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Research Articles

A novel approach for predicting Lockout/Tagout safety procedures for smart maintenance strategies

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Pages 4754-4775 | Received 24 Dec 2022, Accepted 03 Oct 2023, Published online: 01 Nov 2023

References

  • Aggarwal, Anubhav, Jasmeet Singh, and K. Gupta. 2018. “A Review of Different Text Categorization Techniques.” International Journal of Engineering and Technology(UAE) 7: 11–15. https://doi.org/10.14419/ijet.v7i3.8.15210.
  • Al-Hawari, Assem, Hassan Najadat, and Raed Shatnawi. 2021. “Classification of Application Reviews into Software Maintenance Tasks Using Data Mining Techniques.” Software Quality Journal 29 (3): 667–703. https://doi.org/10.1007/s11219-020-09529-8.
  • Al-Tarawneh, Batool, and Hani Bani-Salameh. 2023. “Classification of firewall logs actions using machine learning techniques and deep neural network.” In AIP Conference Proceedings. Vol. 2979, 050003-1–050003-10. Melville, NY: AIP Publishing.
  • Almarie, Bassel, Carlos Rossetti, Paulo EP Teixeira, Kevin Pacheco-Barrios, and Felipe Fregni. 2023. “The Use of Large Language Models in Science-Opportunities and Challenges.” Principles and Practice of Clinical Research 9 (1): 1–4.
  • Almutairi, Raid, Zaid Albeladi, and Ali Elrashidi. 2023. “Assessment of Health and Safety Hazards Affecting Workers at Saline Water Conversion Corporation Lathe Workshop.” In Digitalisation: Opportunities and Challenges for Business. Vol. 2, edited by Alareeni Bahaaeddin, Hamdan Allam, Khamis Reem, and Khoury Rim El, 824–837. Cham: Springer International Publishing.
  • Aning, Samuel, and Małgorzata Przybyła-Kasperek. 2022. “Comparative Study of Twoing and Entropy Criterion for Decision Tree Classification of Dispersed Data.” Procedia Computer Science 207: 2434–2443. https://doi.org/10.1016/j.procs.2022.09.301.
  • Anthony, L., and G. V. Lashkia. 2003. “Mover: A Machine Learning Tool to Assist in the Reading and Writing of Technical Papers.” IEEE Transactions on Professional Communication 46 (3): 185–193. https://doi.org/10.1109/TPC.2003.816789.
  • Beetz, Michael, Georg Bartels, Alin O. Albu-Schäffer, Ferenc Bálint-Benczédi, Rico Belder, Daniel Beßler, Sami Haddadin, et al. 2015. “Robotic Agents Capable of Natural and Safe Physical Interaction with Human co-Workers.” Paper presented at the 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 6528–6535.
  • Bielza, C., G. Li, and P. Larrañaga. 2011. “Multi-dimensional Classification with Bayesian Networks.” International Journal of Approximate Reasoning 52 (6): 705–727. https://doi.org/10.1016/j.ijar.2011.01.007.
  • Bin, M. A. 2015. “Study of an Improved K_Nearest Neighbor Algorithm for Network Public Opinion Classification.” Microelectronics & Computer 32 (6): 62–66. https://doi.org/10.19304/j.cnki.issn1000-7180.2015.06.014.
  • Boateng, Ernest Yeboah, Joseph Otoo, and Daniel A Abaye. 2020. “Basic Tenets of Classification Algorithms K-Nearest-Neighbor, Support Vector Machine, Random Forest and Neural Network: A Review.” Journal of Data Analysis and Information Processing 8 (4): 341–357. https://doi.org/10.4236/jdaip.2020.84020.
  • Bodendorf, Frank, Philipp Merkl, and Jörg Franke. 2022. “Artificial Neural Networks for Intelligent Cost Estimation – A Contribution to Strategic Cost Management in the Manufacturing Supply Chain.” International Journal of Production Research 60 (21): 6637–6658. https://doi.org/10.1080/00207543.2021.1998697.
  • Boulesteix, Anne-Laure, Silke Janitza, Jochen Kruppa, and Inke R. König. 2012. “Overview of Random Forest Methodology and Practical Guidance with Emphasis on Computational Biology and Bioinformatics.” WIRES Data Mining and Knowledge Discovery 2 (6): 493–507. https://doi.org/10.1002/widm.1072.
