Control charts visualize the temporal course of measured variables, which either individually or in large numbers characterize the manufactured products. Control charts are usually used for process understanding. By collecting and statistically evaluating the process parameters which are determined, valuable insights can be gained into compliance with the quality of production and service processes. Control charts graph the deviations of process variables and allow conclusions to be drawn as to whether these deviations can be traced back to natural fluctuations or special causes.
Another term for control chart is statistical process control (SPC). These terms are used synonymously.
The American physician Walter A. Shewhart developed this tool in 1924 and used it for process optimization. The concept of the Shewhart control chart has become prevalent in many different contexts.
Increasing importance is being accorded to monitoring and controlling production processes. Globalization and the associated competitiveness are forcing companies to become more effective and efficient. For this reason, controlled processes, appropriately adapted or reduced inspection processes and inspection costs guarantee that cost targets will be achieved. This course offers insights into the statistical basics on the topic of SPC and clarifies the application and the benefits using plenty of practical and industry-related examples. An understanding of how to use control charts and how to interpret them is considered and taught in a pertinent manner. Thanks to this method, weak spots are visible in the process and these insights are integrated into optimization.
The two-day training
First of all, the two-day training looks at the basics of control charts and explains when processes are in control / out of control and capable / notcapable. Participants use suitable software (Minitab®) to produce control charts for normally distributed process data based on practical examples and work with the trainer to evaluate the results. As a result, the following questions can be answered:
- When do you need to intervene in the process to prevent rejects?
- What happens when you intervene in the process too early or when there are natural deviations?
- Which control charts are suitable to meaningfully document and visualize a process improvement that has been carried out?
- What are specification limits? What are intervention limits?
- What are rational subgroup samples and how can they be used to determine short- and long-term scatter?
- What is a control chart and what is it meaningfully used for?
Tips and informationon how to handle this correctly, and on errors and pitfalls as well, are then provided. The control chart is a tool used in relation to the measurement system analysis (MSA) and the process capability analysis (PCA).
On Day 2, special topics are looked at. In professional practice, it is quite common that process data are not normally distributed (yields, throughput times, etc.). Data is often available in counted form: Number of faults, faulty units.
For these cases, there are special control charts for process visualization.For particularly sensitive processes (food stuffs, chip manufacturing, security-relevantproducts, etc.) in certain circumstances even small deviations must be acknowledged. Moving-average control charts with and without weighting (MA, EWMA, CUSUM control charts) are used for this purpose.
The two-day training is rounded off with control charts for several output variables, which are related to one another, and for rare occurrences.
- Introduction to statistical process control with control charts
- Benefits and limitations of control charts
- The aim: capable and controlled processes
- Control charts for normally distributed data: X(transverse), I/MR control chart
- Control charts for abnormally distributed data: Data transformation
- Control charts for attributive data: p-, np-, c-, u-control chart
- Special control charts for special requirements
– Control chart for sliding averages; with and without weighting (EWMA)
– CUSUM control chart
– Multivariate control chart (when multiple outputs are available)
– Control charts for rare occurrences: g- and t-control chart
- Alternatives to control chart
- Pitfalls and misconceptions
- Information on the measurement system analysis and the process capability analysis
- Practical examples with suitable software (Minitab®)
The benefits of using control charts are clear: As well as documenting processes, deviations and shifts in the target values and often be detected before rejects occur.
- 2 days
- Extensive training documents in printed format
- Practical examples with data records from research, development, production, QA
- Photographic documentation of the flipcharts & workshops being presented
- Secure detection of deviation in the target values before rejects occur
- Reliable differentiation between natural and non-natural scatter
- Use of the results for process optimization