[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-120629-en":3,"doc-seo-120629-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":20,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},120629,7971461741311,"Ophelia","https://ap-avatar.wpscdn.com/avatar/74000253aff267980c6?x-image-process=image/resize,m_fixed,w_180,h_180&k=1779345379180704826",8,"Research & Report","POWER CONSUMPTION PREDICTION IN SMART MANUFACTURING USING MACHINE LEARNING - Master’s Thesis","In industrial environments, real-time fault detection is essential for minimizing equipment failures, safeguarding personnel, and optimizing operational efficiency. This thesis applies machine learning (ML) regression models to estimate power consumption during the roll testing phase of paper machine operations. By presenting estimated power trends alongside actual consumption, operators can rapidly respond when deviations arise, helping prevent hazardous events such as fires and reducing risks of asset loss and financial damage. The work uses operational parameters including speed, temperature, and pressure to support real-time estimation and anomaly identification.","Ali Abdelsalam  \nPOWER CONSUMPTION PREDICTION IN SMART MANUFACTURING USING MACHINE LEARNING  \nFaculty of Information Technology and Communication Sciences (ITC) Master’s Thesis  \nSupervisors/Examiners: Prof. Moncef Gabbouj Dr. Fahad Sohrab  \nDecember 2025  \ni  \nAbstract  \nAli Abdelsalam: POWER CONSUMPTION PREDICTION IN SMART MANUFACTURING USING MACHINE LEARNING  \nMaster’s Thesis Tampere University  \nMaster of Science (Technology) in Computing Sciences Specialization: Signal Processing and Machine Learning December 2025  \nIn industrial environments, real-time fault detection is essential for minimizing equipment failures, safeguarding personnel, and optimizing operational efficiency. This thesis examines the application of machine learning (ML) regression models to estimate power consumption during the critical roll testing phase of paper machine operations. The estimated power trend is displayed alongside the actual consumption, enabling operators to make rapid decisions when significant deviations occur which can potentially prevent hazardous events such as fires and mitigating the risk of asset loss and financial damage.  \nThe research was motivated by an increasing demand for intelligent monitoring systems capable of enhancing fault detection capabilities. Leveraging key operational parameters including speed, temperature, and pressure, the study investigates the effectiveness of ML regression models in estimating power consumption in real time and identifying anomalous patterns indicative of system faults.  \nThis investigation is guided by three primary research questions: the accuracy of machine learning-based power estimation, the comparative performance of different regression algorithms based on quantitative, qualitative, and business defined measures, and their computational suitability for real-time deployment. By integrating predictive analytics into the roll-testing workflow, this thesis demonstrateshow intelligent systems can complement traditional monitoring approaches, reduce reliance on manual oversight, and enhance both safety and operational resilience. The findings contribute to the broader initiative of digital transformation in industrial environments, offering actionable insights into data-driven fault detection methodologies.  \nKeywords: M.Sc. thesis, Machine Learning, Regression, Fault Detection.  \nThe originality of this thesis has been checked using the Turnitin Originality Check service.  \nii  \nUse of Artificial Intelligence in This Work  \nArtificial Intelligence (AI) has been utilized in the preparation of this thesis:  \n⊠ Yes  \n□ No  \nI hereby declare, that the AI-based applications used in generating this work areas follows:  \n\n| Application | Version |\n| --- | --- |\n| Microsoft Copilot | GPT-4 architecture |\n\nPurpose of the Use of AI  \nThe AI was used in this thesis work in brainstorming, generating ideas, Overleaf code, and suggesting linguistic synonyms. Parts of this work, where AI was used AI has helped in generating ideas in Chapter 2 and Chapter 3 . Furthermore, it assisted for suggesting linguistic synonyms, it has been used in re-writing parts of the thesis more professionally except for the Abstract.  \nAcknowledgement of risks  \nI hereby acknowledge, that as the author of this work, I am fully responsible for the contents presented in this thesis. This includes the parts that were generated by an AI, in part or in their entirety. I therefore also acknowledge my responsibility in the case, where use of AI has resulted in ethical guidelines being breached  \niii  \nPreface  \nI would like to express my sincere gratitude to my family for their unwavering support and encouragement throughout this journey. Their belief in me has been a constant source of strength and motivation.  \nI am deeply thankful to Tampere University and Valmet for offering me the opportunity to explore and apply advanced technologies in industrial environments. This experience has not only contributed to the success of the","cbCaie0Bfj3uhPCQ","https://ap.wps.com/l/cbCaie0Bfj3uhPCQ","pdf",10575724,1,72,"English","en",105,"# Contents\n## Introduction\n## Background","[{\"question\":\"What problem does the thesis address in smart manufacturing?\",\"answer\":\"It addresses the need for real-time fault detection by estimating power consumption during the roll testing phase of paper machine operations.\"},{\"question\":\"Which machine learning approach is used for power consumption estimation?\",\"answer\":\"The thesis uses ML regression models to estimate power consumption and identify anomalous patterns that may indicate system faults.\"},{\"question\":\"What operational parameters does the study leverage?\",\"answer\":\"It leverages key operational parameters including speed, temperature, and pressure to model and estimate power consumption in real time.\"}]","POWER CONSUMPTION PREDICTION IN SMART MANUFACTURING USING MACHINE LEARNING - Master’s Thesis | PDF",1785730985,181,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":86,"head_meta":88,"extra_data":90,"updated_unix":28},"power-consumption-prediction-in-smart-manufacturing-using-machine-learning-masters-thesis","",{"@graph":36,"@context":85},[37,54,68],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/power-consumption-prediction-in-smart-manufacturing-using-machine-learning-masters-thesis/120629/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":62,"encodingFormat":61,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-03",true,{"@type":65,"interactionType":66,"userInteractionCount":20},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"What problem does the thesis address in smart manufacturing?","Question",{"text":75,"@type":76},"It addresses the need for real-time fault detection by estimating power consumption during the roll testing phase of paper machine operations.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"Which machine learning approach is used for power consumption estimation?",{"text":80,"@type":76},"The thesis uses ML regression models to estimate power consumption and identify anomalous patterns that may indicate system faults.",{"name":82,"@type":73,"acceptedAnswer":83},"What operational parameters does the study leverage?",{"text":84,"@type":76},"It leverages key operational parameters including speed, temperature, and pressure to model and estimate power consumption in real time.","https://schema.org",{"og:url":52,"og:type":87,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":89,"canonical":52},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":92},[93,97,101,105,110,115,120,123,128,131,135],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":94,"show_sort_weight":95,"slug":96},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":98,"show_sort_weight":99,"slug":100},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":46,"category_name":102,"show_sort_weight":103,"slug":104},"Exam",70,"exam",{"id":106,"doc_module":4,"doc_module_name":46,"category_name":107,"show_sort_weight":108,"slug":109},5,"Comic",60,"comic",{"id":111,"doc_module":4,"doc_module_name":46,"category_name":112,"show_sort_weight":113,"slug":114},6,"Technology",50,"technology",{"id":116,"doc_module":4,"doc_module_name":46,"category_name":117,"show_sort_weight":118,"slug":119},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":121,"slug":122},30,"research-report",{"id":124,"doc_module":4,"doc_module_name":46,"category_name":125,"show_sort_weight":126,"slug":127},9,"Religion & Spirituality",20,"religion-spirituality",{"id":126,"doc_module":4,"doc_module_name":46,"category_name":129,"show_sort_weight":126,"slug":130},"World Cup","world-cup",{"id":132,"doc_module":4,"doc_module_name":46,"category_name":133,"show_sort_weight":132,"slug":134},10,"Lifestyle","lifestyle",{"id":136,"doc_module":4,"doc_module_name":46,"category_name":137,"show_sort_weight":106,"slug":138},19,"General","general"]