal":{"name":"Journal of Industrial Information Integration","volume":"41 ","pages":"Article 100660"},"PeriodicalIF":10.4,"publicationDate":"2024-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2452414X24001043/pdfft?md5=756cdcd5a4e6ebe2047139e04b1b1f85&pid=1-s2.0-S2452414X24001043-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141703209","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":"Knowledge reuse for ontology modelling and application of maintenance motion state sequence","authors":"Qidi Zhou ,&nbsp;Dong Zhou ,&nbsp;Yan Wang ,&nbsp;Ziyue Guo ,&nbsp;Chao Dai","doi":"10.1016/j.jii.2024.100659","DOIUrl":"10.1016/j.jii.2024.100659","url":null,"abstract":"<div><p>With the current digital transformation and the development of complex manufacturing systems, advanced maintenance is proposed to improve the competitiveness of complex products, generating a large amount of heterogeneous maintenance data and information. There is a lack of standardized representations of motion-centred maintenance knowledge which leads to semantic ambiguity and poor intertranslatability. In addition, it causes subjective deviations and human resource investments in related time prediction applications. Therefore, a knowledge reuse method for ontology modelling and the application of maintenance motion state sequences is proposed. First, a framework for reusing maintenance motion state sequence (MMSS) knowledge is established, which is defined as the state sets of time-sequence maintenance motion. Second, maintenance motion state sequence ontology (MMSSO) is constructed to standardize the definition of MMSS, as a supplement to the current maintenance ontologies. Third, an MMSSO application for automatic maintenance time prediction is proposed by incorporating the standardized specifications of MMSSO and improving the MODAPTS method. Finally, using aviation equipment as an example, the rationality and superiority of MMSSO in real applications are verified. MMSSO is a new practice of integrating multi-source information in advanced maintenance. It can also provide predicted time as an iterative reference for industrial practitioners in the digital design stage.</p></div>","PeriodicalId":55975,"journal":{"name":"Journal of Industrial Information Integration","volume":"41 ","pages":"Article 100659"},"PeriodicalIF":10.4,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141708363","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 force-inspired paradigm for performance-based decision support—Physics of Decision application in nonlinear dynamical systems","authors":"Nafe Moradkhani ,&nbsp;Frederick Benaben ,&nbsp;Benoit Montreuil ,&nbsp;Matthieu Lauras ,&nbsp;Thibaut Cerabona ,&nbsp;Clara Le Duff ,&nbsp;Louis Faugere ,&nbsp;Julien Jeany","doi":"10.1016/j.jii.2024.100656","DOIUrl":"https://doi.org/10.1016/j.jii.2024.100656","url":null,"abstract":"<div><p>This paper provides a perspective on performance-based decision support. The chosen approach is based on the principles of “Physics of Decision”, which considers the performance of a system as a physical trajectory within the boundaries of its performance indicators that might be deviated through variation of system parameters. According to the overall premise of employing the state-space method to simulate physical systems, this work presents a decision aggregation method in dynamic systems. The core contribution is to propose a multi-criteria performance framework to manage multi-input-multi-output (MIMO) system performance with a combination of affordable decisions. A nonlinear inventory-workforce management model has been used to demonstrate the proposed approach.</p></div>","PeriodicalId":55975,"journal":{"name":"Journal of Industrial Information Integration","volume":"41 ","pages":"Article 100656"},"PeriodicalIF":10.4,"publicationDate":"2024-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141540132","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":"Domain-specific languages for the automated generation of datasets for industry 4.0 applications","authors":"Brian Sal,&nbsp;Diego García-Saiz,&nbsp;Alfonso de la Vega,&nbsp;Pablo Sánchez","doi":"10.1016/j.jii.2024.100657","DOIUrl":"https://doi.org/10.1016/j.jii.2024.100657","url":null,"abstract":"<div><p>Data collected in Industry 4.0 applications must be converted into tabular datasets before they can be processed by analysis algorithms, as in any data analysis system. To perform this transformation, data scientists have to write complex and long scripts, which can be a cumbersome process. To overcome this limitation, a language called Lavoisier was recently created to facilitate the creation of datasets. This language provides high-level primitives to select data from an object-oriented data model describing data available in a context. However, industrial engineers might not be used to deal with this kind of model. So, this work introduces a new set of languages that adapt Lavoisier to work with fishbone diagrams, which might be more suitable in industrial settings. These new languages keep the benefits of Lavoisier, reducing dataset creation complexity by 40% and up to 80%, and outperforming Lavoisier in some cases.