Reference no: EM132459190

MN5618 Advanced Measurement Systems and Data Analysis Assignment - Brunel University London, UK

Learning outcomes for the assessment (refer to the appropriate module learning outcomes) - Students will be able to demonstrate the following:

- To gain systematic understanding of measurement errors and uncertainties;

- To gain comprehensive understanding of the operating principles of advanced sensors;

- To develop critical awareness of the range and capabilities of advanced measuring instruments;

- To gain systematic understanding of linear/nonlinear models for advanced data analysis.

- To perform error analysis and uncertainty evaluation of practical measurement systems;

- To critically apply and evaluate different linear/nonlinear models for advanced data analysis.

- To gain practical experience in the use of measuring instruments;

- To develop critical awareness of the wide applications of advanced measuring instruments.

Main objectives of the assessment: To enable students to demonstrate their in-depth knowledge of the principles of advanced measurement system and data analysis and abilities to apply them to solve practical problems related to advanced measurement system and data analysis.

Brief Description of the assessment: Given some measurement tasks in an industrial context, you will need to complete two tasks: 1) to identify and evaluate the suitable measurement solutions and 2) to design/develop the Matlab program for the measurement data analysis. Both tasks are related to the key topics of the module.

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 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 a substantial number of features with tolerances in the region of 50 µm, but some precision spindles have tolerances of only 5 microns. The surface roughness 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, 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.

Describe briefly how measurement uncertainty is evaluated. Given the standard uncertainty of x and y coordinates is 30 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:

Measurement Results (unit: mm)

Note - Format is a formal written report including diagrams/code; calculations (with data; formula; workings and assumptions) and discussion/ comments. Typical length of report is 2500 words, comprising Title Page; Introduction; Task 1, Task 2, Discussions, Conclusions and References.