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
Keyword(s):  
Quality Control ◽  
Control Charts ◽  
Statistical Quality Control ◽  
Statistical Quality

Monitoring intensive care unit performance using statistical quality control charts

1993 ◽  
Vol 10 (3) ◽  
pp. 155-161 ◽  
Author(s):  
William H. Chamberlin ◽  
Kevin A. Lane ◽  
James N. Kennedy ◽  
Scott D. Bradley ◽  
Charles L. Rice
Keyword(s):  
Intensive Care Unit ◽  
Quality Control ◽  
Intensive Care ◽  
Control Charts ◽  
Statistical Quality Control ◽  
Statistical Quality ◽  
Quality Control Charts ◽  
Unit Performance

scholarly journals On-the-Fly Massively Multitemporal Change Detection Using Statistical Quality Control Charts and Landsat Data

2014 ◽  
Vol 52 (6) ◽  
pp. 3316-3332 ◽  
Author(s):  
Evan B. Brooks ◽  
Randolph H. Wynne ◽  
Valerie A. Thomas ◽  
Christine E. Blinn ◽  
John W. Coulston
Keyword(s):  
Quality Control ◽  
Change Detection ◽  
Control Charts ◽  
Statistical Quality Control ◽  
Landsat Data ◽  
Statistical Quality ◽  
Quality Control Charts

scholarly journals Analisis Pengendalian Kualitas Menggunakan Bagan Kendali Bivariat dengan Copula pada Industri Manufactur di Indonesia

2020 ◽  
Vol 6 (1) ◽  
pp. 27
Author(s):  
Tika Endah Lestari ◽  
Sri Susilawati Islam
Keyword(s):  
Quality Control ◽  
Distribution Function ◽  
Control Charts ◽  
Control Process ◽  
Simple Random Sampling ◽  
Statistical Quality Control ◽  
Consumer Decision Making ◽  
Manufacturing Companies ◽  
Statistical Quality ◽  
Quality Control Process

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

scholarly journals PRODUCT QUALITY CONTROL ANALYSIS USING STATISTICAL QUALITY CONTROL (SQC) ON MARINE WORKS IN BUSINESS AMPLANG SAMARINDA

2020 ◽  
Vol 6 (1) ◽  
pp. 70-77
Author(s):  
Silvia Maulida Arianti ◽  
Emy Rahmawati ◽  
RR Yulianti Prihatiningrum
Keyword(s):  
Quality Control ◽  
Product Quality ◽  
Control Charts ◽  
Quantitative Research ◽  
Quantitative Methods ◽  
Control Measures ◽  
Control Limit ◽  
Statistical Quality Control ◽  
Control Analysis ◽  
Statistical Quality

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.

scholarly journals ANALISIS STATISTICAL QUALITY CONTROL DALAM UPAYA MENGURANGI JUMLAH PRODUK CACAT DI PABRIK ROTI THE LI NO’U BAKERY

2020 ◽  
Vol 1 (1) ◽  
pp. 24-36
Author(s):  
RAHMAWATY AHMAD ◽  
RESMAWAN RESMAWAN ◽  
DEWI RAHMAWATY ISA
Keyword(s):  
Quality Control ◽  
Control Charts ◽  
Raw Materials ◽  
Statistical Quality Control ◽  
Bakery Products ◽  
Management Activity ◽  
Statistical Quality ◽  
Cause And Effect ◽  
Production Errors ◽  
Cause And Effect Diagram

Quality control is a technical and management activity which measures the quality characteristics of a product or service. Statistical quality control can be used to find production errors that result in defective products so that further corrective action can be taken to overcome them. The objective to be achieved in this research is to determine the Statistical Quality Control (SQC) method with pareto diagrams, control charts, cause and effect diagrams and 5W+1H analysis applied to The Li No'u Bakery in controlling quality to minimize failed products. The data in this study were obtained through direct observation and field interviews. Data analysis tools used are control charts, pareto diagrams, cause and effect diagrams and 5W + 1H analysis. Through a cause and effect diagram, the main factors causing the failure of bakery products at The Li No'u Bakery are manufacturers/employees. This is because the operator fails in making bakery products both the preparation of raw materials, the production process and packaging. So training is needed on making the dough, how to put bread and how to covenant and employee order according to the standard of The Li No'u Bakery.

Sign in / Sign up

Export Citation Format

Share Document