[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"detail-sidebar-cat-0-en-105":3,"doc-seo-290596-105":59,"doc-detail-290596-en":130},{"code":4,"msg":5,"data":6},0,"success",[7,13,18,23,28,33,38,43,48,51,55],{"id":8,"doc_module":4,"doc_module_name":9,"category_name":10,"show_sort_weight":11,"slug":12},1,"Document","Story & Novel",90,"story-novel",{"id":14,"doc_module":4,"doc_module_name":9,"category_name":15,"show_sort_weight":16,"slug":17},2,"Literature",80,"literature",{"id":19,"doc_module":4,"doc_module_name":9,"category_name":20,"show_sort_weight":21,"slug":22},4,"Exam",70,"exam",{"id":24,"doc_module":4,"doc_module_name":9,"category_name":25,"show_sort_weight":26,"slug":27},5,"Comic",60,"comic",{"id":29,"doc_module":4,"doc_module_name":9,"category_name":30,"show_sort_weight":31,"slug":32},6,"Technology",50,"technology",{"id":34,"doc_module":4,"doc_module_name":9,"category_name":35,"show_sort_weight":36,"slug":37},7,"Healthcare",40,"healthcare",{"id":39,"doc_module":4,"doc_module_name":9,"category_name":40,"show_sort_weight":41,"slug":42},8,"Research & Report",30,"research-report",{"id":44,"doc_module":4,"doc_module_name":9,"category_name":45,"show_sort_weight":46,"slug":47},9,"Religion & Spirituality",20,"religion-spirituality",{"id":46,"doc_module":4,"doc_module_name":9,"category_name":49,"show_sort_weight":46,"slug":50},"World Cup","world-cup",{"id":52,"doc_module":4,"doc_module_name":9,"category_name":53,"show_sort_weight":52,"slug":54},10,"Lifestyle","lifestyle",{"id":56,"doc_module":4,"doc_module_name":9,"category_name":57,"show_sort_weight":24,"slug":58},19,"General","general",{"code":4,"msg":60,"data":61},"ok",{"site_id":62,"language":63,"slug":64,"title":65,"keywords":66,"description":67,"schema_data":68,"social_meta":123,"head_meta":125,"extra_data":127,"updated_unix":129},105,"en","an-industry-maturity-model-for-implementing-machine-learning-operations-in-manufacturing","An industry maturity model for implementing Machine Learning operations in manufacturing","","The work addresses how the next stage of industrial automation moves toward fully integrating factory automation with Internet of Things and computer-based systems to streamline production, lower costs, and support Zero Defect Manufacturing. It frames Machine Learning Operations (MLOps) as an ML-driven solution that automates product-relevant steps from development to deployment. 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All this seeks to streamline, improve, and increase production at the lowest possible cost and avoid any failure in the creation of the product, following a strategy called “Zero Defect Manufacturing”. Machine Learning Operations (MLOps) provide a ML-based solution to this challenge, promoting the automation of all product-relevant steps, from development to deployment. When integrating different machine learning models within manufacturing operations, it is necessary to understand what functionality is needed and what is expected. This article presents a maturity model that can help companies identify and map their current level of implementation of machine learning models.\u003Cbr>Key words:\u003Cbr>Machine Learning, Manufacturing Execution System, Zero-defect Manufacturing, Manufacturing Operations, CMM, ISA-95, MLOps. |  |\n| --- | --- |\n| 1. Introduction | and is introduced, these algorithms “learn” andoptimise their output to improve performance and |\n| Over four decades ago, Phillip Crosby coined the concept of “zero defects”, a vision that thanks to the | increase their “intelligence” over time (Ongsulee, 2014) . Machine Learning (ML) is a key tool in the |\n| rise of Artificial Intelligence (AI) in manufacturing has become achievable (Escobar et al., 2020). AI can be defined as the process by which, using different | implementation of Zero Defects Manufacturing (ZDM) (Psarommatis et al., 2020) . |\n| techniques, machines can be endowed with cognitive | ZDM is a strategy followed to minimise, mitigate or |\n| capabilities and intellect. Central to this is the concept | eliminate failures and defects during the production |\n| of machine learning (ML) (El-Naqa et al., 2015), | process (Serrano-Ruiz et al., 2021) . It is based |\n| AI can be defined as the process by which, using | on the evidence that they will always exist and |\n| different techniques, machines can be endowed with | will eventually affect production and its output, |\n| cognitive capabilities and intellect. Central to this | but recognising that (i) faults and defects can be |\n| is the concept of machine learning (ML) (Frank et al., 2019) . ML is one of the most essential concepts | detected and minimised more quickly online; (ii) any production output that deviates from specification |\n| for Industry 4.0, which aims to provide analytical | should not be allowed to pass to the next step in |\n| data modelling and outcome prediction (Frank et al., 2019) . ML uses algorithms that receive and | the value chain or, eventually, to an end customer (Lindström et al., 2020) . However, through the |\n| analyse data in real time to predict output values | implementation of ML, the prediction and early |\n| within an acceptable range. As n","cbCaildtoETPeK5J","https://ap.wps.com/l/cbCaildtoETPeK5J","pdf",468119,"English","# Introduction\n## Zero Defects Manufacturing and AI in manufacturing\n## Machine Learning and Industry 4.0 concepts\n## MLOps integration with MES and production lifecycle\n# Proposed maturity model","[{\"question\":\"What problem does the document focus on in manufacturing automation?\",\"answer\":\"It focuses on automating factory elements to streamline production and reduce failures while aligning with the goals of Zero Defect Manufacturing.\"},{\"question\":\"How does the document connect MLOps with manufacturing?\",\"answer\":\"It presents MLOps as an approach that manages the ML model lifecycle and deployment in real time, enabling continuous updating and better production outcomes.\"},{\"question\":\"What is the purpose of the proposed maturity model?\",\"answer\":\"It helps companies identify and map their current level of ML implementation within manufacturing operations.\"}]","An industry maturity model for implementing Machine Learning operations in manufacturing | PDF",1789642154]