scholarly journals Control Charts: An Introduction to Statistical Quality Control.

1948 ◽  
Vol 43 (242) ◽  
pp. 343
Author(s):  
Joseph M. Juran ◽  
Mason E. Wescott ◽  
Edward S. Smith
1993 ◽  
Vol 10 (3) ◽  
pp. 155-161 ◽  
Author(s):  
William H. Chamberlin ◽  
Kevin A. Lane ◽  
James N. Kennedy ◽  
Scott D. Bradley ◽  
Charles L. Rice

2014 ◽  
Vol 52 (6) ◽  
pp. 3316-3332 ◽  
Author(s):  
Evan B. Brooks ◽  
Randolph H. Wynne ◽  
Valerie A. Thomas ◽  
Christine E. Blinn ◽  
John W. Coulston

2020 ◽  
Vol 6 (1) ◽  
pp. 27
Author(s):  
Tika Endah Lestari ◽  
Sri Susilawati Islam

Product quality control is an important factor for the industrial world because good quality control and carried out continuously will be able to detect abnormal production results quickly, so that anticipatory action can be taken immediately. Quality is a major factor in consumer decision making before buying goods / services. The problem that occurs at this time in manufacturing companies in Indonesia is how the statistical quality control process can be applied properly. The purpose of this statistical analysis is to find out the statistical quality control process that is applied to manufacturing companies in Indonesia using bivariate control charts with copula. Copula is a function that combines a multivariate distribution function with a uniform one-dimensional marginal distribution function, in this condition the Copula used is the Archimedean Copula group. The method used in this data collection is a simple random sampling with the sample used are three manufacturing companies in Indonesia which covers the areas of Jakarta, Bandung and Makassar. The implementation of Copula in this control chart results in Frank Copula being the best Copula, this supports that the use of Copula in the quality control process has a good role


Author(s):  
Silvia Maulida Arianti ◽  
Emy Rahmawati ◽  
RR Yulianti Prihatiningrum

Purpose of the study: The objectives of this study are: (i) To analyze the quality control of the products applied to the amplang Karya Bahari business based on Statistical Quality Control (SQC) tools, (ii) To find out and analyze what factors cause product damage/disability amplang work at the Maritime business in Samarinda. Methodology: This research uses quantitative methods discretionary quantitative research method that is research that is used to Investigate, find, describe, and explain the quality or features of social influences that can’t be explained or Described measured through a quantitative approach. The operational definitions of this research are (i) Quality control processes, (ii) Quality control measures. Types and sources of the data the primary use of data Obtained directly from the object of research. Data collection techniques are (i) observation, (ii) interviews, (iii) documentation, (iv) laboratory tests. Analysis of the Data used are: (i) collecting the data (check sheet), (ii) a histogram, (iii) making control charts, (iv) the causal diagrams, (v) the proposed improvements. Main Findings:  The results of the study suggest that Maritime work is applied to the already on the limit of control. It can be seen at chart, upper control limit (UCL) of 1 and the lower control limit (LCL) of 0.3362 under controlled conditions or reasonable limits, but in reality, they are experiencing product damage or defect in the production of amplang processing. Novelty/Originality of this study: This study is expected to be an additional reference for studies in the field production related to analysis quality control (quality control) and product quality by using Statistics Quality Control. This study is expected to provide information for the company about procedure control in keeping a quality product that will be produced.


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