[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-126130-en":3,"doc-seo-126130-105":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},126130,5909887254083,"Miles","https://ap-avatar.wpscdn.com/davatar_276721f389ce27ea32af1340a28f341c",8,"Research & Report","RECIPROCAL HUMAN-MACHINE LEARNING IN MANUFACTURING - Dissertation","Global manufacturing faces accelerating digital transformation alongside labor skill shortages, creating pressure for learning systems that can keep workers productive while they upskill. Reciprocal human-machine learning (RHML) is presented as a hybrid-intelligence approach drawing on analogies between human learning and AI learning. RHML enables bidirectional, interaction-based learning where humans and machines contribute strengths, combining HITL-ML and CITL learning to support manufacturing work-integrated learning. The work clarifies RHML via systematic review, builds a theory artifact with framework and taxonomy, derives design principles, and evaluates them through focus groups and simulations.","DISSERTATION  \nRECIPROCAL  \nHUMAN-MACHINE LEARNING IN MANUFACTURING  \ncarried out for the purpose of obtaining the degree ofDoctor technicae (Dr. techn.),  \nsubmitted at TU Wien  \nFaculty of Mechanical and Industrial Engineering  \nby  \nDipl.-Ing. Steffen Nixdorf  \nMatr.Nr. 01225457  \nunder the supervision ofUniv.-Prof. Dr.-Ing. Fazel Ansari  \nInstitute of Management Science, E330, Research Group of Production and Maintenance Management  \nReviewed by Prof. József Váncza  \nBudapest University of Technology and Economics, Department of Manufacturing Science and Technology  \nand Prof. Erwin Rauch  \nFree University of Bozen-Bolzano, Professor for Smart and Sustainable Manufacturing, Faculty of Engineering  \nPlace, Date Signature  \nThe secret is there is no secret.  \nMike Tomlin  \nAFFIDAVIT  \nIdeclare in lieu of oath, that I wrote this thesis and carried out the associated research myself,  \nusing only the literature cited in this volume. If text passages from sources are used literally, they are marked as such.  \nIconfirm that this work is original and has not been submitted for examination elsewhere, nor is it currently under consideration for a thesis elsewhere.  \nI acknowledge that the submitted work will be checked electronically-technically using suitable and state-of-the-art means (plagiarism detection software). On the one hand, this ensures that the submitted work was prepared according to the high-quality standards within the applicable rules to ensure good scientific practice „Code ofConduct“ at the TU Wien. On the other hand, a comparison with other student theses avoids violations of my personal copyright.  \nPlace & Date Signature  \nACKNOWLEDGEMENTS  \nABSTRACT  \ns the global economy experiences an era of digital transformation, skill shortages in the labor  \nAinnovmarativkeetsolare chutionsalletonbgingridgieduhestgraieps wbetldwieen aeai. lThabils shore skillaganedundersmarkeores thedemandurgInentresnpeedonsefro  \nthis pressing challenge, the novel concept of reciprocal human-machine learning (RHML) is emerging as apromising concept. Inspired by the symbiotic relationship between humans and machines, RHML recognizes the analogy between human learning processes and those ofAI systems as an integration towards hybrid intelligence. RHML describes a bidirectional learning process encompassing human learning and machine learning in human-machine interaction. At its core, RHML envisions a cooperation in which both agents can contribute their strengths to performing tasks and ultimately trigger learning for both agents. RHML is thus understood as an integration of human-in-the-loop machine learning (HITL-ML) and computer-in-the-loop (CITL) learning. In this way, RHML is believed to enhance assistance of workers in manufacturing by means of extending capabilities of assistance systems, in particular learning assistance systems, and enable work-integrated learning. In fact, RHML is not yet defined in a way that it projects uniform understanding, nor a comprehensive analysis of a state ofthe art exists. Naturally, design knowledge for building RHML is scarce. Hence, this work aims to bring RHML into practice by means ofa design science research project. This work contributes to the clarification of the concept ofRHML by providing an analysis of the state ofthe art by means ofa systematic literature review (cf. Chapter 3).  \nFurther, this work contributes a theory artifact of RHML, encompassing a framework to clarify what it is and what it is not and a taxonomy of design instantiations, as well as a classification of archetypes ofRHML (cf. Chapter 4). This work derives design knowledge for RHML from its theoretical foundation in form of design principles of RHML to transfer RHML into practice. Design principles ofRHML are further instantiated in a software artifact, i.e. , a proofof-concept (PoC) demonstrator. The software artifact is based on an interactive conversational agent incorporating communication, feedback mechanisms, as","cbCaiujzXEvDNfZe","https://ap.wps.com/l/cbCaiujzXEvDNfZe","pdf",4006059,3,1,137,"English","en",105,"# Abstract\n## Concept of RHML and problem background\n## Research contributions and artifacts\n## Design principles and software PoC\n## Evaluation approach and results\n## Practical implications","[{\"question\":\"What is reciprocal human-machine learning (RHML) in manufacturing?\",\"answer\":\"RHML is a bidirectional learning concept where human learning and machine learning co-occur in human-machine interaction. It aims to let both agents contribute their strengths and trigger learning for both sides.\"},{\"question\":\"What research outputs does the thesis provide for RHML?\",\"answer\":\"The work clarifies the concept through a systematic literature review and develops a theory artifact including a framework, a taxonomy of design instantiations, and classification of RHML archetypes.\"},{\"question\":\"How is the proposed RHML approach evaluated?\",\"answer\":\"Design principles are instantiated in a software proof-of-concept using an interactive conversational agent, then evaluated in two cycles: focus group analysis with practitioners and a simulation study in corrective maintenance with novice and expert participants.\"}]","RECIPROCAL HUMAN-MACHINE LEARNING IN MANUFACTURING - Dissertation | PDF",1785903323,345,{"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},"reciprocal-human-machine-learning-in-manufacturing-dissertation","",{"@graph":37,"@context":86},[38,54,69],{"@type":39,"itemListElement":40},"BreadcrumbList",[41,45,49,51],{"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":20},"https://docshare.wps.com/document/research-report/",{"item":52,"name":13,"@type":44,"position":53},"https://docshare.wps.com/document/reciprocal-human-machine-learning-in-manufacturing-dissertation/126130/",4,{"url":52,"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","2026-08-23","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},"What is reciprocal human-machine learning (RHML) in manufacturing?","Question",{"text":76,"@type":77},"RHML is a bidirectional learning concept where human learning and machine learning co-occur in human-machine interaction. It aims to let both agents contribute their strengths and trigger learning for both sides.","Answer",{"name":79,"@type":74,"acceptedAnswer":80},"What research outputs does the thesis provide for RHML?",{"text":81,"@type":77},"The work clarifies the concept through a systematic literature review and develops a theory artifact including a framework, a taxonomy of design instantiations, and classification of RHML archetypes.",{"name":83,"@type":74,"acceptedAnswer":84},"How is the proposed RHML approach evaluated?",{"text":85,"@type":77},"Design principles are instantiated in a software proof-of-concept using an interactive conversational agent, then evaluated in two cycles: focus group analysis with practitioners and a simulation study in corrective maintenance with novice and expert participants.","https://schema.org",{"og:url":52,"og:type":88,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":90,"canonical":52},"index,follow",{"doc_id":7,"site_id":25},{"code":4,"msg":5,"data":93},[94,98,102,106,111,116,121,124,129,132,136],{"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":53,"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":117,"doc_module":4,"doc_module_name":47,"category_name":118,"show_sort_weight":119,"slug":120},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":47,"category_name":12,"show_sort_weight":122,"slug":123},30,"research-report",{"id":125,"doc_module":4,"doc_module_name":47,"category_name":126,"show_sort_weight":127,"slug":128},9,"Religion & Spirituality",20,"religion-spirituality",{"id":127,"doc_module":4,"doc_module_name":47,"category_name":130,"show_sort_weight":127,"slug":131},"World Cup","world-cup",{"id":133,"doc_module":4,"doc_module_name":47,"category_name":134,"show_sort_weight":133,"slug":135},10,"Lifestyle","lifestyle",{"id":137,"doc_module":4,"doc_module_name":47,"category_name":138,"show_sort_weight":107,"slug":139},19,"General","general"]