![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](https://image.slidesharecdn.com/shewhart-200302171111/85/Walter-A-Shewhart-8-320.jpg)
Walter A Shewhart
- 1. Walter A Shewhart By Ayshathul Femitha 9897 4th 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: Six sigma Statistical Process Control Reducing Variation – To Improve Quality Shewhart cycle (also know as the PDSA Cycle, PDCA Cycle)
- 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’.
- 11. THANK YOU