Industry today utilises several types of high temperature industrial equipment, including melting kilns, ovens, furnaces, and heat exchangers. Equally important for industrial businesses is to ensure energy efficiency and pollution abatement within industrial practices, especially because of new legal requirements and goals for improved cost-effectiveness. In essence, energy efficient and eco-friendly manufacture relies on high temperature equipment that generates products by utilising less energy and fewer raw materials, while emitting reduced amounts of liquid, gas, solid, and thermal wastes. Fortunately, the EXLIBRIS project meets these requirements. In fact, the EXLIBRIS project was designed to develop, apply and test an expert system methodology that optimises the design, operation and control of these types of high temperature industrial equipment. The consortium of Portuguese, French, British, Belgian, and Greek researchers devised a novel way of incorporating physical and model-based knowledge along with advanced optimisation algorithms that led to the EXLIBRIS expert system. Furthermore, the EXLIBRIS system works in a predictive fashion, and allows for on-line operation optimisation and off-line design optimisation. The project was founded on previously developed concepts, including physical-based modelling tools, a database that fused data from sensors, modelling results and process data and made the information accessible to an optimisation algorithm, and advanced identification models. These already-developed concepts were then consolidated into an innovative platform by the EXLIBRIS researchers. The result is a system that optimises operating conditions and helps to design the best equipment possible for a vast array of industrial processes. Ultimately, the EXLIBRIS system aims to reduce energy consumption and minimise pollution emissions. All these functions along with the ultimate goals of the system promise to help industry in the difficult process of optimising production while utilising less energy and emitting fewer pollutants.