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Statistical Capability and Control Methods for CAE Processes

30 Chapters
View Course Samples Online
01
CAE process variation
sources, impact on simulation fidelity, and the need for statistical capability assessment.
CAEvariation
02
Statistical foundations for CAE
distributions, sampling, confidence intervals, and hypothesis testing in simulation contexts.
Statisticalfoundations
03
Process capability indices (Cp, Cpk, Pp, Ppk) for CAE outputs
definitions, assumptions, and interpretation.
capabilityCAE
04
Establishing specification limits for CAE results
tolerance allocation, design requirements, and customer-driven targets.
Establishingspecification
05
Measurement systems analysis for CAE
verification, validation, and uncertainty quantification of simulation models.
Measurementanalysis
06
Data collection strategies for CAE process capability
sampling plans, run order, and replication.
collectionstrategies
07
Normality assessment and transformation methods for CAE response data.
Normality assessment and transformation methods for CAE response data.
Normalityassessment
08
Capability analysis for non-normal CAE outputs
alternative indices and robust methods.
Capabilityanalysis
09
Multivariate capability analysis for correlated CAE responses.
Multivariate capability analysis for correlated CAE responses.
Multivariatecapability
10
Statistical process control (SPC) fundamentals for CAE workflows
control charts for simulation outputs.
StatisticalSPC
11
Control chart selection for CAE processes
X-bar, R, S, I-MR, and multivariate charts.
selectionCAE
12
Phase I analysis
establishing baseline control limits from historical CAE runs.
analysisestablishing
13
Phase II monitoring
detecting shifts in CAE process performance.
monitoringdetecting
14
Dealing with autocorrelation and non-independence in CAE simulation time series.
Dealing with autocorrelation and non-independence in CAE simulation time series.
autocorrelationnon-independence
15
Process stability assessment
run rules, trend detection, and out-of-control action plans.
stabilityassessment
16
Capability and control integration
linking SPC signals to capability degradation.
Capabilityintegration
17
Design of experiments (DOE) for CAE process improvement
screening, characterization, and optimization.
experimentsDOE
18
Variance component analysis in CAE
partitioning variation from input parameters, mesh, and solver settings.
Variancecomponent
19
Tolerance interval estimation from CAE results for robust design.
Tolerance interval estimation from CAE results for robust design.
Toleranceinterval
20
Reliability and confidence in CAE-based capability estimates
sample size and power considerations.
Reliabilityconfidence
21
Case study
capability assessment of a structural FEA process for stress predictions.
capabilityassessment
22
Case study
SPC implementation for a CFD simulation workflow in thermal management.
SPCimplementation
23
Case study
multivariate capability analysis for crashworthiness CAE outputs.
multivariatecapability
24
Case study
capability and control of an optimization loop in CAE-driven design.
capabilityoptimization
25
Software tools for statistical capability and control in CAE
Minitab, JMP, Python/R integration.
Softwarestatistical
26
Automating capability and control charts in CAE pipelines
scripting and dashboards.
Automatingcapability
27
Reporting and communication of CAE process capability to stakeholders.
Reporting and communication of CAE process capability to stakeholders.
Reportingcommunication
28
Auditing and compliance
statistical evidence for CAE process validation.
Auditingcompliance
29
Common pitfalls and best practices in CAE capability studies.
Common pitfalls and best practices in CAE capability studies.
pitfallspractices
30
Future trends
machine learning for anomaly detection and adaptive control in CAE processes.
detectionadaptive