![Control Charts ,[object Object],[object Object]](data:image/gif;base64,R0lGODlhAQABAIAAAAAAAP///yH5BAEAAAAALAAAAAABAAEAAAIBRAA7)
Recommended
More Related Content
What's hot
What's hot (20)
Similar to Control charts[1]
Similar to Control charts[1] (20)
Recently uploaded
Recently uploaded (20)
Control charts[1]
- 1. Control Charts Training Slides 02/19/01
- 18. Examples of Control Charts
- 19. Examples of Control Charts
- 21. Example of Control Charts
Editor's Notes
- A simple basic definition that can be built on to service your company’s needs.
- http://deming.eng.clemson.edu/pub/tutorials/qctools/ccmain1.htm#History “ Dr. Shewhart developed the control charts as an statistical approach to the study of manufacturing process variation for the purpose of improving the economic effectiveness of the process. These methods are based on continuous monitoring of process variation.”
- These are the main to types of control charts. Each type has several specific charts that deal with a specific sample set of data.
- Use variable charts should be used whenever the data is something that is measured. The data should be for example the weight of a piece of candy.
- The main types of variable control charts are listed above.
- These are the definitions of the specific types of variable control charts. This will help in determining what type of chart to use when you are collecting sample data.
- Definition of attribute control charts. Tests the quality of the specific attributes of a product.
- The main types of attribute control charts are listed above.
- The definitions of the attribute control charts, help in determining the correct chart to use given a sample set of data.
- Control charts can be a huge asset to a company if used correctly. The reason for using control charts are clear, they will help your company improve.
- Real world example of a company that uses control charts to sell products to the United States. The products must be defect free to save lives.
- Brainstorming Activity: This is to help your employees realize the need to improve. The goal with control charts is basically three fold: Reduce Defects Improve processes Improve productivity
- This is just a list of key terms that one should know and understand to create a control chart and understand its results.
- There are other extreme examples of when a control charts is out of control but these are the main three that you should focus one.
- If your process is currently in control continue to monitor it to insure that productivity remains at a high level to produce good quality products.
- The control chart basically consists of three main lines. The center of mean line, and then the two control limits. This lines are called the Upper Control Limit, and the Lower Control Limit. They both can be shortened (UCL,and LCL).
- http://www.robertluttman.com/vms/Week5/page6.htm Statistical Thinking Tools-Control Charts for the Average Date:February 12, 2001 Bob Luttman, Robert Luttman & Associates Example of a control chart that has points outside the UCL. This process may need to be reworked. The problem is becoming worse, you can see that the data is consistently above the mean towards the end of the data.
- Processes and Process Variability, Date accessed: Feb 12, 2001 http://www.sytsma.com/tqmtools/ctlchtprinciples.html Example of a process that is in-control.
- Process improvement.
- Processes and Process Variability, Date accessed: Feb 12, 2001 http://www.sytsma.com/tqmtools/ctlchtprinciples.html The control chart above shows the improvements that a firm made in their process to improve quality.
- Formula for computing the standard deviation for a P-chart.
- The control limits can be computed by multiplying the standard deviation by +/- 3.
- The procedure to calculate the upper and lower control limits for a X-Bar chart. Follow the formula provided, your should remember to make sure that you are using a sample size greater than 28. http://www.statlets.com/usermanual/sect7_3.htm 7.3 Control Charts for Variables Date Accessed: February 13, 2001
- Building a R-chart. The slide helps in computing the three main lines in the chart. http://www.statlets.com/usermanual/sect7_3.htm 7.3 Control Charts for Variables Date Accessed: February 13, 2001
- The most important thing to remember when constructing a control chart is to have a sample set greater than 28. If your set is smaller that 28 you may not be able to represent a large enough portion of data to get accurate results.
- Follow the steps to insure that the control chart will produce the outcome that you are looking for. A control chart is useless if the wrong chart is used for the wrong type of data.
- Practice designing a chart. Use the steps outlined in slide show.
- You should use a Attribute control chart because the data is in percent form.
- After determining that the sample set should use a attribute control chart? Determine the correct type of chart to use in creating a control chart. (p-chart) Because it is the percent defect or errors of a sample set.
- Reinforcing the idea that you sample set must be greater than 28.
- First: Notice the sample size Second: Calculate the mean (.056786) Third: Use the mean to calculate the control limits (UCL: .07442 ), (LCL: .03914) ) Plot the points and determine if you process is capable: I would say that this process is pretty much capable, only a few points are outside the control limits
- Determine if your process is capable by looking at your results and determining if your process needs changes.
- What to do after you design the chart and look at the results. Make the chart work for you. Like it help your company improve quality.
- Summary, the control chart can greatly improve your company’s profits and process capability.