Statistical Process Control Training
| Commitment | 3-4 days, 7-8 hours a day. |
| Language | English |
| How To Pass | Pass all graded assignments to complete the course. |
| User Ratings | Average User Rating 4.8 See what learners said |
| Price | Call |
| Delivery Options | Instructor-Led Onsite, Online, and Classroom Live |
Course Overview
Statistical Process Control Training Course – Hands-on
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Course Details:
Statistical Process Control Training Course – Customize it
- We can adapt this training course to your group’s background and work requirements at little to no added cost.
- If you are familiar with some aspects of this training course, we can omit or shorten their discussion.
- We can adjust the emphasis placed on the various topics or build the training around the mix of technologies of interest to you (including technologies other than those included in this outline).
- If your background is nontechnical, we can exclude the more technical topics, include the topics that may be of special interest to you (e.g., as a manager or policy-maker), and present the training course in manner understandable to lay audiences.
Statistical Process Control Training Course – Audience/Target Group
The target audience for this training course:
- All
Statistical Process Control Training Course – Objectives:
Upon completing this training course, learners will be able to meet these objectives:
- Develop an effective Statistical Process Control system.
- Objectively identify Statistical Process Control opportunities.
- Work together to implement and improve your Statistical Process Control program.
Course Syllabus
Statistical Process Control Training – Course Content
Day 1: 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 ChartsPlotting 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
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Great content; real-world examples and stories. Instructor had excelle