Day 1: Course Overview and Introductory Concepts
- Course Overview
- Course outline
- Introductions
- The Industrial Revolution
- Mass production
- Division of labor
- Taylorism
- Typical engineering drawing and specification practices
- Engineering tolerances historical contexts
- Typical engineering drawing tolerance responsibilities
- Manufacturing Processes
- Process capabilities
- Process capability versus engineering tolerances
- Deterministic versus Probabilistic Thinking
- Typical test and inspection approaches
- Typical build-and-inspect approaches
- The psychology of inspection
- Product quality responsibilities
- The sampling approach and its pitfalls
- Detection versus prevention management philosophies
- Driving blindfolded
- Introduction to Statistics and Probability
- The nature of variability
- Shewhart’s formative work
- Frequency distributions
- Histograms
- The normal curve, means, and standard deviations
- Normal curve mathematics
- Averages of averages and the central limit theorem
- Statistical Process Control
- SPC overview
- SPC basic concepts
- SPC control in World War II
- The US rejection of SPC after World II
- Japan’s SPC acceptance after World War II
- SPC success stories
- Placing product quality responsibility in the operator’s hands
- Statistical Process Control Concepts
- Inspection shortfalls
- Attributes versus variables data
- Placing quality responsibility in the hands of the operator
- xbar:r charts
- SPC capabilities
- Class exercise
Day 2: SPC Implementation
- Training
- Management training
- Supervisor training
- Operator training
- Selecting Processes for SPC application
- Variables data opportunities
- Optimizing early successes
- Defining the process
- Flowcharting
- Assessing existing test and inspection points
- Selecting critical characteristics for SPC application
- Identifying critical dimensions
- Identifying sources of variability
- Ishikawa charts
- Minimizing variability
- Case study
- Class exercises
- Gathering SPC Preliminary Data
- Collecting data for establishing upper and lower control limits
- Calculating upper and lower control limits
- Defining subgroups and calculating averages
- Class exercise
- Preparing, Maintaining, and Using Charts
- xbar:r charts
- Typical xbar:r charts required information
- Collecting individual data points
- Calculating average values
- Finding the range
- Defining nominal and upper and lower control limits
- Plotting averages, ranges, and the grand average
- Finding the standard deviation
- Using Excel to simplify xbar:r calculations
- Finding the average range
- Finding upper and lower control limits for the range
- Simplified approaches for determining upper and lower control limits
- Class exercises
- p-Charts
- Attributes data applicability
- Converting attributes data to variables data
- The nature of p
- Finding the average p
- Finding p upper and lower control limits
- Using the average p and upper and lower control limits to create a p chart
- Class exercises
Day 3: Putting SPC To Work For Your Organization
- Using SPC Charts
- Plotting process data on SPC charts
- Noting process changes
- Identifying trends
- Shifting responsibility to the operator
- Class exercise
- SPC Trend Analysis
- No trend
- Subgroup averages trending upward or downward
- Multiple points above or below the average
- Cyclical patterns
- Range changes
- Calling for help when trends are recognized
- Class exercise
- SPC Implementation Challenges
- Resistance to change
- Inspector job security
- Seeking input from affected personnel
- Selecting initial SPC-implementation points
- Maintaining momentum
- Publicizing success
- Course Review and Wrap-Up
- Wrap-up.
- A suggested Statistical Process Control implementation roadmap.
- Course critique.