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

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):  
Evan Mandala Putra ◽  
Sri Mukti Wirawati ◽  
Pugy Gautama

This study aims to analyze defects in the sheet production process in the 301 Corrugator area by analyzing the total number of sheets produced and the number of sheets that have been damaged over a certain period of time using the Statistical Process Control (SPC) method and Failure Modes and Effect Analysis (FMEA). Based on the research results, there are 6 defects, namely untidy cuts, wrinkled sheets, uneven surface, curved sheets, uneven sides, loose sheet layers. The most dominant defect is uneven surface, which is 185.141 Kg or 60%. Based on the value of the RPN table, the product defect that has the highest value is the loose sheet layer with an RPN value of 245 from the calculation stage of the RPN value, a suggestion is made to reduce defects resulting from the loose sheet layer. From the stage of making improvements, the company should prioritize and focus on the types of disabilities and types of disabilities that have the highest RPN ranking when using the Failure Mode and Effect Analysis (FMEA) method.


2018 ◽  
Vol 5 (1) ◽  
pp. 31
Author(s):  
Elisa Mardya Ratri ◽  
Eka Bambang G. ◽  
Marmono Singgih

This study aims to control the quality of sweet bread products at PT Indoroti Prima Cemerlang Jember by analyzing the total amount of bread produced and the amount of bread that is damaged over a period of time using Statistical Process Control (SPC) and Failure Modes and Effect Analysis ( FMEA).. Selection of sweet bread that will be studied is based on the proven data of bread production on Januari 2017 which show that the most damaged product were found in sweet bread variant, so it needs to get more attention from the company in priority improvement. Based on the p chart, the damage of sweet breads is within control limits. It is indicated by the whole point that are within UCL dan LCL. The UCL line is 0,0930, LCL line is 0,0238, and p (midline) is 0,0085. The types of damage which happened to the sweet breads are dents, filthy, leak, defated, and truncated. The damaged can be caused by three factors such as man, machine, and method. Based on FMEA (Failure Mode and Effect Analysis) Method, it shows that the priority improvement for production and packing process are different. Improvement in production process prioritized on man factor, while improvement in packing process prioritized on machine factor. Keywords: Failure Mode and Effect Analysis (FMEA), Quality Control, Statistical Process Control (SPC)


2018 ◽  
Vol 5 (2) ◽  
pp. 200
Author(s):  
Elisa Mardya Ratri ◽  
Eka Bambang G ◽  
Marmono Singgih

This study aims to control the quality of sweet bread products at PT Indoroti Prima Cemerlang Jember by analyzing the total amount of bread produced and the amount of bread that is damaged over a period of time using Statistical Process Control (SPC) and Failure Modes and Effect Analysis ( FMEA).. Selection of sweet bread that will be studied is based on the proven data of bread production on Januari 2017 which show that the most damaged product were found in sweet bread variant, so it needs to get more attention from the company in priority improvement. Based on the p chart, the damage of sweet breads is within control limits. It is indicated by the whole point that are within UCL dan LCL. The UCL line is 0,0930, LCL line is 0,0238, and p (midline) is 0,0085. The types of damage which happened to the sweet breads are dents, filthy, leak, defated, and truncated. The damaged can be caused by three factors such as man, machine, and method. Based on FMEA (Failure Mode and Effect Analysis) Method, it shows that the priority improvement for production and packing process are different. Improvement in production process prioritized on man factor, while improvement in packing process prioritized on machine factor. Keywords: Failure Mode and Effect Analysis (FMEA), Quality Control, Statistical Process Control (SPC)  


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 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


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