  • Brundage, Michael P., Thurston Sexton, Melinda Hodkiewicz, Alden Dima, and Sarah Lukens. 2021. “Technical Language Processing: Unlocking Maintenance Knowledge.” Manufacturing Letters 27: 42–46. https://doi.org/10.1016/j.mfglet.2020.11.001.
  • Bulzacchelli, Maria T., Jon S. Vernick, Gary S. Sorock, Daniel W. Webster, and Peter S.J. Lees. 2008. “Circumstances of Fatal Lockout/Tagout-Related Injuries in Manufacturing.” American Journal of Industrial Medicine 51 (10): 728–734. https://doi.org/10.1002/ajim.20630.
  • Bulzacchelli, M. T., J. S. Vernick, D. W. Webster, and P. S. Lees. 2007. “Effects of the Occupational Safety and Health Administration's Control of Hazardous Energy (Lockout/Tagout) Standard on Rates of Machinery-Related Fatal Occupational Injury.” Injury Prevention 13 (5): 334–338. https://doi.org/10.1136/ip.2007.015677.
  • Burlet-Vienney, Damien, Yuvin Chinniah, Ayoub Nokra, and Abdallah Ben Mosbah. 2021. “Safety in the Quebec Construction Industry: An Overview of and Possible Improvements in Hazardous Energy Control Using Lockout on Construction Sites by Electricians, Pipefitters, Refrigeration Mechanics and Construction Millwrights.” Safety Science 144. https://doi.org/10.1016/j.ssci.2021.105468.
  • Chapron, Kévin, Valère Plantevin, Florentin Thullier, Kévin Bouchard, Elise Duchesne, and Sébastien Gaboury. 2018. “A More Efficient Transportable and Scalable System for Real-Time Activities and Exercises Recognition.” Sensors 18 (1): 268. https://doi.org/10.3390/s18010268.
  • Charbuty, Bahzad, and Adnan Abdulazeez. 2021. “Classification Based on Decision Tree Algorithm for Machine Learning.” Journal of Applied Science and Technology Trends 2 (01): 20–28. https://doi.org/10.38094/jastt20165.
  • Ciano, Maria Pia, Patrick Dallasega, Guido Orzes, and Tommaso Rossi. 2021. “One-to-one Relationships Between Industry 4.0 Technologies and Lean Production Techniques: A Multiple Case Study.” International Journal of Production Research 59 (5): 1386–1410. https://doi.org/10.1080/00207543.2020.1821119.
  • Delpla, Victor, Kevin Chapron, Jean-Pierre Kenné, and Lucas Hof. 2022. “Towards Intelligent Manufacturing System Safety Strategies: Generating LockOut/TagOut Sheets by Machine Learning – A Case Study.” IFAC-PapersOnLine 55 (10): 1001–1006. https://doi.org/10.1016/j.ifacol.2022.09.493.
  • Dewi, Luciana Triani. 2018. “Investigation of Lockout / Tagout Procedure Failure in Machine Maintenance Process.” Jurnal Teknik Industri 20 (2): 135–140. https://doi.org/10.9744/jti.20.2.135-140.
  • Dreßler, Kevin, and Axel-Cyrille Ngonga Ngomo. 2017. “On the Efficient Execution of Bounded Jaro-Winkler Distances.” Semantic Web 8: 185–196. https://doi.org/10.3233/SW-150209.
  • Emami-Mehrgani, Behnam, Jean-Pierre Kenné, and Sylvie Nadeau. 2013. “Lockout/Tagout and Optimal Production Control Policies in Failure-Prone non-Homogenous Transfer Lines with Passive Redundancy.” International Journal of Production Research 51 (4): 1006–1023. https://doi.org/10.1080/00207543.2012.662305.
  • Gauthier, François, Yuvin Chinniah, Georges Abdul-Nour, Sabrina Jocelyn, Barthélemy Aucourt, Guy Bordeleau, and Abdallah Ben Mosbah. 2021. “Practices and Needs of Machinery Designers and Manufacturers in Safety of Machinery: An Exploratory Study in the Province of Quebec, Canada.” Safety Science 133: 105011. https://doi.org/10.1016/j.ssci.2020.105011.
  • Ghosh, Surjya, Shivam Goenka, Niloy Ganguly, Bivas Mitra, and Pradipta De. 2019. Representation Learning for Emotion Recognition from Smartphone Keyboard Interactions.
