[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-31797":3,"doc-seo-31797":27},{"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,"file_id":15,"file_url":16,"file_type":17,"file_size":18,"view_count":4,"is_deleted":4,"is_public":19,"is_downloadable":19,"audit_status":19,"page_count":20,"language":21,"language_code":22,"table_of_contents":23,"faqs":24,"seo_title":13,"seo_description":14,"update_tm":25,"read_time":26},31797,549758146520,"Patrick","https://ap-avatar.wpscdn.com/avatar/80002397d8c0411e94?_k=1775819394049821470",8,"Research & Report","A Hybrid Process Mining and Statistical Process Control Approach for Enhanced Transition Loss Identification in Cosmetic Manufacturing","Transition loss in cosmetic manufacturing denotes hidden inefficiencies occurring between production activities, including idle time, repeated steps, and uneven durations that traditional monitoring often overlooks. A hybrid method combining process mining and statistical process control (SPC) analyzes real production event logs from PT XYZ to detect, quantify, and interpret workflow delays. Process mining reveals sequence deviations such as self-loops, unauthorized activities, and unstable transitions, while SPC assesses variation and stability in recurring tasks. Findings show 408+ hours of undocumented idle time and instability in critical preparation stages for 50 ml and 100 ml lines, totaling about 12% of recorded production hours.","cbCaibZvpbWtZxNE","https://ap.wps.com/l/cbCaibZvpbWtZxNE","pdf",1524608,1,6,"English","en","# Introduction\n## Manufacturing efficiency and transition losses\n## Limits of traditional monitoring\n## Hybrid rationale: process mining + SPC\n# Literature Review\n## Transition loss in cosmetic manufacturing\n## Process mining as a diagnostic tool","[{\"question\":\"What key results were found from PT XYZ event logs?\",\"answer\":\"The study identified 408+ hours of undocumented idle time, frequent repeated machine cleaning, and unstable performance in critical preparation stages affecting transitions for 50 ml and 100 ml product sizes, representing about 12% of recorded production hours.\"}]",1780174826,15,{"code":4,"msg":28,"data":29},"ok",{"site_id":30,"language":22,"slug":31,"title":13,"keywords":32,"description":14,"schema_data":33,"social_meta":76,"head_meta":78,"extra_data":80,"updated_unix":25},105,"a-hybrid-process-mining-and-statistical-process-control-approach-for-enhanced-transition-loss-identification-in-cosmetic-manufacturing","",{"@graph":34,"@context":75},[35,52,66],{"@type":36,"itemListElement":37},"BreadcrumbList",[38,42,46,49],{"item":39,"name":40,"@type":41,"position":19},"https://docshare.wps.com","Home","ListItem",{"item":43,"name":44,"@type":41,"position":45},"https://docshare.wps.com/document/","Document",2,{"item":47,"name":12,"@type":41,"position":48},"https://docshare.wps.com/document/research-report/",3,{"item":50,"name":13,"@type":41,"position":51},"https://docshare.wps.com/document/a-hybrid-process-mining-and-statistical-process-control-approach-for-enhanced-transition-loss-identification-in-cosmetic-manufacturing/31797/",4,{"url":50,"name":13,"@type":53,"author":54,"headline":13,"publisher":56,"fileFormat":59,"description":14,"dateModified":60,"datePublished":60,"encodingFormat":59,"isAccessibleForFree":61,"interactionStatistic":62},"DigitalDocument",{"name":9,"@type":55},"Person",{"url":39,"name":57,"@type":58},"DocShare","Organization","application/pdf","2026-05-30",true,{"@type":63,"interactionType":64,"userInteractionCount":4},"InteractionCounter",{"@type":65},"ViewAction",{"@type":67,"mainEntity":68},"FAQPage",[69],{"name":70,"@type":71,"acceptedAnswer":72},"What key results were found from PT XYZ event logs?","Question",{"text":73,"@type":74},"The study identified 408+ hours of undocumented idle time, frequent repeated machine cleaning, and unstable performance in critical preparation stages affecting transitions for 50 ml and 100 ml product sizes, representing about 12% of recorded production hours.","Answer","https://schema.org",{"og:url":50,"og:type":77,"og:title":13,"og:site_name":57,"og:description":14},"article",{"robots":79,"canonical":50},"index,follow",{"doc_id":7,"site_id":30}]