</p></div>","PeriodicalId":55975,"journal":{"name":"Journal of Industrial Information Integration","volume":"41 ","pages":"Article 100657"},"PeriodicalIF":10.4,"publicationDate":"2024-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2452414X24001018/pdfft?md5=d889d7ec504c180c01cd190b069820dc&pid=1-s2.0-S2452414X24001018-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141540900","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":"A green scheduling model for two-stage photo-etching and acid-etching collaboration in semiconductor manufacturing","authors":"Min Kong ,&nbsp;Yajing Zhang ,&nbsp;Jin Xu ,&nbsp;Weizhong Wang ,&nbsp;Shaojun Lu ,&nbsp;Amir M. Fathollahi-Fard","doi":"10.1016/j.jii.2024.100655","DOIUrl":"10.1016/j.jii.2024.100655","url":null,"abstract":"<div><p>In semiconductor manufacturing, photo-etching and acid-etching processes play crucial roles in precisely crafting intricate patterns on storage chip wafers. However, these processes generate significant hazardous waste, leading to high disposal costs. Consequently, there has been increased research into cost-effective and environmentally friendly solutions. This study introduces a custom green scheduling framework inspired by sustainable practices in storage chip wafer fabrication. The framework optimizes the coordination of photo-etching and acid-etching processes, taking into account wait time limits and capacity constraints. Additionally, we propose an efficient hybrid meta-heuristic algorithm designed to reduce energy consumption, minimize makespan, and optimize the quantity of acid-etching baths. This approach identifies the most efficient number of acid-etching tanks for various scenarios, significantly reducing waste production. Empirical results demonstrate the algorithm's effectiveness, highlighting its potential for substantial cost savings and waste reduction. By exploring the relationship between the number of acid-etching tanks and makespan, we identify the optimal tank quantity for diverse scenarios. These insights pave the way for enhanced resource efficiency and sustainable practices in semiconductor manufacturing.</p></div>","PeriodicalId":55975,"journal":{"name":"Journal of Industrial Information Integration","volume":"41 ","pages":"Article 100655"},"PeriodicalIF":10.4,"publicationDate":"2024-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141463794","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":"Adaptive optimization federated learning enabled digital twins in industrial IoT","authors":"Wei Yang ,&nbsp;Yuan Yang ,&nbsp;Wei Xiang ,&nbsp;Lei Yuan ,&nbsp;Kan Yu ,&nbsp;Álvaro Hernández Alonso ,&nbsp;Jesús Ureña Ureña ,&nbsp;Zhibo Pang","doi":"10.1016/j.jii.2024.100645","DOIUrl":"https://doi.org/10.1016/j.jii.2024.100645","url":null,"abstract":"<div><p>The Industrial Internet of Things (IIoT) plays a pivotal role in steering enterprises towards comprehensive digital transformation and fostering intelligent production, which serves as a critical pillar of Industry 4.0. Digital twin (DT) emerges as a highly promising technology, enabling the digital transformation of the IIoT by seamlessly bridging physical systems with digital spaces. However, the overall service quality of the IIoT is severely impacted by the resource-limited devices and the massive, heterogeneous and sensitive data in the IIoT. As an innovative distributed machine learning paradigm, federated learning (FL) inherently possesses advantages in handling private and heterogeneous data. In this paper, we propose a novel framework integrating <strong>F</strong>L with <strong>D</strong>T-<strong>e</strong>nabled <strong>I</strong>IoT, termed FDEI, which combines the merits of both to improve service quality while maintaining trustworthiness. To enhance the modeling efficiency, we develop FedOA, an <strong>a</strong>daptive <strong>o</strong>ptimization <strong>F</strong>L method that dynamically adjusts the local update coefficient and model compression rate in resource-limited IIoT scenarios, to construct the FDEI model. Specifically, leveraging the interdependence between the two variables, we conduct a theoretical analysis of the model convergence rate and derive the associated convergence bounds. Building upon the theoretical analysis, we further propose a joint adaptive adjustment strategy by optimizing the two variables across various clients to minimize runtime differences and accelerate the convergence rate. Numerical results demonstrate that our proposed approach achieves an approximate 68% improvement in convergence speed and a reduction of approximately 66% in traffic consumption compared to the benchmarks (e.g., FedAvg, AFL, and CSFL).</p></div>","PeriodicalId":55975,"journal":{"name":"Journal of Industrial Information Integration","volume":"41 ","pages":"Article 100645"},"PeriodicalIF":10.4,"publicationDate":"2024-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141439070","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":"Assessment of process chain suitability of the optical 3D measuring system by using influencing factors for measurement uncertainty","authors":"Martin Bilušić ,&nbsp;Luka Olivari","doi":"10.1016/j.jii.2024.100654","DOIUrl":"10.1016/j.jii.2024.100654","url":null,"abstract":"<div><p>Optical 3D measuring systems serve as indispensable tools for the measurement and quality control of complex objects feeding process chains in industrial information integration. However, the accuracy of 3D measurements is influenced by a multitude of parameters, and the associated measurement uncertainties and influential factors remain insufficiently researched. This study investigates the effects of measurement object properties and software on measurement outcomes. Specifically, we examine seven geometries (diameter, distance, roundness, concentricity, flatness, parallelism and verticality) and four influencing factors (surface roughness, coating, polygonization, and interpolation). Our analysis employs variance analysis and compares the results with those obtained through linear regression using machine learning. In conclusion, the analysis of measurement uncertainty for optical 3D measurement systems in the assessment of seven distinct geometric characteristics provides a framework for determination of process chain suitability of the optical 3D measuring system.</p></div>","PeriodicalId":55975,"journal":{"name":"Journal of Industrial Information Integration","volume":"41 ","pages":"Article 100654"},"PeriodicalIF":10.4,"publicationDate":"2024-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141410010","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}