Accuracy, Precision, and Error Sources in Oil Analysis – 1-Day Customized Onsite Masterclass

$3,500.00

Accuracy, Precision, and Error Sources in Oil Analysis – 1-Day Customized Onsite Masterclass delivers practical tools for strengthening data integrity in condition monitoring programs. Participants will gain a working understanding of measurement accuracy and precision, with direct applications in viscosity testing, elemental spectroscopy, FTIR, and particle counting. The course equips attendees to recognize false positives, false negatives, and anomalies that compromise decision-making, while providing checklists and diagnostic methods for improving sampling, calibration, and laboratory communication. Case studies and exercises can be customized to reflect the challenges of power generation, petrochemical, or heavy industry environments, ensuring the training addresses sector-specific reliability needs.

Focus: Data integrity in condition monitoring and reliability.
What Participants Gain:

  • A clear understanding of measurement accuracy vs. precision, with applications in viscosity, elemental spectroscopy, FTIR, and particle counting.
  • Tools to recognize false positives, false negatives, and data anomalies in oil analysis reports.
  • Practical checklists and diagnostic methods to improve sampling, calibration, and laboratory communication.
  • Customization: Case material can be tailored to power generation, petrochemical, or heavy industry applications.
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Description

8-Hour OutlineSession 1: Foundations of Accuracy and Precision (1 hr)
  • Definitions with visual/quantitative examples
  • Systematic vs. random error
  • Why misinterpretation occurs in oil analysis
Session 2: Sources of Error in Oil Analysis (1.25 hr)
  • Sampling errors (technique, container, timing)
  • Instrument errors (calibration, drift)
  • Method and operator effects
Session 3: Laboratory Data Variability (1.25 hr)
  • Viscosity, elemental spectroscopy, FTIR, particle count
  • Examples of bias across labs
  • Exercise: identify anomalies in datasets
Lunch (1 hr)Session 4: Case Studies of Error Impact (1.25 hr)
  • False positives leading to unnecessary maintenance
  • False negatives masking failures
  • Group activity: diagnose error vs. real signal
Session 5: Diagnostic Approaches (1 hr)
  • Statistical checks for repeatability and validity
  • Cross-validation with complementary tests
  • Establishing acceptance limits
Session 6: Best Practices and Reliability Integration (1 hr)
  • Sampling protocols and checklists
  • Laboratory communication strategies
  • Integration into condition monitoring programs
Wrap-Up & Q&A (20 min)
  • Consolidated tools for error recognition and decision confidence

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