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 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 Improving Process Performance of Cotton Spinning by Using Statistical Process Control Techniques

2020 ◽  
pp. 15-22
Author(s):  
Dereje Girma ◽  
Omprakash Sahu
Keyword(s):  
Process Control ◽  
Statistical Process Control ◽  
Control Charts ◽  
Shop Floor ◽  
Statistical Control ◽  
Statistical Process ◽  
Process Capability Analysis ◽  
Capability Analysis ◽  
R Process ◽  
And Control

Identifying the presence and understanding the causes of process variability are key requirements for well controlled and quality manufacturing. This pilot study demonstrates the introduction of Statistical Process Control (SPC) methods to the spinning department of a textile manufacturing company. The methods employed included X Bar and R process control charts as well as process capability analysis. Investigation for 29 machine processes identified that none were in statistical control. Recommendations have been made for a repeat of the study using validated data together with practical application of SPC and control charts on the shop floor and extension to all processes within the factory.

scholarly journals ANALISIS KUALITAS PRODUK MENGGUNAKAN METODE STATISTIC PROCESS CONTROL (SPC) MINITAB DAN TIME-CHARTING DI PT. COCA-COLA BOTTLING INDONESIA UNIT LAMPUNG

2017 ◽  
Vol 1 (2) ◽  
Author(s):  
Joko Saryono ◽  
Keyword(s):  
Quality Control ◽  
Process Control ◽  
Statistical Process Control ◽  
Control Method ◽  
Production Data ◽  
Statistical Process ◽  
Research Results ◽  
Statistic Process Control ◽  
Gas Volume ◽  
A Company

Abstract PT. COCA-COLA BOTTLING INDONESIA is a company engaged in the field of Agro-industry is bottling soft drinks and not sparkling. The products produced are Coca-Cola, Sprite, Fanta, and Tea. To be able to compete with similar industries then the company implements quality control by Statistical Process Control method. In the development of this SPC many methods there are manual or who use the software. Currently PT. Coca-Cola Bottling Indonesia in quality control using Time Charting method, but since the transition from Minitab to Time Charting the tendency of the value of capability below standard, whereas production data is almost the same as using Minitab. The purpose of this research is to analyze the inequality of Statistical Process Control between Minitab 13 and Time Charting. Time Charting method is a new method that is given by the headquarters for the process of quality control can be fast and accurate. Quality control with the Statistical Process Control of Minitab and Time Charting methods after the results of the research results was found to be part of different LSL and USL charging, and Calculate Statistic Using different from Minitab method should still be 6 but in written procedure 3. For writing LSL And USL if the Time Charting is determined by the head office while Minitab analysts fill in based on experiments on the decrease of gas volume marketed in previous years. From the research results obtained Cpk data for Minitab method 13 is Sprite 390 ml 1.47, Sprite 1000 ml 1.90 and Sprite 1500 ml 1.38. The result of the research was using Minitab method and the Charting Time of Capacity that is above 1.33 average. The causes of the resulting inequality of both methods are the LSL, USL and Calculate Statistic Using values. The smaller the value of Calculate Statistic Using the higher Cpk produced. Keywords: Production, Statistical Process Control, Quality.

scholarly journals Statistical process control and CAQ systems as a tools assuring quality in the automotive industry

2019 ◽  
Vol 2 (1) ◽  
pp. 336-344
Author(s):  
Łukasz Wiecha ◽  
Grzegorz Ćwikła
Keyword(s):  
Quality Management ◽  
Process Control ◽  
Statistical Process Control ◽  
Automotive Industry ◽  
Management System ◽  
Quality Management System ◽  
Statistical Process ◽  
Assurance System ◽  
A Company

Abstract The aim of the article is to present the case study of implementation of the example CAQ system, which allows to meet the requirements of IATF 16949:2016 and the VDA 6.1 standards in the field of statistical process control (SPC). The foundations of the CAQ systems concept and their specific requirements, especially for companies operating in the automotive industry, for which modern CAQ tools are necessary, in the described case based on the LEAN-QS program, are presented. The article presents the observations and results of the analysis of the operation of the quality assurance system in a company that is a supplier of car parts. One of the modules of the LEAN-QS program was implemented there, which makes it possible to meet the requirements of a certified quality management system. The effectiveness of the presented tool was demonstrated, allowing to meet industry requirements while minimizing resources necessary for supervision and proper implementation of the quality management system process, which in this case is the SPC.

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 Process Capability and Average Roughness in Abrasive Water Jet Cutting Process of Stainless Steel

2018 ◽  
Vol 8 (3) ◽  
pp. 2931-2936
Author(s):  
M. Boujelbene
Keyword(s):  
Stainless Steel ◽  
Process Capability ◽  
Water Jet ◽  
Process Capability Index ◽  
Abrasive Water Jet ◽  
Process Capability Analysis ◽  
Capability Index ◽  
Water Jet Cutting ◽  
Abrasive Water Jet Cutting ◽  
Capability Analysis

Process capability analysis is frequently employed to evaluate if a product or a process can meet the customer’s requirement. In general, process capability analysis can be represented by using the process capability index. Until now, the process capability index was frequently used for manufacturing processes with quantitative characteristics. However, for a process with qualitative characteristic like cutting surface, the data’s type and single specification caused limitations of using the process capability index. Taguchi developed a surface quality by abrasive water jet cutting or quadratic quality loss function to address such issues. In this study, we intend to construct a measurable index which incorporates the process capability index philosophy concept to analyze the process capability with the consideration of the qualitative surface roughness. The manufacturers can employ the proposed index to self-assess the process capability. The objective of this study was to examine the effects of abrasive water jet machining variables like cutting speed of the stainless steel material. The roughness of the varied surface through the cut depth was also measured and determined as a process capability index of 3 zones machined surface.

Retrospective analysis for phase I statistical process control and process capability study using revised sample entropy

2018 ◽  
Vol 31 (11) ◽  
pp. 7415-7428 ◽  
Author(s):  
Shing I. Chang ◽  
Zheng Zhang ◽  
Siim Koppel ◽  
Behnam Malmir ◽  
Xianguang Kong ◽  
...  
Keyword(s):  
Process Control ◽  
Phase I ◽  
Retrospective Analysis ◽  
Statistical Process Control ◽  
Process Capability ◽  
Sample Entropy ◽  
Statistical Process
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