ISO 16949 certification and  Measurement Systems Analysis (MSA) trainingStatistical Process Control (SPC) and Measurement Systems Analysis (MSA)

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As well as being core components of the Six Sigma approach, Statistical Process Control (SPC) and Measurement Systems Analysis (MSA) are also key elements of ISO/TS16949, where it is required to be used within the Product Realisation process.

Many problems encountered with Statistical Process Control (SPC) and Design of Experiments (DOE) are caused by problems with measurement systems where the process of obtaining measurements and data may have variation and produce defects.

Statistical Process Control is an optimisation philosophy concerned with continuous process improvement, using a collection of (statistical) tools for data and process analysis making inferences about process behaviour. SPC is a key component of Total Quality initiatives and ultimately SPC seeks to maximise profit by improving product quality, improving productivity, streamlining process, reducing wastage and reducing variation.

Measurement Systems Analysis evaluates the test method, measuring instruments, and the entire process of obtaining measurements to ensure the integrity of data used for analysis (usually quality analysis) and to understand the implications of measurement error for decisions made about a product or process.

Course Objectives

Delivered in-house, this interactive and practical course will provide delegates with a basic knowledge of the principles of SPC and MSA and the methodologies for performing capability and measurement systems studies with respect to bias, linearity and stability. Our course is highly practical and avoids detailed knowledge or discussion of statistics.

Key Skills / Learning Objectives

Through the combination of interactive tutorials and workshops, our course will enable the delegates to:

  • Use MSA to determine the suitability of measurement systems.
  • Perform a capability study and generate and utilise SPC Xbar R charts.
  • Perform a Repeatability and Reproducibility (R&R) study.
  • Interpret the results in the context of the process variation and product acceptance criteria.
  • Use the data to improve the effectiveness of the measurement system.

Course Outline

SPC - Introduction, concepts of variation, control charts and process capability

  • The existence and measurement of variation
    • Concepts
    • Variation
    • Data tables, histograms and run charts
    • Normal Distribution
    • Accuracy and Precision
    • Measures of variation (mean, mode, median, range, standard deviation and variance)
    • The standard deviation
  • Understanding and Managing Variation
    • Common and special causes
    • Taking appropriate action on common and special causes
    • Process improvement methodology
    • Reacting to special causes
    • Statistical Control, what it is, and the advantages of processes being in control vs tampering with the process
  • Role of control charts
    • Role and uses and definition of control charts
    • Drawing and interpreting control charts
    • Keeping control charts up to date
    • Types of control chart
  • X-Range charts
    • Use of charts
    • Preparation and use of control chart
    • Examples
  • Attributes Charts
    • c, p, np and u charts (overview)
    • Examples
  • Capability Analysis
    • Process capability (Cp, Cpk)
    • Performing a process capability study

MSA - Overview of methodologies and use of data

  • Concepts of MSA
  • Measurement system elements and their contribution to measurement variation
  • Terminology and concepts (bias, linearity, stability, repeatability and reproducibility)
  • The statistical requirements of a measuring system
  • MSA Studies
  • Bias (overview and methodology)
  • Linearity (overview and methodology)
  • Stability studies (overview and methodology)
  • Measurement Uncertainty (overview)
  • Measurement system analysis and studies (variable and attribute)
  • Repeatability and Reproducibility
  • Performance of a gauge R&R study
  • Interpretation and use of study data (from example data provided)
  • Using data for cost-saving (calibration intervals, number of measurements taken etc)

Additional Core Tools relating to the Automotive industry include: Advanced Product Quality Planning (APQP) and Production Part Approval Process (PPAP); Failure Mode & Effects Analysis (FMEA)

Who Should Attend?

  • Quality professionals, Six Sigma change agents, lean practitioners and support staff who require a basic understanding of Measurement system evaluation techniques and Statistical Process Control tools and techniques.
  • Personnel with responsibility for design / process engineering who should be requiring MSA studies to help them specify tolerances, production processes and acceptance criteria, and need to understand the information when it is presented.
  • Those who are required to support MSA studies, but are not directly responsible for the analysis.
  • In house "experts" who need to plan and execute MSA studies and will become the "champions" for the appropriate use of MSA to drive continuous improvement and influence senior management.

Booking and Course Fees

Fees include:

  • Delegate workbook, including reference information
  • Training provided by qualified and experienced tutors with extensive practical management auditing experience across a variety of manufacture and service industries
  • Certificate verifying attendance and completion of course

This course is for delivery in-house only. Offering better value for money, in-house training can be customised and designed to meet specific individual and company needs.

Please Contact us to discuss your in-house requirements

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