UNCERTAINTY ANALYSIS AND QUALITY ASSURANCE FOR COORDINATE MEASURING SYSTEM SOFTWARE
Table Of Contents
- TABLE OF CONTENTS
1. INTRODUCTION .................................................................................................... 1
1.1 Coordinate Measuring Systems .......................................................................... 1
1.2 The Problem of Uncertainty................................................................................ 4
1.3 The Problem of Software Uncertainty ................................................................ 6
1.4 The NIST ATEP-CMS software testing program............................................. 11
2. BACKGROUND INFORMATION AND LITERATURE SURVEY................... 14
2.1 NIST work ........................................................................................................ 14
2.2 NIST Algorithm Information............................................................................ 17
2.3 NPL work.......................................................................................................... 21
2.4 Other documentation......................................................................................... 24
3. LEAST SQUARES FITTING ................................................................................ 26
3.1 The Problem of Least Squares Fitting .............................................................. 26
3.2 The Need for Least Squares Fitting .................................................................. 27
3.3 Issues involved in solving Least Squares Fitting Problems.............................. 27
3.4 An Approach to Least Squares Fitting.............................................................. 28
3.5 Implementation of the Approach ...................................................................... 28
3.6 Results of the Implementation .......................................................................... 29
3.7 An Application of Least Squares Fitting .......................................................... 29
4. MINIMUM ZONE FITTING ................................................................................. 39
4.1 The Problem of Minimum Zone Fitting............................................................ 39
4.2 The Need for Minimum Zone Fitting ............................................................... 40
4.3 Issues involved in solving Minimum Zone Fitting Problems........................... 42
4.4 An Approach to Solving Minimum Zone Fitting ............................................. 43
4.5 Implementation of the Approach ...................................................................... 44
4.6 Reference vs. Commercial Algorithm Performance......................................... 46
4.7 Results of the Implementation .......................................................................... 48
5. MAXIMUM INSCRIBED AND MINIMUM CIRCUMSCRIBED FITTING...... 49
5.1 The Problem of Maximum Inscribed and Minimum Circumscribed Fitting.... 49
5.2 The Need for Maximum Inscribed and Minimum Circumscribed Fitting........ 51
5.3 Issues involved in solving Maximum Inscribed and Minimum Circumscribed
Fitting Problems...................................................................................................... 52
- 5.4An approach to Maximum Inscribed and Minimum Circumscribed Fitting .... 53
- 5.5Implementation of the Approach ...................................................................... 59
- 5.6Reference vs. Commercial Algorithms for Maximum Inscribed and Minimum
Circumscribed Fitting ............................................................................................. 59
- 5.7Results of the Implementation .......................................................................... 61
- 6.LEAST SQUARES FITTING OF COMPLEX SURFACES................................. 62
- 6.1The Problem of Least Squares Fitting of Complex Surfaces............................ 62
- 6.2The Need for Fitting of Complex Surfaces....................................................... 63
6.3 Issues involved in solving Least Squares Fitting of Complex Surfaces Problems
................................................................................................................................. 64
6.4 An Approach to Solving Least Squares Fitting of Complex Surfaces Problems
................................................................................................................................. 68
- 6.5Implementation of the Approach ...................................................................... 69
6.6 Results of the Implementation .......................................................................... 77
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7. OTHER ISSUES AND FUTURE WORK ............................................................. 78
7.1 Other Issues Involved in CMS Fitting Software............................................... 78
7.2 Future Work...................................................................................................... 79
- 8.Conclusions............................................................................................................. 81 REFERENCES ........................................................................................................... 87
Thesis Abstract
Abstract
