Open AccessPengendalian Kualitas Produksi dengan Statistical Process Control (SPC)
Author(s) -
Mohamad Solihudin
Publication year - 2017
Publication title -
jiems/jiems (journal of industrial engineering and management systems)
Language(s) - English
Resource type - Journals
eISSN - 2579-8154
pISSN - 1979-1720
DOI - 10.30813/jiems.v10i1.33
Subject(s) - statistical process control , quality assurance , quality (philosophy) , manufacturing engineering , engineering , process (computing) , mathematics , computer science , operations management , physics , external quality assessment , quantum mechanics , operating system
PT. Surya Toto Indonesia Tbk. is one of the processing industry (manufacturing insudtry) with export and domestic market share. To keep the share, the company provides high quality assurance for products offered to consumers and the improvement of quality has always been the main point of fulfilling the production process. This study aims to determine what factors cause the occurrence of reject products are not standard sizes (UTS) and How can quality control with application approach Statitical Process Control (SPC) in machining section PT. Surya Toto Indonesia Tbk. to overcome reject nonstandard size (UTS). The results of this study indicate that the product quality control in machining section on the BNC-1machine, there are the highest reject percentage (11.80%) on part number S23059 with the highest type of rejection is not a standard size (uts) at a size of 9 ± 0,05mm. From the results of field observation and brainstorming, the factors that cause bad part (reject) is a factor of BNC-1 machines are old, worn collet locking bolt and fastener tool insert screws loose. The corrective action taken is to move the process of part number S23059 in production in BNA-DHY2 machine, after analysis process by the method of Statistical Process Control (SPC) concluded for capabilty process (CP) BNA-DHY2 machine excellent is 1,85. Keywords: Quality assurance, manufacturing industry, quality control, Statistical Process Control