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 (SPC) UNTUK PENGENDALIAN KUALITAS PRODUK MEBEL DI UD. IHTIAR JAYA

2020 ◽  
Vol 6 (1) ◽  
pp. 50
Author(s):  
RICKI ELYAS ◽  
WIWIK HANDAYANI
Keyword(s):  
Quality Control ◽  
Process Control ◽  
Statistical Process Control ◽  
Control Chart ◽  
Control Method ◽  
Statistical Process ◽  
Dominant Type ◽  
Fishbone Diagram ◽  
Teak Wood ◽  
Product Defect

ABSTRACT The influence of globalization in the industrial world today has led to intense and competitive competition between companies. UD. Ihtiar Jaya is a manufacturing company engaged in furniture, especially those made from teak wood. The company serves retail product sales, as well as servicing or renovating various types of furniture. To be able to produce good quality, quality control activities are carried out. This research aims to determine the number of defective furniture products and the most dominant type of defects at UD. Ihtiar Jaya, to analyze the implementation of quality control at UD. Jaya Jaya uses Statistical Process Control in an effort to reduce the number of defective products, and to identify what factors cause damage/defects in products manufactured by UD. Ihtiar Jaya.In this research, the sample used was the number of defects in furniture products at UD. Ihtiar Jaya in 2018. The technique of determining this sample uses purposive sampling. This research uses the Statistical Process Control method, namely check sheet, pareto diagram, control chart, and fishbone diagram.Based on the results of the check sheet, it was concluded that the average product defect was 10.38% per month. From the results of the Pareto diagram can be seen that the highest level of defects is scratched with a total of 104 units or 61.18% of the total defective products in 2018. While the results of the control chart that have been made can be seen that the quality control is not controlled and not in accordance with standards. From the results of fishbone diagram concluded that the factors that cause product defects are human factors, production machinery, materials, work methods, and work environment.

scholarly journals Estimating the Time to Benefit for Preventive Drugs with the Statistical Process Control Method: An Example with Alendronate

Drugs & Aging ◽  
2016 ◽  
Vol 33 (5) ◽  
pp. 347-353 ◽  
Author(s):  
Esther M. M. van de Glind ◽  
Hanna C. Willems ◽  
Saeid Eslami ◽  
Ameen Abu-Hanna ◽  
Willem F. Lems ◽  
...  
Keyword(s):  
Process Control ◽  
Statistical Process Control ◽  
Control Method ◽  
Statistical Process

The Intelligent Quality Control Technology System Based on the Integration Methods of SPC and EPC

2012 ◽  
Vol 263-266 ◽  
pp. 839-842 ◽  
Author(s):  
Zhong Qiu Jiang
Keyword(s):  
Quality Control ◽  
Process Control ◽  
Statistical Process Control ◽  
Control Process ◽  
Control Mode ◽  
Statistical Process ◽  
Technology System ◽  
Quality Control Process ◽  
Dynamic Quality ◽  
And Function

SPC (statistical process control) and EPC (engineering process control) is the scientific methods of quality quality control and quality improvement. It is the difficult problems of quality control process for network manufacturing enterprise how to effectively solve the dynamic quality fluctuation monitoring and the fluctuation abnormal diagnostic analysis and timely process adjustments, this paper designs the intelligent quality control mode and function system architecture, the modes expatiates quality management network based on quality control network of the workshop level and enterprise class network, and researches the integration applications of statistical process control and enterprise ERP quality system, and applies J2EE technology to achieve the system organic combination of design and development.

Quality Control of Plastic Cup Products Using Statistical Process Control Methods and Failure Modes and Effect Analysis

2019 ◽  
Vol 7 ◽  
Author(s):  
Kurniawan Eka Rusandi ◽  
Wiwik Sulistiyowati
Keyword(s):  
Quality Control ◽  
Process Control ◽  
Statistical Process Control ◽  
Failure Modes ◽  
Total Production ◽  
Statistical Process ◽  
Effect Analysis ◽  
A Value ◽  
Fmea Analysis ◽  
Cup Products

PT. ICP is a company engaged in manufacturing of packaging, with a wide variety of packaging technologies that fit the needs of the current market share. Among the resulting product is aplastic cup, the results of thermoforming. This research aims to know the main cause of the defect (defect) in a plastic cup products and to reduce product defects in the production process. From the results of the observations made in September 2017 until December 2017 known that the plastic cup products with total production of 63,314,964 pcs to 3,671,341 pcs disability amount. Based on the problems faced by the company efforts on product quality control plastic cup to find the cause of a disability and find solutions for improvement. Proper methods used in the problems that occurred in PT ICP are using Statistical Process Control (SPC) and the method of Failure Mode and Effects Analysis (FMEA). The method is intended to reduce defects in the product and look for the main cause of defect products in a plastic cup. From the results of research conducted has been known that the biggest cause of disability plastic cup is of a rough lip with disabilities amount of 1,346,308 pcs with a cumulative value of 42%. FMEA analysis and the results of that unknown cause rough lip is from wear cutting factor with a value of 224 RPN.

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