Managing and Quantifying Uncertainty in Measurement 1 dayAn authoritative overview for scientists and engineers responsible for

sigma
engineering partnership

Managing and Quantifying Uncertainty in Measurement 1 day
An authoritative overview for scientists and engineers responsible for measurement processes

Why measure?, clarifying measurement objectives, ISO/ UKAS requirements, gauge R&R studies, understanding measurement variation, measurement stability, continual improvement, calibration, over-adjustment, standard errors (standard uncertainties), resolution, accuracy, repeatability and reproducibility, mean squared-error, propagation of errors, working with uncertainty

Introduction to Linear Regression and Calibration 1 day
For engineers and scientists with some statistical interests wishing to widen their range of skills

Explaining variation, visualising association, the linear model, assumptions, stability, correlation, Taguchi loss-functions, least-squares calculations, diagnostics, residuals analysis, control charts, goodness-of-fit, leverage, prediction and uncertainty, standard errors for regression; confidence, prediction and tolerance intervals; intervals and bands, a practical approach to calibration, designing studies

Introduction to Statistics for Test Engineers 2 days
A practical tool-kit for all engineers involved in product testing and project management, aimed at adding genuine value for the business

The test engineer's job, products and processes, test lab. processes, variation and uncertainty, Taguchi's loss-function, collecting data, What data?, enumerative and analytic statistics, sampling, types of data, exploring data, exploratory and confirmatory data analysis, graphical methods, means, standard deviations, correlation, standard errors, process stability, control charts, informal confirmation, the three-sigma rule, formal confirmation, hypothesis tests, difficulties with formal tests, test power, choosing sample size, confidence intervals, sense and nonsense.

Quality Improvement through Experiments 2 days
All the tools and techniques that you need for understanding Taguchi's ideas and developing products that delight your customers

Variation and quality, Taguchi's robust-design philosophy, a strategy for quality improvement, the need for experimental design, interactions and robust design, capturing variation, orthogonal arrays, the conventional wisdom of experiments, enumerative and analytic statistics, process stability, fractional factorials, experimenting near an optimum, response-surface methods, nuisance variables, replication, randomisation, analysis of results, Yates' algorithm, half-normal plots, analysis of means, diagnostics, control charts

FMEA in Design and Manufacture 2 days
Robust methods for engineering management to identify risks and plan for success

Fault Modes and Effects Analysis, systems, faults and failures, common and special causes of failure, the design process, the Kano model, developing specifications, standards and targets, affinity diagrams, relationship to QFD, understanding systems effects, assessing severity, cause and effects analysis, interfaces and interactions, the HAZOPS model, mechanisms at the detail level, formatting the FMEA, closing the loop, recovering from faults, prioritisation and FMECA, aggregate dependability, FMEA and risk management, process FMEA, control plans

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This page last updated 19th November 2000