SPC is an effective method to control processes but also the foundation for continuous improvement. This course provides participants with the basic statistical techniques and strategies for process control and improvement. Participants will gain knowledge of the fundamentals of process improvement, concept of variation, and statistical control, be introduced to statistical software, and learn other simple but powerful statistical techniques.
This course emphasizes the concepts that motivate and underlie the techniques along with practical advice for implementation so that the participant can effectively use these techniques on their own processes. In addition to on-line SPC, this course points out the use of off-line SPC as the foundation for more advanced data analysis methods.
Who Should Attend
This course is designed for engineers, quality professionals, researchers, and managers who need to understand and use statistical control methods.
Through training, participants will:
- Know the difference between common and special cause in order to correctly decide when an unwanted process change has occurred so that appropriate root cause corrective action can be taken.
- Identify specific areas of opportunity for SPC implementation within their companies
- Achieve an in-depth understanding of the concepts underlying SPC including using statistical software to gain information about center, spread, and shape to improve process characterization
- Examine the necessary steps in implementing effective SPC, including selecting the right SPC chart for their type of data and out-of-control action plans (OCAPs)
- Know how to apply the concept of capability so that continuous improvement actions can effectively be identified and efforts focused on centering, reduction of variation, or stability improvement
Fundamentals of Process Improvement and Concepts of Variation
- History of SPC/Concept of Loss
- Definitions of Statistics, Process, Control
- Stable versus Unstable Process
- Common versus Special Causes
- Four States of Process
Deriving Information from Data
- Attribute vs. Variables Data
- Measure of Location and Dispersion
- Empirical Rule/Normal Distribution
- How Averages Behave
Statistical Process Control Charts
- Concept Behind Control Charts
- Basic Variables Control Charts: Xbar-R, Xbar-S, I-MR
- Handling batched process with the I/MR/R Chart
- Basic Attribute Control Charts: np, p, c, u
- Subgrouping Techniques
- OOC Rule Selection
- Chart Critique and Interpretation
- Out-of-Control Action Plan (OCAP)
Effective Implementation Strategies
- Process Capability
- Capability for Attribute versus Variables Data
- Definitions of Capability Indices: Cp, Cpk, Pp, Ppk, Non-Normal Cpk
- Use and Abuse of Capability Indices
- Capability Graph and Selecting Appropriate Improvement Actions
Instructor-led class training, with opportunities to practice learned skills using prepared data, live demonstrations, and data collected real time in class
Minitab Statistical Software
Course Evaluations Set 1
Course Evaluations Set 2
Course Evaluations Set 3 – front
Course Evaluations Set 3 – back
Course Instructor: Saleha Yusof-Mullenix – Consultant, Statistical/Quality Methods and Six Sigma for Manufacturing and Research
8:30am-4:30pm (EST) each day
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