Academic Year 2020/21 1 ASSIGNMENT/COURSEWORK PROFORMA Module code: MN5610 Assessment title: Advanced measurement systems and data analysis Module tutors: Dr QingPing Yang 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. 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. Assessment criteria: 1. Understanding of measurement systems (including sensors / transducers, CMMs and surface measuring machines) (40%) 2. Consideration of error sources and calibration (10%) 3. Selection considerations (10%) 4. Understanding of nonlinear least square method (15%) 5. Data analysis algorithm / coding (15%) 6. Discussions and presentation (10%) Assessment method by which a student can demonstrate the learning outcomes: Identification and evaluation of the practical measuring systems for the given measurement tasks. Design and implementation of algorithms and Matlab programs for practical data analysis. Weighting: 40% of module marks Format of the assessment/coursework: (Guidelines on the expected format and length of submission): *Note: full reports may not exceed 30 pages (including appendices) Format is a formal written report including diagrams/code; calculations (with data; formula; workings and assumptions) and discussion/ comments. Report to be written using Word in a 12 point font. Typical length of report is 2000 words, comprising Title Page; Introduction; Task 1, Task 2, Discussions, Conclusions and References. Assessment date/submission deadline: Please submit by Friday 30th April 2021 via WISEflow Academic Year 2020/21 2 Indicative reading list: Fraden J. (2015). Handbook of modern sensors: physics, designs, and applications. Springer. Morris A S. (2012). Measurement and instrumentation: theory and application. Academic Press. Leach R. (2014). Fundamental principles of engineering nanometrology (Micro and Nano Technologies). Elsevier. Flack D R and Hannaford J. (2005). Fundamental good practice in dimensional metrology”. NPL Good practice guide No. 80 (free download from http://www.npl.co.uk). Bell S A. (2001). A beginner’s guide to uncertainty in measurement. NPL good practice guide No. 11 (free download from http://www.npl.co.uk). Barker R M, Cox M G, Forbes A B and Harris P M. (2007). Software Support for Metrology Best Practice Guide No. 10: Discrete Modelling and Experimental Data Analysis. National Physical Laboratory, Teddington. Higham D J, Higham N J. (2016). MATLAB Guide, Third edition. Philadelphia: Society for Industrial and Applied Mathematics. Other information Use your student ids for anonymity (i.e. no student names on the assignment itself). Academic Year 2020/21 3 ASSIGNMENT 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 20 μm. Some precision spindles have tolerances of only 5 microns with a batch size in the range 1 – 50. 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 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 squares 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: Academic Year 2020/21 4 Measurement Results (unit: mm) X Y 84.047 73.303 44.041 4.015 -35.996 -65.250 -75.972 -65.241 -35.979 4.025 44.029 73.330 84.006 5.038 45.008 74.326 85.021 74.319 45.003 5.038 -34.997 -64.263 -74.969 -64.241 -34.975 5.006