  • Glorot, Xavier, Antoine Bordes, and Yoshua Bengio. 2011. “Deep Sparse Rectifier Neural Networks.” Paper presented at the Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics.
  • Hakimian, Soroosh, Shamim Pourrahimi, and Lucas Hof. 2022. “Application of Machine Learning Algorithms to Classify and Predict Corrosion Behavior of Stainless Steels in Lactic Acid.” Paper presented at the Electrochemical Society Meeting Abstracts 241.
  • Ittoo, Ashwin, Le Minh Nguyen, and Antal van den Bosch. 2016. “Text Analytics in Industry: Challenges, Desiderata and Trends.” Computers in Industry 78: 96–107. https://doi.org/10.1016/j.compind.2015.12.001.
  • Ivanov, Dmitry. 2022. “The Industry 5.0 Framework: Viability-Based Integration of the Resilience, Sustainability, and Human-Centricity Perspectives.” International Journal of Production Research 61: 1–13.
  • Jamwal, Anbesh, Rajeev Agrawal, Monica Sharma, and Antonio Giallanza. 2021. “Industry 4.0 Technologies for Manufacturing Sustainability: A Systematic Review and Future Research Directions.” Applied Sciences 11 (12): 5725. https://doi.org/10.3390/app11125725.
  • Jayaprakash, K., and S. P. Balamurugan. 2022. “Design of Optimal Multilevel Thresholding Based Segmentation with AlexNet Model for Plant Leaf Disease Diagnosis. Paper presented at the 2022 4th International Conference on Smart Systems and Inventive Technology (ICSSIT), 20–22 January 2022.
  • Jindal, Rajni, Ruchika Malhotra, and Abha Jain. 2015. “Techniques for Text Classification: Literature Review and Current Trends.” Webology 12: 1–28.
  • Jivani, Anjali. 2011. “A Comparative Study of Stemming Algorithms.” International Journal of Computer Applications in Technology 2: 1930–1938.
  • Jo, Taeho. 2019. “Text Association.” In Text Mining, edited by Thomas Ditzinger, 59–75. Cham: Springer International Publishing.
  • Jusoh, Shaidah, and Hejab Al Fawareh. 2007. Natural Language Interface for Online Sales Systems.
  • Khanday, Akib Mohi Ud Din, Syed Tanzeel Rabani, Qamar Rayees Khan, Nusrat Rouf, and Masarat Mohi Ud Din. 2020. “Machine Learning Based Approaches for Detecting COVID-19 Using Clinical Text Data.” International Journal of Information Technology 12 (3): 731–739. https://doi.org/10.1007/s41870-020-00495-9.
  • Kulkarni, Akshay, and Adarsha Shivananda. 2021. “Extracting the Data.” In Natural Language Processing Recipes, 1–29. Berkeley, CA: Apress.
  • Kumar, S., and S. M. Tauseef. 2021. “Development of an Internet of Things (IoT) based Lockout/Tagout (LOTO) Device for Accident Prevention in Manufacturing Industries.” IOP Conference Series: Materials Science and Engineering 1017: 012017. https://doi.org/10.1088/1757-899X/1017/1/012017.
  • Kusiak, Andrew. 2018. “Smart Manufacturing.” International Journal of Production Research 56 (1–2): 508–517. https://doi.org/10.1080/00207543.2017.1351644.
  • Leng, Jiewu, Weinan Sha, Baicun Wang, Pai Zheng, Cunbo Zhuang, Qiang Liu, Thorsten Wuest, Dimitris Mourtzis, and Lihui Wang. 2022. “Industry 5.0: Prospect and Retrospect.” Journal of Manufacturing Systems 65: 279–295. https://doi.org/10.1016/j.jmsy.2022.09.017.
  • Li, Jianquan, Xiaokang Liu, Wenpeng Yin, Min Yang, Liqun Ma, and Yaohong Jin. 2021. “Empirical Evaluation of Multi-Task Learning in Deep Neural Networks for Natural Language Processing.” Neural Computing and Applications 33 (9): 4417–4428. https://doi.org/10.1007/s00521-020-05268-w.
  • Liu, Pengfei, Xipeng Qiu, and Xuanjing Huang. 2017. “Adversarial Multi-Task Learning for Text Classification.” arXiv preprint arXiv:1704.05742.
