scholarly journals Implementation of Statistical Process Control through PDCA Cycle to Improve Potential Capability Index of Drop Impact Resistance: A Case Study at Aluminum Beverage and Beer Cans Manufacturing Industry in Indonesia

2020 ◽  
Vol 24 (1) ◽  
pp. 104 ◽  
Author(s):  
Sunadi Sunadi ◽  
Humiras Hardi Purba ◽  
Sawarni Hasibuan
Keyword(s):  
Process Control ◽  
Statistical Process Control ◽  
Manufacturing Industry ◽  
Impact Resistance ◽  
Process Capability ◽  
Drop Impact ◽  
Nominal Group ◽  
Statistical Process ◽  
Capability Index ◽  
Pdca Cycle

<p><strong>Purpose:</strong> The purposes of this study are first, to analyze why the <em>process capability index </em>(<em>Cpk</em>) for drop impact resistance (DIR) does not meet the specification or less than 1.33, and second, to find out what improvements should be made to make it meet the specification.</p><p><strong>Methodology/Approach:</strong> The methodology used was Statistical Process Control (SPC) through the PDCA cycle, supporting with Cause and Effect Diagram (CED), Nominal Group Technique (NGT) and “why, what, where, when and how (5W1H)” method.</p><p><strong>Findings:</strong> With the above methods, the result of the study was given a positive impact on the company. The average of DIR was increased from 20.40 cm to 25.76 cm, increased by 26.27% and the standard deviation was reduced from 1.80 to 1.48, and then the<em> Cpk</em> index was increased from 0.48 to 1.79 it means the process is in control and capable.</p><p><strong>Research Limitation/implication:</strong> This research was limited only on the two-piece can aluminum cans manufacturing process, no for three-piece cans manufacturing. SPC through PDCA cycle is an interesting method for continuous improvement of process capability in the cans manufacturing industry.</p><strong>Originality/Value of paper:</strong> This study highlights the area of future research SPC through the PDCA cycle to analyze and optimize process capability. Therefore, this research is considered to promote and adopt high-valued methodologies for supporting industry to achieve global competitive advantages.

scholarly journals PROCESS CAPABILITY ANALYSIS PADA NUT (STUDI KASUS: PT SANKEI DHARMA INDONESIA)

2017 ◽  
Vol 12 (2) ◽  
pp. 137
Author(s):  
Helena Sisilia R. S. ◽  
Hendy Tannady
Keyword(s):  
Process Control ◽  
Statistical Process Control ◽  
Process Capability ◽  
Statistical Process ◽  
Process Capability Analysis ◽  
Capability Index ◽  
Inside Diameter ◽  
Capability Analysis ◽  
Improved Performance ◽  
A Company

PT Sankei Dharma Indonesia merupakan perusahaan yang bergerak di bidang otomotif. Salah satu produk yang dihasilkan adalah nut (berfungsi sebagai dudukan kabel sensor). Proses nut dianggap critical to quality, dimana hasil dari proses memperhatikan inside diameter nut yang dihasilkan PT A, PT B, dan PT C. Peningkatan kinerja proses dilakukan dengan menggunakan process capability yang merupakan salah metode dari Statistical Process Control. Hasil dari penelitian menunjukkan bahwa process capability pada inside diameter PT B berjalan dengan tidak sesuai, di mana nilai capability index Cp = 0.57, Cpl = 0.58, Cpu = 0.56, Cpk = 0.56, dan Cpm = 0.54. Sedangkan process capability pada inside diameter PT A dan PT C tergolong sangat memuaskan. Di mana nilai capability index PT C Cp = 2.34, Cpl = 2.37, Cpu = 2.30, Cpk = 2.30, dan Cpm = 2.26. Dan nilai capability index PT A Cp = 1.77, Cpl = 1.79, Cpu = 1.75, Cpk = 1.75, dan Cpm = 1.86. AbstractPT Sankei Dharma Indonesia is a company engaged in the automotive field. One of the resulting product is a nut (functioning as a sensor cable holder). Nut process is considered critical to quality, which result from the attention generated inside diameter nut PT A, PT B, dan PT C. Improved performance of process is done by using process capability, which is one method of Statistical Process Control. Results from the study showed that the process capability to the inside diameter of the PT B running is not appropriate, in which the value of capability index Cp = 0,57; Cpl = 0,58; Cpu = 0,56; Cpk = 0,56, dan Cpm = 0,54; While the process capability to inside diameter PT A and PT C as very satisfactory. Where the value of capability index PT C Cp = 2.34, Cpl = 2.37, Cpu = 2.30, Cpk = 2.30, dan Cpm = 2.26. And the value of capability index PT A Cp = 1.77, Cpl = 1.79, Cpu = 1.75, Cpk = 1.75, dan Cpm = 1.86.

