Statistical Process Control
(including Capability Analysis)
Two Day Training Course
Statistical process control (SPC) is used to monitor two types of manufacturing industry data; (a) measurements (variables) data, and (b) non-measurement data (attributes).
Statistical process control for measurements (variables) can be considered as essentially two separate but closely related subjects, namely (a) process capability analysis, and (b) control charts. Process capability is the ability of a manufacturing operation to
produce product within specification, and the calculation of the capability indices, Cp/Cpk and Pp/Ppk is widely practised in industry. However, control charts are not as widely used as they should be, and the role of the control chart is not well understood. The primary function of the control chart is to ensure, as far as is possible, that the process mean remains on target, in a stable condition, and it is important that personnel with responsibility for operating processes understand the important role that control charts play in assuring optimum capability.
Statistical process control for attributes is used to monitor the percentage of nonconforming product, or rate of occurrence of defects, in the manufacturing operation. The control chart for attributes provides personnel with responsibility for quality of product with crucially important information, which will assist them in controlling and reducing the incidence of defects.
On successful completion of this training course, delegates should be able to:
- Undertake capability analysis, including analysis of non-normal data, and understand the meaning of the indices Cp/Cpk and Pp/Ppk
- Implement statistical process control methods in production
- Construct and interpret control charts for variables and attributes
- Demonstrate understanding of the important relationship between capability analysis and process stability as observed on control charts
- Use Minitab software for data analysis and identifying trends
Who Should Attend
- Product managers and team leaders
- Quality engineers, process engineers and technicians
- Staff concerned with controlling manufacturing processes
Participants don’t require a prior knowledge of statistics as the course will commence with a session on basic statistics. However, having knowledge of mathematics, for example Pass Leaving Certificate level, will be helpful in understanding the statistical concepts presented on the course.
- The objectives and benefits of SPC – assessing process performance, distinguishing special from common causes
- Introduction to Statistics Underlying SPC
- Variation in manufacturing processes and its causes; Calculation of basic statistics including standard deviation
- The normal and standard normal distribution and use of the normal tables to calculate tail values
- Sampling distribution of the mean
- Process Capability Analysis
- Conducting process capability studies – identifying characteristics, specifications, and/or tolerances
- Distinguishing between natural process limits and specification limits, and calculating process performance metrics including percent defective and PPM
- Calculating process capability indices Cp, Cpk, capability ratio, and assessing process capability
- Calculating process performance indices Pp and Ppk and assessing process performance
- Process capability analysis involving nonnormal data:
o Using Box-Cox and Johnson transformations
o Fitting nonnormal distributions such as Weibull, Smallest Extreme Value and Largest Extreme Value
- Variables Control Charts
- Identifying and selecting characteristics for monitoring by control chart
- Rational subgrouping
- Construction and interpretation of the X-bar and R chart. Distinguishing between common and special causes using the rules for determining statistical control
- Individual and moving range charts
- The role of control charts in optimising capability – explanation of how the differences between Cp/Cpk and Pp/Ppk arise.
- Attributes Control Charts
- The four attributes control charts; p, np, c, and u charts and when it is appropriate to use them
- Laney p’ and Laney u’ charts to be used when the sample size is very large
- The advantages/disadvantages of attributes control charts versus variables control charts.
- Interpreting the charts using the rules for determining statistical control
Minitab will be demonstrated as part of the training. Delegates are invited to bring a laptop loaded with either Minitab 16 or Minitab 17 and they will work through several Minitab exercises throughout the two days of the course. A free 30 day trial version of Minitab 17 is available on www.minitab.co.uk. The course will also be beneficial to delegates who are not in a position to bring a laptop with Minitab.
Albert Plant is a chartered engineer (FIEI) and has a B.Sc. degree in statistics. He has twenty years experience training and consulting in SPC. His work is in the pharmaceutical and medical devices industries, food industry, electronics, automotive parts, and other manufacturing. Albert has used Minitab software since 1994. He is a volunteer tester for Minitab on new versions and he was involved in testing version 17 of Minitab in 2013.
Testimonials Click Here
Course Times 9.00am - 5.00pm
Public Course Cost €790 (includes course documentation, lunch and refreshments)
For In-House courses, the tutor will contact you in advance to discuss the course programme in more detail in order to tailor it specifically for your organisation.
Delegates will receive a very comprehensive course manual written by the course tutor, which explains the statistics underlying SPC and worked examples of the calculation of process capability analysis and the calculation of control chart limits. The worked examples in the public course manual are based on actual practical data from Irish manufacturing plants where SPC is in daily use. For In-House training the manual will be prepared using data collected in advance from the company, and the participants will undertake exercises in the manual using their own workplace data.