  • Liu, Zimei, Kefan Xie, Ling Li, and Yong Chen. 2020. “A Paradigm of Safety Management in Industry 4.0.” Systems Research and Behavioral Science 37 (4): 632–645. https://doi.org/10.1002/sres.2706.
  • Margherita, Emanuele Gabriel, and Alessio Maria Braccini. 2023. “Industry 4.0 Technologies in Flexible Manufacturing for Sustainable Organizational Value: Reflections from a Multiple Case Study of Italian Manufacturers.” Information Systems Frontiers. https://doi.org/10.1007/s10796-020-10047-y.
  • Memarian, Babak, Sara B. Brooks, Jean Christophe Le, and Jerry E. Rivera. 2022. “High-Risk Electrical Tasks & Contributing Work Factors.” Professional Safety 67 (8): 14–20.
  • Mittal, Sameer, Muztoba Ahmad Khan, Jayant Kishor Purohit, Karan Menon, David Romero, and Thorsten Wuest. 2020. “A Smart Manufacturing Adoption Framework for SMEs.” International Journal of Production Research 58 (5): 1555–1573. https://doi.org/10.1080/00207543.2019.1661540.
  • Mohan, Vijayarani. 2015. “Preprocessing Techniques for Text Mining - An Overview.” International Journal of Computer Science & Communication Networks 5 (1): 7–16.
  • Na, X. U., M. A. Ling, Qing Liu, Wang. Li, and Yongliang Deng. 2021. “An Improved Text Mining Approach to Extract Safety Risk Factors from Construction Accident Reports.” Safety Science 138: 105216. https://doi.org/10.1016/j.ssci.2021.105216.
  • Occupational Safety and Health Administration, OSHA 29 CFR 1910.147. The control of hazardous energy (lockout/ tagout). Occupational Safety and Health Standards. 1989.
  • Ouellet, Maxime. 2022. “Calculating the Process Time Required to Develop Lock Out Tag Out (LOTO) Procedures.” Accessed June 14. https://www.conformit.com/lockout-tagout-procedures-calculating-tool/.
  • Panzer, Marcel, and Benedict Bender. 2022. “Deep Reinforcement Learning in Production Systems: A Systematic Literature Review.” International Journal of Production Research 60 (13): 4316–4341. https://doi.org/10.1080/00207543.2021.1973138.
  • Podgórski, Daniel, Katarzyna Majchrzycka, Anna Dąbrowska, Grzegorz Gralewicz, and Małgorzata Okrasa. 2017. “Towards a Conceptual Framework of OSH Risk Management in Smart Working Environments Based on Smart PPE, Ambient Intelligence and the Internet of Things Technologies.” International Journal of Occupational Safety and Ergonomics 23 (1): 1–20. https://doi.org/10.1080/10803548.2016.1214431.
  • Qiu, XiPeng, TianXiang Sun, YiGe Xu, YunFan Shao, Ning Dai, and XuanJing Huang. 2020. “Pre-trained Models for Natural Language Processing: A Survey.” Science China Technological Sciences 63 (10): 1872–1897. https://doi.org/10.1007/s11431-020-1647-3.
  • Rahimi, Amir, Amirreza Shaban, Ching-An Cheng, Richard Hartley, and Byron Boots. 2020. “Intra Order-Preserving Functions for Calibration of Multi-Class Neural Networks.” Advances in Neural Information Processing Systems 33: 13456–13467.
  • Rai, Rahul, Manoj Kumar Tiwari, Dmitry Ivanov, and Alexandre Dolgui. 2021. “Machine Learning in Manufacturing and Industry 4.0 Applications.” International Journal of Production Research 59 (16): 4773–4778. https://doi.org/10.1080/00207543.2021.1956675.
  • Romero, David, and Johan Stahre. 2021. “Towards the Resilient Operator 5.0: The Future of Work in Smart Resilient Manufacturing Systems.” Procedia CIRP 104: 1089–1094. https://doi.org/10.1016/j.procir.2021.11.183.
  • Rožanec, Jože M., Inna Novalija, Patrik Zajec, Klemen Kenda, Hooman Tavakoli Ghinani, Sungho Suh, Entso Veliou, et al. 2023. “Human-centric Artificial Intelligence Architecture for Industry 5.0 Applications.” International Journal of Production Research, 1–26. https://doi.org/10.1080/00207543.2022.2138611.
