Validating Requirements and Improving Specifications with Telematics Data



Field failures cause high warranty expenses, perhaps the highest quality cost. Failures occur when new designs are introduced, existing products are sold in new markets, and product specifications don’t reflect actual product usage. Any mistake in product specifications affects the entire product development process and cascades through the supply chain.

New product requirements are developed using prior requirements, rely on customer surveys, use “expert” opinion, or are the result of compromises to meet timing or management direction. The resulting requirements may be excessive or insufficient. If excessive, then verification testing costs are too high; if insufficient, then product verification is inadequate.

This course teaches the student how to analyze development and field usage data with a focus on projecting to design life targets. Data needs to be collected from the customer. Today’s availability of wireless services makes this relatively easy and tomorrow’s internet of things (IOT) can provide the raw data for analysis. This course uses selected automotive telematics data collected by special modules installed in development, fleet, and retail vehicles.

Learning Objectives
By attending this course, you will be able to:
  • Define different types of data in Telematics.
  • Determine the need and ways to standardize data metrics
  • Determine the best probability distributions to describe counting or continuous data for a group of vehicles
  • Apply cumulative distributions to determine population percentiles and project data metrics to design life targets. Examples: Engine start/stop events and vehicle speeds
  • Analyze state transitions for product that operate in a finite number of states.
  • Analyze two-dimensional multivariate data. (Engine Speed vs. Engine Torque)
  • Make comparisons of different vehicle categories. (Police vehicles vs. retail vehicles)
Who Should Attend

The course is designed for more senior personnel who validate requirements, develop test plans and verify conformance to requirements.  These analytic methods will be useful to information technologists, reliability engineers, product engineers, quality engineers and management.

Statistics and an engineering degree.
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