Statistical quality control and control charts Presented by:-Somya Shukla (55)Vishwadeep Mishra (56)Statistical Quality ControlThe application of statistical techniques to measure and evaluate the quality of a product, service, or process.

The objective of statistical quality control is to monitor production through many stages of manufacturing.

2HistorySQC was pioneered by Walter A. Shewhart at Bell Laboratories in the early 1920s.Shewhart developed the control chart in 1924 and the concept of a state of statistical control.W. Edwards Deming invited Shewhart to speak at the Graduate School of the U.S. Department of Agriculture, and served as the editor of Shewharts book Statistical Method from the Viewpoint of Quality Control (1939) which was the result of that lecture.Deming was an important architect of the quality control short courses that trained American industry in the new techniques during WWII.Characteristics Control quality standard of goods produced for marketing.Exercise by the producers during production to assess the quality of goods.Carried out with the help of certain statistical tools like Mean Chart, Range Chart, P-Chart, C-Chart etc.Designed to determine the variations in quality of the goods & limits of toleranceMethods of Statistical Quality ControlVariations in QualityNo two items are exactly alike.Some sort of difference in the two items is bound to be there. Infact it is an integral part of any manufacturing process.This difference in characteristics known as variation.This variation may be due to substandard quality of raw material, carelessness on the part of operator, fault in machinery system etc..Causes of Variations7ASSIGNABLE CAUSES It refers to those changes in the quality of the products which can be assigned or attributed to any particular causes like defective materials, defective labour, etc.Assignable causes are non-random and can be identified and correctable.Non random causes likeDifference in quality of raw materialDifference in machinesDifference in operatorsDifference of time

8CHANCE CAUSES These causes take place as per chance or in a random fashion as a result of the cumulative effect of a multiplicity of several minor causes which cannot be identified. These causes are inherent in every type of production. Variation occurred due to chance. This variation is NOT due to defect in machine, Raw material or any other factors. Behave in random manner". Negligible but Inevitable. The process is said to be under the state of statistical control.

Statistical Process ControlSPC is a statistical procedure using control charts to see if any part of a production process is not functioning properly and could cause a poor quality. Statistical process control (SPC) involves inspecting a random sample of the output from a process and deciding whether the process is producing products with characteristics that fall within a predetermined range. SPC answers the question of whether the process is functioning properly or not.

11Control Charts

A point that plots within the control limits indicates the process is in control.A point that plots outside the control limits is evidence that the process is out of control. Control charts are graphs that establishes the control limit of a process.A control chart contains. A center line.An upper control limitA lower control limit

12Control charts for Variables Control charts for variables monitor characteristics that can be measured and have a continuous scale, such as height, weight, volume, or width. When an item is inspected, the variable being monitored is measured and recorded.For example, if we were producing candles, height might be an important variable. We could take samples of candles and measure their heights.Two of the most commonly used control charts for variables monitor both the central tendency of the data (the mean) and the variability of the data (either the standard deviation or the range).

A product characteristic that can be measured and has a continuum of values (e.g., height, weight, or volume).

Note that each chart monitors a different type of information. When observed values go outside the control limits, the process is assumed not to be in control. Production is stopped, and employees attempt to identify the cause of the problem and correct it. Next we look at how these charts are developed.

x-bar chart: A control chart used to monitor changes in the mean value of a process.Range (R) chart: A control chart that monitors changes in the dispersion or variability of process

13Control charts for AttributesControl charts for attributes are used to measure quality characteristics that are counted rather than measured. Attributes are discrete in nature and entail simple yes-or-no decisions. For example, this could be the number of nonfunctioning light bulbs, the proportion of broken eggs in a carton, the number of rotten apples, the number of scratches on a tile, or the number of complaints issued. Two of the most common types of control charts for attributes are p-charts and c-charts. A product characteristic that has a discrete value and can be counted.

P-chart : A control chart that monitors the proportion of defects in a sample.C-chart : A control chart used to monitor the number of defects per unit.

14Brushing Through the FundamentalsMean (X-bar) Chart

Alternative Calculation of UCL & LCL in X-bar Chart

R-Chart

24Conclusion (X-bar Chart & R-Chart)P-Chart

C-Chart

When do we use Control Charts?????Thank You..