[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"detail-sidebar-cat-1-en-105":3,"doc-seo-240468-105":53,"doc-detail-240468-en":126},{"code":4,"msg":5,"data":6},0,"success",[7,14,19,24,29,34,39,44,49],{"id":8,"doc_module":9,"doc_module_name":10,"category_name":11,"show_sort_weight":12,"slug":13},11,1,"Template","Presentations",90,"presentations",{"id":15,"doc_module":9,"doc_module_name":10,"category_name":16,"show_sort_weight":17,"slug":18},12,"Resumes",80,"resumes",{"id":20,"doc_module":9,"doc_module_name":10,"category_name":21,"show_sort_weight":22,"slug":23},14,"Invoices",70,"invoices",{"id":25,"doc_module":9,"doc_module_name":10,"category_name":26,"show_sort_weight":27,"slug":28},15,"Posters",60,"posters",{"id":30,"doc_module":9,"doc_module_name":10,"category_name":31,"show_sort_weight":32,"slug":33},16,"Social Media",50,"social-media",{"id":35,"doc_module":9,"doc_module_name":10,"category_name":36,"show_sort_weight":37,"slug":38},17,"Forms",40,"forms",{"id":40,"doc_module":9,"doc_module_name":10,"category_name":41,"show_sort_weight":42,"slug":43},18,"Letters",30,"letters",{"id":45,"doc_module":9,"doc_module_name":10,"category_name":46,"show_sort_weight":47,"slug":48},21,"Paper Templates",5,"papers-templates",{"id":50,"doc_module":9,"doc_module_name":10,"category_name":51,"show_sort_weight":4,"slug":52},158,"General","general-158",{"code":4,"msg":54,"data":55},"ok",{"site_id":56,"language":57,"slug":58,"title":59,"keywords":60,"description":61,"schema_data":62,"social_meta":119,"head_meta":121,"extra_data":123,"updated_unix":125},105,"en","a-mixed-initiative-approach-to-computer-aided-process-planning","A Mixed-Initiative Approach to Computer Aided Process Planning","","Several approaches have been proposed for developing intelligent applications in Computer Aided Process Planning (CAPP), from storing historic designs for retrieval to synthesizing process plans generatively. Despite benefits over traditional methods, these approaches often suffer from drawbacks caused by under- and over-automation in decision processes. This paper proposes a mixed-initiative model that combines plan recognition of a user’s intentions with AI planning techniques to synthesize new designs meeting inferred goals, improving usability and usefulness of intelligent assistants.",{"@graph":63,"@context":118},[64,80,101],{"@type":65,"itemListElement":66},"BreadcrumbList",[67,71,74,77],{"item":68,"name":69,"@type":70,"position":9},"https://docshare.wps.com","Home","ListItem",{"item":72,"name":10,"@type":70,"position":73},"https://docshare.wps.com/template/",2,{"item":75,"name":51,"@type":70,"position":76},"https://docshare.wps.com/template/general/",3,{"item":78,"name":59,"@type":70,"position":79},"https://docshare.wps.com/template/a-mixed-initiative-approach-to-computer-aided-process-planning/240468/",4,{"url":78,"name":59,"@type":81,"image":82,"author":87,"headline":59,"publisher":90,"fileFormat":93,"inLanguage":57,"description":61,"dateModified":94,"datePublished":95,"encodingFormat":93,"isAccessibleForFree":96,"interactionStatistic":97},"DigitalDocument",{"url":83,"@type":84,"width":85,"height":86},"https://docshare.wps.com/thumbnails/a-mixed-initiative-approach-to-computer-aided-process-planning/240468.png","ImageObject",442,249,{"name":88,"@type":89},"Aria Callaghan","Person",{"url":68,"name":91,"@type":92},"DocShare","Organization","application/pdf","2026-09-25","2026-09-11",true,{"@type":98,"interactionType":99,"userInteractionCount":79},"InteractionCounter",{"@type":100},"ViewAction",{"@type":102,"mainEntity":103},"FAQPage",[104,110,114],{"name":105,"@type":106,"acceptedAnswer":107},"What is the main problem addressed in existing CAPP approaches?","Question",{"text":108,"@type":109},"Existing CAPP approaches can suffer from drawbacks due to under- and over-automation of decision processes during planning.","Answer",{"name":111,"@type":106,"acceptedAnswer":112},"How does the proposed mixed-initiative model improve CAPP systems?",{"text":113,"@type":109},"It integrates plan recognition of the user’s intentions with AI planning techniques to synthesize new designs that fulfill the planner’s inferred intentions.",{"name":115,"@type":106,"acceptedAnswer":116},"What distinguishes variant CAPP from generative CAPP?",{"text":117,"@type":109},"Variant CAPP uses standard process plan templates based on Group Technology, while generative CAPP uses feature models and rule sets to synthesize process plans automatically.","https://schema.org",{"og:url":78,"og:type":120,"og:title":59,"og:site_name":91,"og:description":61},"article",{"robots":122,"canonical":78},"index,follow",{"doc_id":124,"site_id":56},240468,1789161832,{"code":4,"msg":5,"data":127},{"doc_id":124,"user_id":128,"nickname":88,"user_avatar":129,"doc_module":9,"category_id":50,"category_name":51,"doc_title":59,"doc_description":61,"doc_content":130,"file_id":131,"file_url":132,"file_type":133,"file_size":134,"view_count":79,"is_deleted":4,"is_public":9,"is_downloadable":9,"audit_status":9,"page_count":15,"language":135,"language_code":57,"site_id":56,"html_lang":57,"table_of_contents":136,"faqs":137,"seo_title":138,"seo_description":61,"update_tm":125,"read_time":79},962084926284,"https://ap-avatar.wpscdn.com/davatar_29158cc5080c5b710cf443261637dec0","A