Advanced Statistical
Validation Engineering Path®
Applied Statistical Analysis for Medical Devices Validation Process | CORe®
Develop advanced statistical validation capabilities for regulated medical devices manufacturing. Designed to integrate risk-based evidence and audit-defendable analysis.
Statistics as a Critical Enabler of Validation Engineering
This program positions statistics not as an isolated academic topic, but as a critical enabler of validation decisions, technical rationale, and audit-defendable conclusions in highly regulated environments.
Objective Evidence
Establish undeniable technical evidence through rigorous data analysis across all validation phases.
Audit Readiness
Ensure every validation report is statistically justified and ready to withstand high-stakes regulatory audits.
Risk-Based Validation
Focus engineering efforts where they matter most, using data-driven risk assessments to optimize resources.
Aligned with Modern Validation Expectations
The program helps participants connect statistical tools with validation decisions across IQ, TMV, OQ, PQ and Continued Process Verification.
VMP / PMV
Validation Master Plan statistical integration.
Data Integrity
Statistical data governance standards.
PQ Capability
Ppk and Cpk for medical manufacturing.
CPV
Continued Process Verification roadmap.
Integrated Across the Validation Lifecycle
Each module connects statistical methods with the technical decisions required throughout the process.
92-Hour Advanced Capability Development Path
A comprehensive journey through engineering statistics for the modern medical devices sector.
Statistical Foundations for Validation Engineering
Core focus: IQ, TMV, OQ, PQ application. Establishing the visual and mathematical baseline for objective evidence.
Content
- • Data visualization & VST by BB&Cross®
- • Descriptive and inferential statistics
- • Comparative tests & Rationale
- • Sample size fundamentals
Applications
- • Validation data evaluation
- • Technical acceptance support
- • Objective evidence justification
Regression Modeling & Machine Learning
Core focus: OQ and PQ optimization. Modeling critical variables to predict and control manufacturing outcomes.
Content
- • Simple and multiple regression
- • Stepwise regression & CART
- • Supervised Machine Learning foundations
- • Predictive analytics for validation
Applications
- • Reflow oven critical variables
- • AOI and defectology variables
- • Process performance modeling
SPC & Capability
Mastering stability and capability (Cp, Cpk, Pp, Ppk) for CPV and PQ readiness in non-normal environments.
REQUEST INFO →TMV & Reliability
Measurement Reliability, Attribute Agreement Analysis and automated system validation for visual inspection.
REQUEST INFO →DOE & Experimental
Full/fractional factorial DOE, Monte Carlo simulation and RSM for optimizing wave solder and reflow processes.
REQUEST INFO →Capabilities Participants Will Develop
Designed by Blackberry & Cross®
Helping organizations strengthen technical capability beyond traditional training.
TRAAC® Methodology
Applied learning methodology designed for industrial results.
Minitab-Powered
Practical workshops utilizing industry-standard software tools.
Industry Context
Examples specific to SMT, Reflow, AOI and Medical assembly.
Mentoring Options
Available coaching to support real-world validation deliverables.