CMSC 2024

Metrology, the science of measurement, plays a crucial role in various industries, ensuring product quality, process control, and compliance with standards. Over the years, traditional metrology techniques have been widely used for measurement and inspection purposes. However, the advent of computer-aided metrology has revolutionized the field, offering numerous advantages over traditional methods. However, uncertainties associated with Computer-Aided Metrology (CAM) measurements continue to pose challenges in achieving accurate and reliable results. This publication aims to bridge the gap between CAM and traditional metrology by addressing uncertainties and proposing strategies to mitigate them.

The publication begins by highlighting the benefits and limitations of CAM compared to traditional metrology methods. Traditional metrology relies on manual measurement tools, such as calipers, micrometers, and gauges, which require human intervention and interpretation. Computer-aided metrology, on the other hand, utilizes advanced hardware and software systems, including coordinate measuring machines (CMMs), laser scanners, laser trackers, and optical measurement devices, which automate the measurement process and provide accurate and reliable data.

The publication digs into the various sources of uncertainties in CAM, including measurement equipment, software algorithms, and environmental factors. It explores the impact of these uncertainties on measurement accuracy and repeatability, emphasizing the importance of error analysis and uncertainty estimation in CAM processes. To bridge the gap between CAM and traditional metrology, the presentation proposes strategies to address uncertainties. These strategies may include calibration and verification of measurement equipment, validation of software algorithms, proper training, and implementation of quality control measures.

In conclusion, this publication provides valuable insights into addressing and minimizing uncertainties in CAM and traditional metrology. By understanding the sources of uncertainties and implementing effective strategies, organizations can maximize the potential of CAM while ensuring accurate and reliable measurements.