COURSE OVERVIEW

 

This practical and highly-interactive course includes various practical sessions and exercises. Theory learnt will be applied using our state-of-the-art simulators. 

The course is designed to provide delegates with a detailed and up-to-date overview of Advancement in Process Measurement. It covers the importance and key objectives of process measurement and the role of measurement in process optimization; the measurement units and standards, SI units and their relevance, calibration standards and traceability, impact of international standards (ISO, ASTM, etc.) and importance of unit consistency; the measurement accuracy and precision and techniques for minimizing errors; the types of sensors, working principles of transducers, sensor selection criteria for various processes and challenges in sensor integration; and the signal conditioning, processing, signal amplification and filtering, analog-to-digital conversion techniques and noise reduction methods. 

Further, the course will also discuss the process control systems, flow measurement techniques, temperature measurement, pressure measurement and level measurement; the chemical composition analysis, measurement in dynamic environments, data acquisition systems, data storage and security and data visualization; the descriptive statistics for process data and regression analysis for measurement trends; and the hypothesis testing in process improvement and statistical process control techniques. 

During the interactive course, participants will learn the role of predictive modelling in process optimization and machine learning techniques for process prediction; the benefits and limitations of wireless systems, network protocols for wireless sensors, power management in wireless sensors and applications in remote and hazardous locations; the principles of fiber optic sensing, types of fiber optic sensors, advantages over traditional sensors and industrial application of fiber optics; the machine vision systems, 3D scanning and imaging, AI and machine learning in measurement and augmented reality (AR) and virtual reality (VR); the role of measurement in energy optimization, monitoring emission and environmental compliance and water and waste management through measurement; and the smart factories and automation, ethical and legal considerations and future trends in process measurement.