Designing intelligence: harnessing soft sensors and advanced analytics in petroleum refining for industry 4.0

Abstract

Industry 4.0 is revolutionizing process industries by transforming vast data sets into actionable insights, improving efficiency, reducing downtime, and ensuring consistent product quality while meeting environmental standards. A key driver of this transformation is the development of intelligent, software-driven soft sensors, which provide real-time analytics for monitoring crucial process parameters traditionally measured through slower offline methods.

This chapter explores the design and implementation of soft sensors, emphasizing the integration of artificial intelligence (AI) and machine learning (ML) in real-time quality monitoring within the petroleum refining industry. Over the past 15 years, these advanced sensors have significantly enhanced monitoring and quality assurance, enabling precise control over raw material composition and final product quality.

By examining different soft sensor models and their applications, the chapter highlights their impact on industrial operations, as well as challenges such as managing large data streams and ensuring sensor reliability. Through real-world case studies, it demonstrates the practical benefits of soft sensors and their role in advancing the oil and gas sector toward Industry 4.0, paving the way for innovation and enhanced operational intelligence.