[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"detail-sidebar-cat-1-en-105":3,"doc-seo-563316-105":53,"doc-detail-563316-en":127},{"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":120,"head_meta":122,"extra_data":124,"updated_unix":126},105,"en","statistical-process-control-chart-spc-in-ipc","Statistical Process Control Chart (SPC) In IPC","","Content explains Statistical Process Control (SPC) using Shewhart control charts for monitoring process performance in IPC. It covers historical development by Walter Shewhart and later expansion through W. Edwards Deming, then describes key control-chart elements: central line, upper and lower control limits using ±3 sigma, and sigma levels. The material distinguishes variable versus attribute control charts (X-bar/S, np/p, c/u) and links each chart type to data measurement/counting and distribution assumptions (normal, binomial, Poisson, geometric). It also references distribution verification via histograms and goodness-of-fit tests, plus formula links.",{"@graph":63,"@context":119},[64,80,102],{"@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":11,"@type":70,"position":76},"https://docshare.wps.com/template/presentations/",3,{"item":78,"name":59,"@type":70,"position":79},"https://docshare.wps.com/template/statistical-process-control-chart-spc-in-ipc/563316/",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/statistical-process-control-chart-spc-in-ipc/563316.png","ImageObject",442,249,{"name":88,"@type":89},"Rhys","Person",{"url":68,"name":91,"@type":92},"DocShare","Organization","application/pdf","2026-10-22","2026-10-12",true,{"@type":98,"interactionType":99,"userInteractionCount":101},"InteractionCounter",{"@type":100},"ViewAction",8,{"@type":103,"mainEntity":104},"FAQPage",[105,111,115],{"name":106,"@type":107,"acceptedAnswer":108},"What is an SPC control chart used for in IPC?","Question",{"text":109,"@type":110},"It is used as a statistical tool to monitor process behavior and assess process success and improvement in IPC.","Answer",{"name":112,"@type":107,"acceptedAnswer":113},"What do the central line and control limits represent in a control chart?",{"text":114,"@type":110},"The central line reflects the average value, while the upper and lower control limits are set using ±3 sigma to indicate typical variation.",{"name":116,"@type":107,"acceptedAnswer":117},"How do you choose between variable and attribute control charts?",{"text":118,"@type":110},"Use variable charts (X-bar and S) for continuous data following a normal distribution, and attribute charts (np/p or c/u) for discrete counted data matched to binomial or Poisson distributions.","https://schema.org",{"og:url":78,"og:type":121,"og:title":59,"og:site_name":91,"og:description":61},"article",{"robots":123,"canonical":78},"index,follow",{"doc_id":125,"site_id":56},563316,1792033525,{"code":4,"msg":5,"data":128},{"doc_id":125,"user_id":129,"nickname":88,"user_avatar":130,"doc_module":9,"category_id":8,"category_name":11,"doc_title":59,"doc_description":61,"doc_content":131,"file_id":132,"file_url":133,"file_type":134,"file_size":135,"view_count":101,"is_deleted":4,"is_public":9,"is_downloadable":9,"audit_status":9,"page_count":136,"language":137,"language_code":57,"site_id":56,"html_lang":57,"table_of_contents":138,"faqs":139,"seo_title":140,"seo_description":61,"update_tm":141,"read_time":142},687207024643,"https://ap-avatar.wpscdn.com/davatar_3d24733baf745e90a7e4bdd5f77d97b2","Statistical Process Control Chart (SPC) In IPC  \nอ.ดร.เพ็ญนภา อุ่นสนิทโรงเรียนพยาบาลรามาธิบดี  \nคณะแพทยศาสตร์โรงพยาบาลรามาธิบดีมหาวิทยาลัยมหิดล  \nประชุมวิชาการ IC Rama Re-union 2022: 2 ส.