scholarly journals Analisis Pengendalian Kualitas Produk Air Minum Dalam Kemasan dengan Menggunakan Statistical Process Control (SPC) dan Kaizen Pada PT. Tujuh Impian Bersama Kabupaten Jember

2018 ◽  
Vol 5 (2) ◽  
pp. 164
Author(s):  
Marga Area Refangga ◽  
Eka Bambang Gusminto ◽  
Didik Pudjo Musmedi

This research aims to analyze the level of damage and identify factors causing damage AMDK 220ml that occurred on March 13 to 11 April 2017 at PT. Tujuh Impian Bersama. The company is engaged in bottled drinking water industry (AMDK) with Al Qodiri brand. This research uses descriptive statistical research model. The analysis used is Statistical Process Control (SPC) and Kaizen. The results of the analysis show that the quality control of the product is beyond the control limits set. The most damage type is dent pack as much as 239pcs. From the causal diagram can be known factors causing damage from the most dominant include machinery, raw materials, humans, and methods. Based on the kaizen implementation tools, the recommendations for improvement are routine maintenance and re-adjustment of production machines, more rigorous selection of suppliers with more stringent standards, and improved human resource performance through supervision and briefing. Keywords: Bottled Water, Kaizen, Quality Control, Statistical Process Control  

2017 ◽  
Vol 1 (2) ◽  
Author(s):  
Joko Saryono ◽  

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.


2012 ◽  
Vol 263-266 ◽  
pp. 839-842 ◽  
Author(s):  
Zhong Qiu Jiang

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.


2019 ◽  
Vol 7 ◽  
Author(s):  
Kurniawan Eka Rusandi ◽  
Wiwik Sulistiyowati

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.


Author(s):  
Sunil Chopra

Looks at the introduction of statistical process control (SPC) into a distribution center servicing a department store chain. Focuses on the receiving process in the distribution center and describes the introduction of SPC methodology. Discusses run charts, pareto diagrams, and control limits.To introduce statistical process control.


2019 ◽  
Vol 60 (2) ◽  
pp. 74-83
Author(s):  
J. Sarfo-Ansah ◽  
K. A. Boakye ◽  
E. Atiemo ◽  
R. Appiah

A Quality control scheme was developed for a 200 ton per day commercial pozzolana plant. The scheme was evaluated for the first 34 days of production. Statistical Process Control tech­niques were specifically applied to the mechanical properties of setting times and compressive strength. Results obtained showed that pozzolana samples tested were chemically suitable with total SiO2, Al2O3 and Fe2O3 content ≥ 70%. Mechanical tests performed were mostly under control and when out-of-control, they gave valuable indication to plant malfunction or operator errors which were promptly corrected. The results of mechanical properties tested against the three major brands of cement on the Ghanaian market showed that pozzolana gave highest compressive strengths with Dangote CEM I 42.5R ranging between 21.3 MPa - 36.3 MPa at 7 days and 33.8 MPa - 45.1 MPa at 28 days whilst lowest compressive strengths were obtained with Ghacem CEM II B-L 32.5R cement ranging between 16.3 MPa – 23.6 MPa at 7 days and 23.3 MPa – 30.7 MPa at 28 days. Compressive strengths obtained with Diamond CEM II B-L 42.5N cement were average. A mean compressive strength for all brands of ce­ment of 25.2 MPa and 33.6 MPa at 7 days and 28 days respectively were obtained. Keywords: Pozzolana cement, statistical process control, Shewhart chart, compressive strength, setting time


2016 ◽  
Vol 32 (3) ◽  
pp. 307-312 ◽  
Author(s):  
Colleen A. Hughes Driscoll ◽  
Jamie A. Schub ◽  
Kristi Pollard ◽  
Dina El-Metwally

Handoffs for neonatal resuscitation involve communicating critical delivery information (CDI). The authors sought to achieve ≥95% communication of CDI during resuscitation team requests. CDI included name of caller, urgency of request, location of delivery, gestation of fetus, status of amniotic fluid, and indication for presence of the resuscitation team. Three interventions were implemented: verbal scripted handoff, Spök text messaging, and Engage text messaging. Percentages of CDI communications were analyzed using statistical process control. Following implementation of Engage, the communication of all CDI, except for indication, was ≥95%; communication of indication occurred 93% of the time. Control limits for most CDI were narrower with Engage, indicating greater reliability of communication compared to the verbal handoff and Spök. Delayed resuscitation team arrival, a countermeasure, was not higher with text messaging compared to verbal handoff ( P = 1.00). Text messaging improved communication during high-risk deliveries, and it may represent an effective tool for other delivery centers.


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