Walter A Shewhart

most known quality guru

1. Walter A Shewhart By Ayshathul Femitha 9897 4 th semester MHA

2. WALTER A SHEWHART One of the most notable contributors to modern industry is Walter Shewhart, a quality control pioneer. Born in New Canton, Illinois in 1891 He started his rise to guru status as a Bell Telephone employee in 1918. “Father of Statistical Quality Control” “Grandfather of Total Quality Management” An American physicist, an engineer and statistician

3. HISTORY He earned his undergraduate degree and post graduation degrees from University of Illinoise . He went on to study at the University of California at Berkeley, where in 1917 he earned his doctorate in physics. Shewart spent the better part of his career at Western Electric, and the Bell Labs. He exceled both as an engineer (from 1918-1924) to technical advisor (from 1925-1956). An accomplished lecturer speaking both overseas and domestically

4. CONTRIBUTION:

5. Reducing Variation – To Improve Quality The emphasis on reducing variation to enhance quality is a great contribution to quality management. Reducing variation to improve quality resulted in manufacture of precise things. Shewhart acknowledged two classes of variation namely ‘special‐cause’ (assignable‐cause) and ‘common‐cause’ (chance‐cause) variation. A control chart was designed by him to explain these two categories of variations. 

6. Variation management Common cause variation , also known as noise variation, is inherent in a process over time. It affects every outcome of the process and everyone working in the process. Managing common cause variation thus requires improvements to the process. Special cause variation, also known as signal cause variation, arises because of unusual circumstances and is not an inherent part of a process.

7. Statistical process control Statistical process control (SPC) is defined as the use of statistical techniques to control a process or production method. SPC tools and procedures can help you monitor process behavior, discover issues in internal systems, and find solutions for production issues. Statistical process control is often used interchangeably with statistical quality control (SQC). A popular SPC tool is the control chart, originally developed by Walter Shewhart in the early 1920s. A control chart helps one record data and lets you see when an unusual event, such as a very high or low observation compared with "typical" process performance, occurs

8. Control chart Control charts, also known as Shewhart charts (after Walter A. Shewhart) or process-behavior charts, are a statistical process control tool used to determine if a manufacturing or business process is in a state of control. It is more appropriate to say that the control charts are the graphical device for Statistical Process Monitoring (SPM). Measurements are plotted on the chart versus a time line. Measurements that are outside the limits are considered to be out of control. The control chart is one of the seven basic tools of quality control.[3] Typically control charts are used for time-series data, though they can be used for data that have logical comparability

9. SHEWART CYCLE Plan:  Recognize an opportunity and plan a change. Do:  Test the change. Carry out a small-scale study. Check:  Review the test, analyze the results, and identify what you’ve learned. Act:  Take action based on what you learned in the study step. If the change did not work, go through the cycle again with a different plan. If you were successful, incorporate what you learned from the test into wider changes. Use what you learned to plan new improvements, beginning the cycle again.

10. SIX SIGMA Shewhart’s ideas and statistical concepts were embraced in clinical laboratories for several years for proficiency testing and quality control operations. Walter described the problem of reducing errors in a process in terms of process variation, which is also the deviation from the mean called ‘Sigma’ Many industries have re-discovered Shewhart’s methods and tools of statistical process control which is named as ‘Six Sigma’. 

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