• Learning Track

    Medical Devices

    This 4-day track provides participants with the foundation for effectively using statistical methods to analyze, improve, and validate manufacturing processes.

    It is appropriate for process engineers, R&D team members, and other quality professionals who need to understand how to apply statistical tools to a medical device process.

    Explore the data analysis techniques necessary to understand variation and defects, assess if a process is capable of meeting customer specifications, and monitor the stability of a validated process.

    Statistical principles will be presented through examples and exercises ― all supported by Minitab Statistical Software.

    Schedule On-Site Training   Find Public Sessions
  • Days 1-4
  • Statistical Tools for Medical Devices

    Manufacturing

    Learn to apply Minitab tools commonly used in the medical devices industry. Develop sound statistical approaches to data analysis by understanding how to select the right tool for a given scenario and correctly interpret the results. Learn how to easily import data and export output.

    Learn the foundation for important statistical concepts for determining if a process mean is off target, whether two means are significantly different, and for demonstrating if a process change does not significantly affect a critical response. Develop the necessary skills to successfully evaluate and certify measurement systems. Understand how to utilize important capability analysis tools to evaluate your product quality relative to internal and customer specifications. Learn how to evaluate a random sample of product from a lot in final inspection to determine whether the lot of product should be shipped. Understand how to apply DOE for improving critical to quality characteristics.

    All applications place emphasis on making good business decisions based upon the practical application of statistical techniques commonly used in the medical device industry.

    Topics include:

    • Importing and Formatting Data
    • Bar Charts
    • Histograms
    • Boxplots
    • Scatterplots
    • Power and Sample Size Determination
    • t-Tests
    • Equivalence Tests
    • Proportion Tests
    • Tolerance Intervals
    • Variables and Attribute Control Charts
    • Regression
    • One-Way ANOVA
    • Multi-Variable ANOVA
    • DOE
    • Attribute Agreement Analysis
    • Gage R&R
    • Attribute Acceptance Sampling
    • Capability Analysis for Normal and Nonnormal Data

    Prerequisite:

    None. This course can be used as a pre-requisite to Response Surface Designs and DOE in Practice.

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