Continue building a strong foundation in Six Sigma Statistical Process Control with this two-day course
This two-day Statistical Process Control (SPC) workshop builds on the concepts from the Introduction to Statistical Methods workshop (SS502). This course teaches students the next level of methodologies that will increase their ability to account for differences in processes while learning the best methods for managing their processes for control and continual improvement. As with the introductory course on statistical methods, this course is invaluable for Six Sigma DMAIC improvement projects and Design for Six Sigma (DFSS) projects, Lean Six Sigma implementations, Business Process Management, Quality Management, Supplier Quality Management, or Statistical Process Control (SPC) and Statistical Quality Control (SQC).
The quality of this course offering is one of the key differentiators between NWCPE’s certified Six Sigma Green Belt and Six Sigma Black Belt programs versus lesser valued Six Sigma instruction. Six Sigma certified Green Belts, and Black Belts will become well equipped to manage basic and complex DFSS and DMAIC process improvement projects. Students will also leave this course with the SPC charts and SPC tools to manage and coach full statistical process control (SPC) and Statistical Quality (SQC) implementations, as well as the ability to manage business process analytics systems for world-class operational excellence.
- How to select, construct, use, and interpret Statistical Process Control (SPC) charts –Xi/MR, Xbar/R, P, nP, U, C, MA and EWMA charts – and then design data collection strategies for spotting trends, or other types of changes to processes, for a wide-array of process situations
- How to assess the process capability to meet the requirement and how it is performing relative to requirements for attribute data
- How to implement SPC tools and SPC software for process analysis to assure the effectiveness of day to day operations and manage Six Sigma, Lean or Lean Six Sigma design and improvement projects
- Ability to apply the methods to SQC and SPC implementations
- Ability to recognize when and how to implement the methods to business analytics for business process analysis and management
- Participants receive free time-limited versions of software for conducting measurement system analysis and general statistical analysis
Day 1 — Process Control Charts for Means (XBAR) & Ranges (R)
- Review of basic stats and statistical process control tools and concepts
- The importance of assumptions about the distributions and patterns of common cause variation and how to identify it
- Benefits of working with averages (Xbars) for process control — the central limit theorem
- Control charts for plotting averages (means) and ranges — Xbar / R control charts
- Control chart construction, interpretation, and protocols for reacting to them
- When, how and how not to apply Xbar/R control charts
- How to sample for effective Xbar/R control charts
Day 2 — Choosing the Right Charts & Sampling Procedures, Attribute Charts
- Data types — variable data versus discrete or attribute data
- Control charts for attribute data, when and why to use, the four — P, nP for defectives or non-conforming process outputs, and U and C for defects or errors
- Moving (Rolling) Average Charts when trends are as important or more important than the performance for a single measurement
- Exponentially Weighted Moving Average Charts (EWMA) for identifying subtle but important trends, for dealing with non-normal data, and accounting for the frequency of events as well as the magnitude of special cause variation
- Process capability for attribute data such as proportion defective or average defect rates
- Summary of when to use what control chart, the role of each, and how to sample and treat the data
- The design of process and quality control plans
- SPC and SQC implementation and what everyone should know about SPC tools
- Application of control charts to DFSS and DMAIC projects, SQC, SPC and business process management and Supplier Quality Management
Upon completion of this two-day workshop, participants will understand the fundamental principles behind Six Sigma statistical process control with the ability to apply the methodologies learned in the classroom to a variety of real-world process challenges.
What Career Paths Benefit the Most From Introduction to Statistical Process Control Workshop?
- Process owners for any type process or anyone who is responsible for developing processes and process analysis, performance management and reporting
- People working with manufacturing or non-manufacturing process analysis, management, and improvement
- Engineers, quality managers, engineers and technicians, manufacturing personnel, and non-manufacturing staff who will select and implement SPC tools for manufacturing and business process management
- Supplier quality engineers for assuring supplier quality especially when it applies to the Product Part Approval Processes (PPAP) or the equivalent
- Six Sigma Green Belt certification candidates and Six Sigma Black Belt certification candidates managing DMAIC or DFSS projects
- Product development engineers, especially those who regularly perform statistical analysis as part of Advanced Product Quality Planning (APQP) or equivalent product development protocols
- Managers for organizations that aspire to world-class operational excellence
Additional Course Notes
Customized and on-site versions of this course are available for organizations desiring to target specific groups or objectives. Examples include: Overview for management, including how to lead successful implementation of SPC and SQC; administrative personnel with an emphasis on how to use SPC methods most suited to their objectives and optimizing how their processes function; equipment operators with a focus on interpretation and how to react to control chart signals; quality and process engineers with an emphasis on the nuances of control chart selection, application, and sampling method design; sales and marketing personnel wishing to more effectively interpret trend data; analysts responsible for initiatives to implement analytics in their organization, with an emphasis on the analytical value of control charts and complementary methods.
Prerequisites: Introduction to Statistical Methods to Manage & Improve Processes (SS502) or the equivalent knowledge is a prerequisite. Specific equivalent experience includes knowledge and understanding of basic statistics – common and special cause variation, histograms, box and whisker plots, the normal distribution, sample statistics and population parameters, run charts, individuals and moving range charts, process capability, and performance measurement for variable data.
Credit & Follow-Up
Participants who complete this course successfully will earn credit toward Lean and Six Sigma Green and Six Sigma Black Belt certification. Participants completing the course will earn the right to return to audit free of charge when the course and classroom space is available.
Credits: 1.5 CEUs