Overview:        
The basic philosophy and tools of Statistical Process Control (SPC) are now well over seventy years old. They arose in an era of data scarcity and production that was manually performed and controlled. However, times have dramatically changed. Automated processes, high-volume data collection and storage, ever-increasing computational capability, powerful and user-friendly statistical software, and increased off-shore manufacturing are now the norm. They present challenges as well as opportunities for new and improved SPC applications. The popularity of "Six Sigma" performance improvement programs has demonstrated that the need for very high quality processes, both manufacturing AND non-manufacturing, as well as continuous process improvement has only intensified. Indeed, the core principles underlying the birth of SPC - the measurement and reduction of variability - are as valid today as they were seventy years ago.

How You Will Benefit:
By the end of the course, participants will have gained:

• A firm grasp of the essential concepts and tools of SPC;
• Motivation and confidence to actively apply standard SPC methods in process improvement and control initiatives in their work environment;
• Insight into how SPC needs to be implemented effectively in common "non-standard" processing environments;
• Awareness of a variety of proven and innovative SPC techniques useful in non-standard processing contexts.

Course Outline:

Day 1

• The Quality Imperative in the 21st Century
  • The Role of SPC in Process Quality Management
• Ten Principles of Variation
  • Describing Variation: Statistical & Graphical Methods
  • Types of Variation: Common, Special, & Systematic/Structural
• Control Charts for Variables Data: Classic SPC
  • Xbar & R, Xbar & S Charts, Individuals Charts
  • Methods of Control Chart Construction & Modification
  • Rules for Chart Interpretation
  • Three Stages of Control Chart Use
• Rational Sub-grouping
  • How to Correctly Sample for Control Charts
  • Identifying the Right Chart for Your Data
• Control Charts for Attributes -
  • p-, c-, u-charts
  • Individuals Charts

Day 2

• Process Capability:
  • Indices and Assessment Methods
  • Dealing with Non-normal Data
  • Sampling and Sample Size issues
• Modern SPC Applications:  Common Problems & Solutions
  • Short Production Runs
  • Non-Normal Data - Autocorrelated Data
  • "Drifting" Processes
  • Very Low Failure Rate Processes
  • Complex Sampling & Batch Processing
  • High-volume Sampling
  • Multi-Characteristic Processes
• Control Plans: Requirements for Successful SPC Implementation

Who Should Attend:
Managers, engineers, or personnel in manufacturing, engineering, quality assurance, or related disciplines who are responsible for quality or productivity improvement initiatives or SPC implementation in their organizations. Prerequisites No pre-requisites are necessary for course participation, although previous exposure to basic statistical concepts is helpful.

Cost:
Two-day course cost: $600 per student for members and $700 per student for non-members.  Tuition includes: class, bound presentation, and lunch for both days.
Please register for this class through Day 1 of 2 posting.

Instructor Bio:  Don Lewis Ph.D.
Don Lewis is Principal, Lewis Consulting LLC, whose mission is to enable clients to improve their competitive performance through effective application of proven quantitative decision-making methodologies.  Since establishing his consulting practice in 1986, Don has trained and mentored over five thousand technical professionals to apply quantitative methods, such as Statistical Process Control and Design of Experiments, in their project work.  His consulting experience accrues from 50+ organizations across a diverse group of industries, including biosciences.  Clients have achieved significant performance improvement, including proprietary breakthroughs, as a result of implementing his services.

Recently, as a Lead Instructor in Motorola University’s Digital Six Sigma Black Belt training program, Don has trained over two hundred and fifty Motorola Black Belts throughout the U.S., Europe, and Asia.  Since 2003 his Northwest Lean Six Sigma clients have saved over $16 million in project work completed in conjunction with his training programs.  He is an Adjunct Professor in both the Department of Management of Science & Technology at the OGI School of Science & Engineering in Portland, Oregon and the Atkinson Graduate School of Management at Willamette University.  Don is also a chapter author of the recently published "Encyclopedia of Statistics in Quality and Reliability."  He received his B.A. in mathematics from Claremont McKenna College and Ph.D. in biostatistics from the University of North Carolina at Chapel Hill.  Don is an ASQ Certified Six Sigma Black Belt.