  • Ruff, Todd, Patrick Coleman, and Laura Martini. 2011. “Machine-related Injuries in the US Mining Industry and Priorities for Safety Research.” International Journal of Injury Control and Safety Promotion 18 (1): 11–20. https://doi.org/10.1080/17457300.2010.487154.
  • Ruppert, T., and J. Abonyi. 2018. “Industrial Internet of Things Based Cycle Time Control of Assembly Lines.” Paper presented at the 2018 IEEE International Conference on Future IoT Technologies (Future IoT), 18–19 January 2018.
  • Saniuk, Sebastian, Sandra Grabowska, and Bożena Gajdzik. 2020. “Social Expectations and Market Changes in the Context of Developing the Industry 4.0 Concept.” Sustainability 12 (4): 1362. https://doi.org/10.3390/su12041362.
  • Sankarasubramanian, P. 2023. “Protection of Hazardous Places in Industries Using Machine Learning.” Paper presented at the 2023 International Conference on Emerging Smart Computing and Informatics (ESCI), 1–3 March 2023.
  • Sha, Lei, Sujian Li, Baobao Chang, and Zhifang Sui. 2016. Recognizing Textual Entailment via Multi-task Knowledge Assisted LSTM. Vol. 10035.
  • Shinyama, Yusuke. 2014. “Pdfminer. Six.” In. online.
  • Silvestri, Alessandro, Fabio De Felice, and Antonella Petrillo. 2012. “Multi-criteria Risk Analysis to Improve Safety in Manufacturing Systems.” International Journal of Production Research 50 (17): 4806–4821. https://doi.org/10.1080/00207543.2012.657968.
  • Singh, Apoorva, Sriparna Saha, Md Hasanuzzaman, and Kuntal Dey. 2022. “Multitask Learning for Complaint Identification and Sentiment Analysis.” Cognitive Computation 14 (1): 212–227. https://doi.org/10.1007/s12559-021-09844-7.
  • Sokolova, Marina, and Guy Lapalme. 2009. “A Systematic Analysis of Performance Measures for Classification Tasks.” Information Processing & Management 45 (4): 427–437. https://doi.org/10.1016/j.ipm.2009.03.002.
  • Srivastava, Nitish, Geoffrey Hinton, Alex Krizhevsky, Ilya Sutskever, and Ruslan Salakhutdinov. 2014. “Dropout: A Simple way to Prevent Neural Networks from Overfitting.” The Journal of Machine Learning Research 15 (1): 1929–1958.
  • Tanguy, Ludovic, Nikola Tulechki, Assaf Urieli, Eric Hermann, and Céline Raynal. 2016. “Natural Language Processing for Aviation Safety Reports: From Classification to Interactive Analysis.” Computers in Industry 78: 80–95. https://doi.org/10.1016/j.compind.2015.09.005.
  • Yulianto, Muhamad Arief, and Nurhasanah Nurhasanah. 2021. “The Hybrid of Jaro-Winkler and Rabin-Karp Algorithm in Detecting Indonesian Text Similarity.” Jurnal Online Informatika 6 (1): 88–95. https://doi.org/10.15575/join.v6i1.640.
  • Zermane, Abderrahim, Mohd Zahirasri Mohd Tohir, Hanane Zermane, Mohd Rafee Baharudin, and Hamdan Mohamed Yusoff. 2023. “Predicting Fatal Fall from Heights Accidents Using Random Forest Classification Machine Learning Model.” Safety Science 159: 106023. doi:https://doi.org/10.1016/j.ssci.2022.106023.
  • Zhang, Yu, and Qiang Yang. 2022. “A Survey on Multi-Task Learning.” IEEE Transactions on Knowledge and Data Engineering, https://doi.org/10.1109/TKDE.2021.3070203.
  • Zhen, Xingwei, Yinan Ning, Wenjie Du, Yi Huang, and Jan Erik Vinnem. 2023. “An Interpretable and Augmented Machine-Learning Approach for Causation Analysis of Major Accident Risk Indicators in the Offshore Petroleum Industry.” Process Safety and Environmental Protection 173: 922–933. doi:https://doi.org/10.1016/j.psep.2023.03.063.
  • Zhou, Liping, Zhibin Jiang, Na Geng, Yimeng Niu, Feng Cui, Kefei Liu, and Nanshan Qi. 2022. “Production and Operations Management for Intelligent Manufacturing: A Systematic Literature Review.” International Journal of Production Research 60 (2): 808–846. https://doi.org/10.1080/00207543.2021.2017055.

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