Watch Now 18:03
Evaluating & Monitoring Your Process Using MSA and SPC
Presenter: Jerry Fish
Quantifying Measurement System Variation and How it Impacts Your Process
See how to:
- Understand basic measurement system evaluation principles
- Understand purposes and types of Gauge Studies
- Understand considerations for conducting a Gauge Study: Random part order, time of day, operator confidentiality, following standard procedures, monitoring but not interfering with tests
- Perform Continuous Gauge Study
- Interpret Variability Gauge Chart, Gauge R&R Measurements, Variance Components for Gauge R&R
- Run Crossed Tests
- Select tolerance intervals or specifications (LSL and USL)
- Perform Attribute Gauge Study
- Interpret Gauge Attribute Chart, Agreement Reports
- Use EMP method to achieve an interclass correlation perspective for classifying a measurement system
- Interpret Range Charts, Parallel Plots, EMP Results, Gauge Classification
- Understand purpose of Process Screening: To determine if process is steady, stable and predictable so you can use it to monitor future performance and/or evaluate impact of changes on the process
- Examine Voice of Process: Is process in control and exhibiting minimal variance?
- Examine Voice of Customer: Is process yielding good/best parts that are within specification?
- Use Control Chart Builder to examine process capability
- Interpret Individual and Moving Range Charts, Limit Summaries, XBar and R Charts, Process Capability Analysis
- Understand purpose of Multivariate Control Charts introduced in JMP 15: To identify two or more interrelated process variables where the interrelation might impact process capability although the individual processes might appear in control
Process Monitoring (from live webinar archive)
The presenter describes the two phases of process monitoring: Phase 1 for characterizing the common cause variability in a system, and Phase 2 for setting up a monitoring approach to identify assignable causes with a stated level or risk. He demonstrates how to use JMP to examine Shewhart variables, rare event charts, attribute charts, multivariate charts using Hotellings T-squared distribution, and more.