Statistical Process Control - Keys to Prevent Process Variation and Ensure Quality
Duration: 60 Minutes
Attend this session to understand the fundamentals of statistical process control, including its role in the proactive detection of process shifts that would otherwise cause nonconformances if not corrected.
Statistical process control (SPC) is a form of feedback process control that does for discrete manufacturing operations what automatic process control does for chemical process operations. The control chart reveals the presence of special or assignable causes that require corrective action, such as adjustment of the process by production personnel.
Objectives of the Presentation
Why Should you Attend
- Fundamental principles behind statistical process control, including variation and accuracy
- Difference between random or common cause variation and assignable or special causes
- Know how variation and accuracy affect quality
- Know how control charts reflect undesirable changes in variation and the process mean
- Understand the concept of the control chart as a statistical hypothesis test
- Understand the implications of the rational subgroup; a sample that reflects all sources of variation in the process
- Know the implications of processes that do not follow a normal distribution
- Off the shelf software (e.g. Minitab or StatGraphics) for handling complex variation and accuracy
- Understand why your control charts don’t seem to work properly—Excessive false alarms; points outside both control limits
William will introduce you to control charts that display how variation and accuracy can affect the quality of the manufacturing operations. You will be able to understand the concept of the control chart along with the implications of the rational subgroup.
Plus, get a link to a Visual Basic program (installable on Windows 7 systems) that teaches the concepts of variation and accuracy, along with their effects on control chart behavior. (A free copy will be provided to all attendees, licensed for use on one computer).
Who will Benefit
- Key concepts of variation and accuracy
- Concept of tampering or over-adjustment for random variation
- Hypothesis testing: null and alternate hypothesis, and associated risks of incorrect decisions about them
- Deployment of hypothesis tests about the process to control charts, which illustrate the tests visually
- The rational subgroup; does the sample reflect all variation sources in the process?
- Implication of non-normal (non-bell-curve) processes
- Setup and use of control charts
- VPs of Quality and Manufacturing
- Manufacturing engineers
- Quality managers, engineers and technicians
Statistical process control is a key quality management tool that tells production workers when a process has gone out of adjustment (special cause or assignable cause) in time to bring it back into control before it generates nonconforming work. It removes the guesswork from the decision as to whether to adjust the process or leave it alone, and avoids over adjustment (tampering) that can actually make matters worse. It is deployed to the production floor in the form of a control chart; a visual control that makes the status of the process obvious without the need to interpret tables of numbers or other data.