Coordinate Measuring Systems (CMS) play a crucial role in modern manufacturing processes for ensuring the accuracy and quality of produced parts. The software used in CMS is a critical component that drives measurement accuracy and reliability. However, uncertainties associated with the software can impact the quality of measurements and, consequently, the overall quality assurance process. Therefore, it is essential to conduct a thorough uncertainty analysis of the CMS software to understand and mitigate these uncertainties effectively. This research project focuses on uncertainty analysis and quality assurance for Coordinate Measuring System software. The primary objective is to develop a systematic framework for evaluating and managing uncertainties in CMS software to enhance measurement accuracy and reliability. The research entails a comprehensive review of existing methodologies for uncertainty analysis in metrology and software engineering. The proposed framework integrates principles from metrology, software engineering, and quality management to address uncertainties specific to CMS software. It includes identification of sources of uncertainty, quantification of uncertainties through mathematical modeling and simulation, and validation of uncertainty models through experimental testing. The framework also incorporates quality assurance measures to ensure the reliability and traceability of measurement results. Key components of the framework include error propagation analysis, sensitivity analysis, and Monte Carlo simulation to quantify uncertainties arising from different sources such as software algorithms, hardware components, environmental factors, and human factors. The research also explores the use of advanced statistical techniques and machine learning algorithms to improve uncertainty quantification and prediction in CMS software. Furthermore, the study investigates the impact of uncertainties in CMS software on measurement accuracy and provides recommendations for minimizing these uncertainties through software validation and verification processes. The research outcomes are expected to contribute to the development of guidelines and best practices for uncertainty analysis and quality assurance in CMS software. In conclusion, this research project aims to enhance the understanding of uncertainties in Coordinate Measuring System software and improve the quality assurance process in metrology. By developing a systematic framework for uncertainty analysis, this study will help manufacturers and quality control professionals ensure the accuracy and reliability of measurements obtained from CMS software, ultimately leading to improved product quality and customer satisfaction.
Thesis Overview
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1. INTRODUCTION
1.1 </p><p>Coordinate Measuring Systems
Coordinate measuring systems (CMSs) are installed in factories, research and medical
labs, as well as many other industrial and scientific facilities. The definition of a CMS
is, "…any piece of equipment which collects coordinates (points) and calculates and
displays additional information using the measured points," [8]. To find the
dimensions of a part, a CMS measures point locations on the object’s surface. This
coordinate data is then processed to determine the part’s dimensions and the types
and locations of variations in the surface. Note that the raw coordinate data generally
must be interpreted before the information gathered is of any real use. Specifically,
once the coordinate data points are collected from the surface of the part by the CMS
hardware, the information is processed by software, which usually performs a
geometric fit to the gathered data. This fitting software, which is usually integrated as
part of the CMS, uses the coordinate data to, for instance, determine a part’s location,
orientation, concentricity, or deviation of the part from the corresponding perfect
geometry. The software can apply appropriate processing of the data to determine if a
part is within tolerances defined in specifications. Since a part is measured through
only a sampling of points, its true surface can never be known exactly; instead, an
approximation of the surface is known based on a finite sampling of coordinate
points. The software will often be required to compute a “substitute geometry” based
on the imperfect data. This substitute geometry is a perfect, theoretical, mathematical
shape fit to the points. For example if a CMS samples points on a surface that is
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nominally cylindrical, then the software can compute a fit to find the “best” perfect
cylinder that is represented by the imperfectly measured points on the imperfect
physical surface. Just how this substitute feature is determined can be complicated
and is discussed in this paper.
CMSs are used to measure everything from pistons and cylinders to gears and screw
threads to airplane wings and car doors. Sometimes their uses go beyond
manufactured parts to include, for example, bones and vertebrae alignment in the
medical field. Many different types of coordinate measuring systems are in use today
including theodolites, photogrammetry, optical systems, and coordinate measuring
machines. Though such variation exists among CMSs, the software packages that
they normally come equipped with are similar and share some basic problems and
issues. Examples of several different types of systems are given1
in figure 1.1. Shown
in the pictures are: 1) CMM: a measuring system with the means to move a probing
system and capable of determining spatial coordinates on a workpiece surface, 2)
theodolite: a small telescope mounted and moving on two graduated circles, one
horizontal, the other vertical, while its axes pass through the center of the circles. The
data points are found using triangulation, and 3) photogrammetry: this system works
by taking pictures of the object being measured with a digital camera then inputting
the image into the software to determine its part information.
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