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MN5610 Advanced measurement systems and data analysis

Objective: To enable students to demonstrate their cognitive and practical skills related to the advanced measurement system and data analysis in a broad context.

Brief Description: Given some dimensional measurement tasks in an industrial context, you will need to complete two tasks: 1) to identify the suitable measurement solutions and 2) to design/develop the Matlab program for the measurement data analysis

Learning outcome 1: To design and evaluate measuring devices / instrumentation / systems;
Learning outcome 2: To appreciate the wide applications of advanced measuring systems;
Learning outcome 3: To master and apply numerical methods for fitting linear/nonlinear models to data;
Learning outcome 4: To design and implement numerical algorithms for data analysis.

Prepare an individual assignment

1. Understanding of measurementsystems (including sensors / transducers, CMMs and surface measuring machines)
2. Consideration of error sources, calibration and traceability
3. Selection considerations
4. Understanding of nonlinearleast square method
5. Data analysis algorithm / coding
6. Discussions and presentation

Evaluation of the practical measuring systems for the given measurement tasks. Design and implementation of algorithms and Matlab programs for practical data analysis.

Task 1:
Over recent years your company has been making substantial investments in automated machine tools, but the inspection techniques have remained virtually unchanged. Most operators still use go/no-go gauges and comparators etc. The emphasis has been on the detection of non-conforming components which are either scrapped or reworked.

The largest overall linear dimension on any components manufactured by the company is 400 mm. The main products are turned and milled components, with batch sizes in thousands and a substantial number of features with tolerances in the region of 25 µm. Some precision spindles have tolerances of only 5 microns with a batch size in the range 1 - 50. The surface roughness (Ra) ranges from 12.5-0.025 µm.

The Managing Director has given you the task of preparing a report on the types of equipment which could be employed to improve the measurement and product quality within the company. You should aim to demonstrate comprehensive knowledge of relevant measuring techniques with sound / innovative solution (paying attention to new and emerging technologies) and also skills for broader considerations, e.g. implications due to batch sizes, component types and materials, commercial and industrial constraints. Your report should cover the use of suitable sensors and transducers (e.g. LVDTs and/or optical encoders), coordinate measuring machines (CMMs) and surface measuring machines, including their operating principles, characteristics and performance. Since CMMs are complicated measuring machine, you should discuss their common error sources and how you are going to calibrate them. You should also describe the important surface parameters the company will likely use.

Task 2:

Your company has a manual 2D microscope which can measure the coordinates of 2D profiles. You have been asked to develop a least square algorithm in either Matlab or Excel to calculate the centre and radius of circular features. Given the standard uncertainty of x and y coordinates is 20 µm, calculate the uncertainties associated with the radius and centre coordinates. Describe how to reduce the measurement uncertainties.

To test your algorithm, you can use the following measurement results, the XY coordinates recorded for a ring gauge: