This document provides an overview of statistical quality control (SQC). It describes the three main categories of SQC as descriptive statistics, statistical process control (SPC), and acceptance sampling. Key aspects of SPC covered include identifying sources of variation, using control charts for variables and attributes, calculating process capability indices, and the concepts of six-sigma quality. Acceptance sampling is introduced as inspecting a sample from a batch to determine if the entire batch meets quality standards.
X‾ -R Chart maximum utilization of information available from data & provide detailed information in process average & variation for control of individual dimensions.
Control is a system for measuring and checking or inspecting a phenomenon. It suggests when to inspect, how often to inspect and how much to inspect. Control ascertains quality characteristics of an item, compares the same with prescribed quality characteristics of an item, compares the same with prescribed quality standards and separates defective item from non-defective ones.
Statistical Quality Control (SQC) is the term used to describe the set of statistical tools used by quality professionals.
SQC is used to analyze the quality problems and solve them. Statistical quality control refers to the use of statistical methods in the monitoring and maintaining of the quality of products and services.
Variation in manufactured products is inevitable; it is a fact of nature and industrial life. Even when a production process is well designed or carefully maintained, no two products are identical.
The difference between any two products could be very large, moderate, very small or even undetectable depending on the sources of variation.
For example, the weight of a particular model of automobile varies from unit to unit, the weight of packets of milk may differ very slightly from each other, and the length of refills of ball pens, the diameter of cricket balls may also be different and so on.
The existence of variation in products affects quality. So the aim of SQC is to trace the sources of such variation and try to eliminate them as far as possible.
Control Charts for variables Xbar and R chart and attributes P, nP, C, and u ...Dr.Raja R
Control Charts for variables Xbar and R chart
and attributes P, nP, C, and u charts, Variables Control Charts,X bar chart using R chart or X bar chart using s chart, X & MR (moving range) chart, Attributes Control Charts,
X‾ -R Chart maximum utilization of information available from data & provide detailed information in process average & variation for control of individual dimensions.
Control is a system for measuring and checking or inspecting a phenomenon. It suggests when to inspect, how often to inspect and how much to inspect. Control ascertains quality characteristics of an item, compares the same with prescribed quality characteristics of an item, compares the same with prescribed quality standards and separates defective item from non-defective ones.
Statistical Quality Control (SQC) is the term used to describe the set of statistical tools used by quality professionals.
SQC is used to analyze the quality problems and solve them. Statistical quality control refers to the use of statistical methods in the monitoring and maintaining of the quality of products and services.
Variation in manufactured products is inevitable; it is a fact of nature and industrial life. Even when a production process is well designed or carefully maintained, no two products are identical.
The difference between any two products could be very large, moderate, very small or even undetectable depending on the sources of variation.
For example, the weight of a particular model of automobile varies from unit to unit, the weight of packets of milk may differ very slightly from each other, and the length of refills of ball pens, the diameter of cricket balls may also be different and so on.
The existence of variation in products affects quality. So the aim of SQC is to trace the sources of such variation and try to eliminate them as far as possible.
Control Charts for variables Xbar and R chart and attributes P, nP, C, and u ...Dr.Raja R
Control Charts for variables Xbar and R chart
and attributes P, nP, C, and u charts, Variables Control Charts,X bar chart using R chart or X bar chart using s chart, X & MR (moving range) chart, Attributes Control Charts,
The presentation is about basic statistical techniques and how statistics can be used effectively in the quality control and process control. It also presents statistical package Minitab version 16 and some of its applications in the field of statistical process control.
Control Charts in Lab and Trend Analysissigmatest2011
Go through this presentation by Sigma Test and Research Centre and know about control charts in lab and trend analysis. To know more about us visit our website.
2. Learning Objectives
Describe Categories of SQC
Explain the use of descriptive statistics
in measuring quality characteristics
Identify and describe causes of
variation
Describe the use of control charts
Identify the differences between x-bar,
R-, p-, and c-charts