scholarly journals Pengendalian Kualitas Produksi dengan Statistical Process Control (SPC)

2017 ◽  
Vol 10 (1) ◽  
Author(s):  
Mohamad Solihudin
Keyword(s):  
Quality Control ◽  
Quality Assurance ◽  
Process Control ◽  
Statistical Process Control ◽  
Manufacturing Industry ◽  
Product Quality Control ◽  
Standard Size ◽  
Statistical Process ◽  
Analysis Process ◽  
Keywords Quality Assurance

<p>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.</p><p>Keywords: Quality assurance, manufacturing industry, quality control, Statistical Process Control</p>

The Application Research of Statistical Process Control in Quality Management

2014 ◽  
Vol 926-930 ◽  
pp. 4000-4003
Author(s):  
Qiu Yan Liu ◽  
Jun Li Shi ◽  
Shi Yuan Xing
Keyword(s):  
Quality Management ◽  
Process Control ◽  
Statistical Process Control ◽  
Control Chart ◽  
Process Capability ◽  
Control Technology ◽  
Application Research ◽  
Statistical Process ◽  
Intensity Index ◽  
Productive Process

By discussing the application of statistical process control technology in the print and package industry, we have been in control of the productive process, for focusing on the heat-seal intensity index of sauce package products, and utilized instability of the control chart discovering the instable in the process , to realize the pre-alarm function. The management makes the process update constantly, and enhances the process capability.

scholarly journals A study on the application of control chart in healthcare

2021 ◽  
Vol 36 ◽  
pp. 01001
Author(s):  
Yee Kam Seoh ◽  
Voon Hee Wong ◽  
Mahboobeh Zangeneh Sirdari
Keyword(s):  
Process Control ◽  
Statistical Process Control ◽  
Control Chart ◽  
Control Charts ◽  
Manufacturing Industry ◽  
Positive Impact ◽  
Healthcare Management ◽  
Healthcare Sector ◽  
Statistical Tool ◽  
Statistical Process

The most concerning issues in the healthcare system will always be quality control and quality improvement as they are significant to the health condition of the patient. A quality statistical tool such as statistical process control (SPC) charts will be efficient and highly effective in reducing the sources of variation within the healthcare process and in monitoring or controlling improvement of the process. The control chart is a statistical process control methodology designed to evaluate the process improvement or change in the manufacturing industry and is being implemented gradually in the healthcare sector. This will enable healthcare organizations to prevent unnecessary investment or spending in any changes that sound good but do not have any positive impact on real progress or improvement. When there is greater participation of humans in healthcare, the risks of error are also greater. Control charts help determine the source of error by differentiating the common and special cause of variation, each requiring a different response from healthcare management. This paper intends to deliver an overview of SPC theory and to explore the application of SPC charts by presenting a few examples of the implementation of control charts to common issues in the healthcare sector. After a brief overview of SPC in healthcare, the selection and construction of the two widely used control charts (Individuals and Moving Range chart, U chart) were adopted and illustrated by using the example from healthcare.

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