Implementation of digitalization technologies for optimizing energy efficiency and thermal management in steam industrial processes

In recent decades, within the framework of the digital world, the control and management of industrial steam consumption and demand have become increasingly difficult. Specifically, in complex industrial processes where spaces and layouts are limited, the possibility of modifying facilities and equipment is significantly less. In addition, the economic cost of controlling consumption per production line or equipment often makes investments unfeasible. Therefore, global consumption is usually controlled in the most complex industrial processes without any subsequent partial demand monitoring. This paper focuses on the development, implementation, and evaluation of a steam control platform by consumers, avoiding the need to install a mass flow meter by equipment, line or installation. An ad-hoc algorithm is designed and assessed by combining information from the monitoring and management systems for optimal operation. Data gathered through combined information from different management systems are integrated into a proposed global management and monitoring platform. In addition, the application of the designed steam control algorithm is used as key information for business decision-making, cost estimation, and predictive maintenance control. A case study and the proposed platform were implemented in an actual chemical plant located in Spain from a multinational corporation. This case study can also be used as a reference model, providing a scalable and easily replicable solution for other factories with steam-consuming equipment. From the results, it is possible to achieve effective steam consumption monitoring for over 50 production units by integrating steam flow meters into the main supply-lines, in combination with other industrial management systems: ERP, MES, or DCS. Notably, this approach is carried out with an investment cost 25 times lower than traditional methods, providing high efficiency, suitability and cost-effectiveness. The results and discussion of the gathered data and the global platform are also included in the paper. The proposed methodology and algorithms are not only suitable for this chemical company case study, but also scalable for any type of factory/plant with steam consumption equipment or process.