Tools of sqc

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Show More. Views Total views. Actions Shares. No notes for slide. Department of Agriculture, and served as the editor of Shewhart's book Statistical Method from the Viewpoint of Quality Control which was the result of that lecture. Define a problem II. Select method i. CE III. Draw the problem base and Centre arrow IV. Specify major sources V.

Identify possible causes VI. Analysis and Solution Select Two factors 2. Collect data in large nos. Draw a graph with independent variable on horizontal axis and dependent variable on vertical axis. If the data clearly form a line or a curve, you may stop. Descriptive statistics are applied to a population of data and are used to describe the data in that population. QW 5 provides an extensive list of these Statistics to select from to best suit any population of data collected in a QW 5 application.

A key understanding of statistics is that they act as indicators, like blood pressure and heart rate, to help diagnose or better understand the data collected. An example would be the Descriptive statistic Observed Out of Specification where each data point in the population is measured against fixed specification limits to determine the number that exceed the specification limits. The inferential example would be the Calculated out of specification which is based on the volatility of the data.

It speculates on whether there would be more out of specification values found if more samples were taken. It can be used as a test on whether the testing frequency is correct based on the variation detected in the data collected. So in summary SPC is focused on minimizing variation in a process and running at target , while SQC , using similar tools, is the auditing method of insuring outputs meet exact requirements.

In addition its failure analysis capabilities to capture, analyze and eliminate productivity losses like Downtime, Defects and Waste making it the complete cost effective solution for the manufacturing floor. The majority of measurements should fall within the control limits. Measurements that fall outside the control limits are examined to see if they belong to the same population as our initial snapshot or model.

Stated differently, we use historical data to compute the initial control limits. Then the data are compared against these initial limits. Points that fall outside of the limits are investigated and, perhaps, some will later be discarded.