Mixed-Initiative Approach to Computer Aided Process Planning  \nMartn G. Marchetta 􀀃  \nFacultad de Ingenier´ıa, Universidad Nacional de Cuyo  \nMendoza, Centro Universitario-5500, Argentina  \nmmarchetta@fi[ng.uncu.edu.ar](ng.uncu.edu.ar)  \nand  \nRaymundo Q. Forradellas  \nFacultad de Ingenier´ıa, Universidad Nacional de Cuyo  \nMendoza, Centro Universitario-5500, Argentina  \n[kike@uncu.edu.ar](kike@uncu.edu.ar)  \nAbstract  \nSeveral approaches have been proposed in order to develop intelligent applications on Computer Aided Process Planning (CAPP) domain. These approaches range from historic designs storage for later recovery, to generative synthesis of process plans. Although these approaches present advantages over traditional methods, they have several drawbacks derived specially from the under and over-automation of the decision processes. In this paper a mixed-initiative model for CAPP systems is proposed, that integrates plan recognition of user’s intentions, with planning techniques in the context of artificial intelligence, in order to synthesize new designs that fulfill process planner’s inferred intentions, thus improving the usability and usefulness of such intelligent assistants.  \nKeywords: Computer Aided Process Planning, Mixed-Initiative System, Planning, Intelligent Agent  \n1 INTRODUCTION  \nIn the manufacturing context, process planning is the definition of manufacturing and assembly operations needed to produce the different parts, along with the machines, tools and fixturing required for these tasks [8] . Parts need to go through a set of manufacturing processes in order to be produced. This set of manufacturing processes is a process plan. Each manufacturing process within a process plan can be performed by machines of some type or family, and also requires certain type of tools. Besides, each part has its own Bill Of Materials (BOM) . The BOM of a part to be manufactured is the set of raw materials and intermediate products, needed by each manufacturing process in the corresponding process plan in order to produce the part.  \nManual process planning is an intense and time consuming activity. Besides, the quality of its results is very dependant on process planner’s experience. The characteristics above mentioned yield the need of computer support to process planning activities. There are basically two approaches to CAPP, although there exist others that are special cases of these. The first one is called variant CAPP. This approach makes use of the concept of Group Technology (GT), in which parts with similar  \n􀀃 CONICET PhD fellow  \nfeatures are grouped together. Then, a standard process plan is created for each group and is stored as a process plan template. When a manufacturing engineer is creating a process plan for a new part, he can retrieve the design template of the part’s group, and adapt this standard process plan to the specific case he is working on.  \nThe second approach for incorporating computer assistance to process planning, is called generative CAPP. This approach uses knowledge based systems, since the parts to be manufactured are described as a feature model. A feature model is a formal description of a part, that contains features and values for these features. Having an “open” description of a part to be manufactured, the manufacturing processes, the capabilities of machines and tools and a rule set indicating which process should be used to produce each feature value, the automatic synthesis of new design processes can be achieved.  \nThe two mentioned approaches to CAPP have some drawbacks. On the one hand, variant CAPP does not assist process planners while they adapt the part family process plan template, to the case of the specific part they are working on. Besides, the manufacturing engineer must be conscious of the existence of a process plan template for that particular part’s family, and needs to know which is the corresponding family in order to retrieve the correct process plan template","cbCaipGmG3loVmD0","https://ap.wps.com/l/cbCaipGmG3loVmD0","pdf",356229,"English","# 1 Introduction\n## Manufacturing context and process planning basics\n## Two main CAPP approaches: variant and generative\n## Limitations of existing approaches\n## Motivation for a mixed-initiative model","[{\"question\":\"What is the main problem addressed in existing CAPP approaches?\",\"answer\":\"Existing CAPP approaches can suffer from drawbacks due to under- and over-automation of decision processes during planning.\"},{\"question\":\"How does the proposed mixed-initiative model improve CAPP systems?\",\"answer\":\"It integrates plan recognition of the user’s intentions with AI planning techniques to synthesize new designs that fulfill the planner’s inferred intentions.\"},{\"question\":\"What distinguishes variant CAPP from generative CAPP?\",\"answer\":\"Variant CAPP uses standard process plan templates based on Group Technology, while generative CAPP uses feature models and rule sets to synthesize process plans automatically.\"}]","A Mixed-Initiative Approach to Computer Aided Process Planning | PDF"]