[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-126053-en":3,"doc-seo-126053-105":31,"detail-sidebar-cat-0-en-105":92},{"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":21,"is_downloadable":21,"audit_status":21,"page_count":22,"language":23,"language_code":24,"site_id":25,"html_lang":24,"table_of_contents":26,"faqs":27,"seo_title":28,"seo_description":14,"update_tm":29,"read_time":30},126053,962084928904,"Asher","https://ap-avatar.wpscdn.com/davatar_155a257f0dc6eb9ab79c44ca47cae57d",8,"Research & Report","Prediction of Chemical Plants Operating Performances - A Machine Learning Approach","Modern environmental regulations demand rigorous optimization of chemical process operations to cut waste, pollution, and operational risks while maintaining high efficiency. Chemical plants often contain non-linear components, which undermines consolidated tuning and control methods. Time-variant, self-adapting, and ad-hoc control strategies with parameter tuning at both subsystem and system levels may be required, though traditional exact-solution workflows can be computationally expensive. This paper proposes an AI-based method to model a real chemical plant performance: a marine scrubber installed on a Ro-Roship, evaluating machine learning techniques to support real-time, cost-effective optimization of shipping environmental compliance.","Prediction of chemical plants operating performances: a machine learning approach  \nLelio Campanile Luigi Piero Di Bonito Mauro Iacono  \nDipartimento di Matematica e Fisica Universit`a degli Studi della Campania ”L. Vanvitelli”viale Lincoln 5  \n81100, Caserta, Italy  \nFrancesco Di Natale Dipartimento di Ingegneria Chimica, dei Materiali e della Produzione Industriale Universit`a degli Studi di Napoli Federico II Piazzale Vincenzo Tecchio, 80 80125 Napoli, Italy  \nKEYWORDS  \nMarine pollution; Sulphur dioxide absorption; Scrubber; Machine Learning; Chemical engineering.  \nABSTRACT  \nModern environmental regulations require rigorous optimization of operations in process engineering to reduce waste, pollution, and risks while maximizing efficiency. However, the nature of chemical plants, which include components with non-linear behavior, challenges the use of consolidated tuning and control techniques. Instead, ad-hoc, self-adapting, and timevariant controls, with a balanced tuning of parameters at both the subsystem and system level, may be necessary. Needed computing processes may require significant resources and high performance systems, if managed by means of traditional approaches and with exact solution methods. In this regard, domain experts suggest instead the use of integrated techniques based on Artificial Intelligence (AI), which include Explainable AI (XAI) and Trustworthy AI (TAI), which are unique in this industry and still in the early stages of development.  \nTo pave the way for a real-time, cost-effective solution for this problem, this paper proposes an AI-based approach to model the performance of a real chemical plant, i.e. a marine scrubber installed on a Ro-Roship. The study aims to investigate Machine Learning (ML) techniques which can be used to model such processes. Notably, this analysis is the first of its kind, atthe best of the authors’ knowledge. Overall, the study highlights the potential of using ML-based techniques, to optimize environmental compliance in the shipping industry.  \nI. INTRODUCTION  \nModern environmental regulations necessitate rigorous optimization of operations which are involved in process engineering in order to decrease waste, pollution, and risks, as well as maximize the efficiency of each step and sub-system. Managing compli-  \nance requires significant computational efforts and nonnegligible performances to ensure that systems keep all operational parameters within the boundaries that allow a safe evolution of their dynamics, with real-time verification and adjustment of all internal and external variables. Considering chemical processes, the nature of chemical plants, which include non-linear components and could constitute one-of-a-kind elements of a chemical plant, these requirements challenge the consolidated tuning and control techniques and suggests the use of ad-hoc, self-adapting, and time-variant controls, possibly with a balanced tuning of parameters at both the subsystem and the system level.  \nAs the real-time computing operations have to be performed on-site to guarantee that the control loop is closed and timely, the case of processes which happen on ships, without the constant supervision of a full team of IT personnel and with limited assets in a non-friendly environment, with a need for constant monitoring and intervention, suggests a quest for solutions that maybe implemented with reduced devices. Domain experts in the process engineering area suggest the use of integrated techniques based on Artificial Intelligence (AI) or, even more interesting, Explainable (XAI) or Trustworthy AI (TAI), which are unique in this industry and are still in the early stages of development. The use of XAI/TAI techniques is significant for the process safety and the imputation of responsibility in case of failures.  \nShipping transports almost 90% of the world’s commerce annually and is critical to international trade and the global economy. Shipping produces higher sulphur emi","cbCaisXmIyHPn8ht","https://ap.wps.com/l/cbCaisXmIyHPn8ht","pdf",3382651,4,1,7,"English","en",105,"# Introduction\n## Optimization under environmental regulations\n## AI-driven control: XAI and trustworthy AI\n## IMO MARPOL VI limits and marine scrubbers\n## Problem setup and machine learning objective","[{\"question\":\"Why are traditional control and tuning techniques difficult to apply to chemical plants in this context?\",\"answer\":\"Chemical plants include non-linear components and system-specific behaviors, which challenge consolidated tuning and control approaches.\"},{\"question\":\"What real-world system is modeled in the proposed study?\",\"answer\":\"The study models a marine scrubber installed on a Ro-Roship (a cargo ship) and focuses on its performance.\"},{\"question\":\"What is the target variable used for the machine learning modeling?\",\"answer\":\"The target variable is the SO2 (g) scrubber outlet concentration.\"}]","Prediction of Chemical Plants Operating Performances - A Machine Learning Approach | PDF",1785902796,18,{"code":4,"msg":32,"data":33},"ok",{"site_id":25,"language":24,"slug":34,"title":13,"keywords":35,"description":14,"schema_data":36,"social_meta":87,"head_meta":89,"extra_data":91,"updated_unix":29},"prediction-of-chemical-plants-operating-performances-a-machine-learning-approach","",{"@graph":37,"@context":86},[38,54,69],{"@type":39,"itemListElement":40},"BreadcrumbList",[41,45,49,52],{"item":42,"name":43,"@type":44,"position":21},"https://docshare.wps.com","Home","ListItem",{"item":46,"name":47,"@type":44,"position":48},"https://docshare.wps.com/document/","Document",2,{"item":50,"name":12,"@type":44,"position":51},"https://docshare.wps.com/document/research-report/",3,{"item":53,"name":13,"@type":44,"position":20},"https://docshare.wps.com/document/prediction-of-chemical-plants-operating-performances-a-machine-learning-approach/126053/",{"url":53,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":24,"description":14,"dateModified":62,"datePublished":63,"encodingFormat":61,"isAccessibleForFree":64,"interactionStatistic":65},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":42,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-24","2026-08-05",true,{"@type":66,"interactionType":67,"userInteractionCount":20},"InteractionCounter",{"@type":68},"ViewAction",{"@type":70,"mainEntity":71},"FAQPage",[72,78,82],{"name":73,"@type":74,"acceptedAnswer":75},"Why are traditional control and tuning techniques difficult to apply to chemical plants in this context?","Question",{"text":76,"@type":77},"Chemical plants include non-linear components and system-specific behaviors, which challenge consolidated tuning and control approaches.","Answer",{"name":79,"@type":74,"acceptedAnswer":80},"What real-world system is modeled in the proposed study?",{"text":81,"@type":77},"The study models a marine scrubber installed on a Ro-Roship (a cargo ship) and focuses on its performance.",{"name":83,"@type":74,"acceptedAnswer":84},"What is the target variable used for the machine learning modeling?",{"text":85,"@type":77},"The target variable is the SO2 (g) scrubber outlet concentration.","https://schema.org",{"og:url":53,"og:type":88,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":90,"canonical":53},"index,follow",{"doc_id":7,"site_id":25},{"code":4,"msg":5,"data":93},[94,98,102,106,111,116,120,123,128,131,135],{"id":21,"doc_module":4,"doc_module_name":47,"category_name":95,"show_sort_weight":96,"slug":97},"Story & Novel",90,"story-novel",{"id":48,"doc_module":4,"doc_module_name":47,"category_name":99,"show_sort_weight":100,"slug":101},"Literature",80,"literature",{"id":20,"doc_module":4,"doc_module_name":47,"category_name":103,"show_sort_weight":104,"slug":105},"Exam",70,"exam",{"id":107,"doc_module":4,"doc_module_name":47,"category_name":108,"show_sort_weight":109,"slug":110},5,"Comic",60,"comic",{"id":112,"doc_module":4,"doc_module_name":47,"category_name":113,"show_sort_weight":114,"slug":115},6,"Technology",50,"technology",{"id":22,"doc_module":4,"doc_module_name":47,"category_name":117,"show_sort_weight":118,"slug":119},"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":47,"category_name":12,"show_sort_weight":121,"slug":122},30,"research-report",{"id":124,"doc_module":4,"doc_module_name":47,"category_name":125,"show_sort_weight":126,"slug":127},9,"Religion & Spirituality",20,"religion-spirituality",{"id":126,"doc_module":4,"doc_module_name":47,"category_name":129,"show_sort_weight":126,"slug":130},"World Cup","world-cup",{"id":132,"doc_module":4,"doc_module_name":47,"category_name":133,"show_sort_weight":132,"slug":134},10,"Lifestyle","lifestyle",{"id":136,"doc_module":4,"doc_module_name":47,"category_name":137,"show_sort_weight":107,"slug":138},19,"General","general"]