Statistical Process and Quality Control

2016 ◽  
pp. 888-950
Author(s):  
William M. Mendenhall ◽  
Terry L. Sincich
Keyword(s):  
Quality Control ◽  
Statistical Process

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.

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.

Statistical Process and Quality Control

2000 ◽  
pp. 233-244
Keyword(s):  
Quality Control ◽  
Quality Improvement ◽  
Quality Management ◽  
Total Quality Management ◽  
Statistical Process Control ◽  
Control Charts ◽  
Statistical Testing ◽  
Total Quality ◽  
Statistical Process ◽  
Sampling Plans

Abstract This chapter provides an introduction to statistical process control and the concept of total quality management. It begins with a review of quality improvement efforts in the extrusion industry and the considerations involved in developing sampling plans and interpreting control charts. It then lays out the steps that would be followed in order to implement statistical testing for billet casting, die performance, or any other process or variable that impacts extrusion quality. The chapter concludes with an overview of the fundamentals of total quality management.

Inspection in Process Control

1998 ◽  
Vol 42 (16) ◽  
pp. 1170-1174
Author(s):  
Somchart Thepvongs ◽  
Brian M. Kleiner
Keyword(s):  
Quality Control ◽  
Process Control ◽  
Signal Detection ◽  
Control Chart ◽  
Control Charts ◽  
Signal Detection Theory ◽  
Detection Theory ◽  
Statistical Quality Control ◽  
Total Quality ◽  
Statistical Process

Consistent with the precepts of total quality control and total quality management, there has been a resource shift from incoming and outgoing inspection processes to statistical quality control of processes. Furthermore, process control operators are responsible for their own quality, necessitating the in-process inspection of components. This study treated the statistical process control task of “searching” control charts for out-of-control conditions as an inspection task and applied the Theory of Signal Detection to better understand this behavior and improve performance. Twelve subjects participated in a research study to examine how the portrayal of control chart information affected signal detection theory measures. The type of display did not have a significant effect on the sensitivity and response criterion of subjects. These results are discussed in terms of the applicability of Signal Detection Theory in control chart decision making as well as implications on display design.

scholarly journals A Quality Control Scheme for a Commercial Pozzolana Plant: A Case Study of Pozzolana Ghana Ltd

2019 ◽  
Vol 60 (2) ◽  
pp. 74-83
Author(s):  
J. Sarfo-Ansah ◽  
K. A. Boakye ◽  
E. Atiemo ◽  
R. Appiah
Keyword(s):  
Mechanical Properties ◽  
Quality Control ◽  
Compressive Strength ◽  
Process Control ◽  
Statistical Process Control ◽  
Setting Time ◽  
Mechanical Tests ◽  
Statistical Process ◽  
Control Scheme ◽  
Quality Control Scheme

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

Sign in / Sign up

Export Citation Format

Share Document