ค. 65  \nControl Charts  \n-Control charts or Shewhart charts or process-behavior charts .  \n-Control charts are a statistical process control tool.  \n-Developed by Dr. Walter Shewhart in the 1920’s  \n-Expanded by Dr. W. Edwards Deming, who introduced SPC to Japanese industry after WWII.  \nบ่ งชี&ปัญหาในกระบวนการ ประเ มิ นความ สําเร็จ และ พัฒนา ต่ อ  \nControl Charts  \nมีเส้นกราฟที,สําคัญ▪ อัตราการ ติ ดเ ชื7 อ  \n4 เ ส้ น  \n▪ ค่ าเฉลี,ย (central line)  \n▪ Upper control limit ปก ติใ ช้ +3 sigma  \n▪ Lower control limit ปก ติใ ช้ -3 sigma  \nA  \nB  \nC  \nC  \nB  \nA  \n+1 Sigma  \n-1 Sigma  \n+3 Sigma  \n+2 Sigma  \n-2 Sigma  \n-3 Sigma  \nแผนภูมิควบคุมของ Shewhart  \nControl Charts  \nTypes of Control Charts  \ncontrol charts fall into oneof two categories:  \n• Variable control charts plot measurable process data in a time-ordered sequence . (X-bar and S chart)  \n• Attribute control charts plot data that is counted instead of being measured. (np/p/c/u chart)  \nControl Charts  \n• np or a p control chart should be used when analyzing discrete data that should be distributed according to a  \nbinomial distribution  \n• c or u control chart should be used when analyzing count data that should be distributed according to a Poisson distribution  \n• X-bar and S chart should be used together for continuous data that should be distributed according to a normal distribution.  \ng chart  \n▪ ใช้กบัข้อมูลที.มีการกระจายแบบเรขาคณิ ต(geometric distribution)  \n▪ ใช้กรณีที.มีจํานวนเห ตุการณ์เกิ ดขึDนน้อย  \n▪ การสร้างกราฟใช้จานวนระหว่างเห ตุการณ์ (plot  \n.  \ncount between events) ซึงอาจเป็นจํานวนผู้ป่วย หรือจํานวนเวลาระหว่างเห ตุการณ์ที. สนใจ  \nประเภทของข้อมูล  \nnominal scales /ordinal scales interval scales / ratio scales  \nverify the type of distribution  \n-plot histograms  \n-mathematical ‘goodness-of-fit’ tests.  \nสูตรการคํานวณ  \n[https://www.dimins.com/online-help/prodiver_help/Content/ProDiver/control](https://www.dimins.com/online-help/prodiver_help/Content/ProDiver/control)- chart-formulas.html  \nLinks การคํานวณ Control charts ในแต่ละประเภทของ Charts  \nControl Charts  \nxbar chart หรือ s chart ▪ ใช้วิ เคราะห์ข้อมูลที) เป็นข้อมูลชนิดต่อเนือง (Continous  \n)  \ndata) และมีการกระจายเป็นแบบ Normal distribution  \nControl Charts  \nnp chart หรือ p chart  \n▪ ใช้วิ เคราะห์ข้อมูลที) เป็นข้อมูลชนิดไม่ต่อเนื) อง (discrete data) และมีการกระจายเป็นแบบ binomial distribution  \n▪ ผลที) เกิ ดขึ/นเป็นไปได้เพียงสองอย่าง ติดเชื/อหรือไม่ติ ดเชื/อ ป่วยหรือไม่ป่วย และใช่หรือไม่ใช่ เป็นต้น  \n▪ การกระทําแต่ละครั/งเป็นอิสระจากกัน เช่น เพศชายหรือหญิง","cbCairXa8n7KAr0j","https://ap.wps.com/l/cbCairXa8n7KAr0j","pdf",4833926,26,"English","# Control Charts\n## Key components and sigma limits\n## Types of Control Charts\n## Selecting charts by data type and distribution\n## Verifying distribution and reference formulas","[{\"question\":\"What is an SPC control chart used for in IPC?\",\"answer\":\"It is used as a statistical tool to monitor process behavior and assess process success and improvement in IPC.\"},{\"question\":\"What do the central line and control limits represent in a control chart?\",\"answer\":\"The central line reflects the average value, while the upper and lower control limits are set using ±3 sigma to indicate typical variation.\"},{\"question\":\"How do you choose between variable and attribute control charts?\",\"answer\":\"Use variable charts (X-bar and S) for continuous data following a normal distribution, and attribute charts (np/p or c/u) for discrete counted data matched to binomial or Poisson distributions.\"}]","Statistical Process Control Chart (SPC) In IPC | PDF",1791828623,9]