(195c) Development of a Joint Infrastructure for Chemical Engineering Applications Related to Industry 4.0 and Digital Transformation

This work provides an overview on the opportunities created when a developed Industry 4.0 infrastructure is applied to chemical engineering processes. Industry 4.0 defines a technology framework designed to revolutionize the world process industries. In this context, research groups have been exploring such a revolution by bringing to this environment improvements to link chemical engineering research, applications and teaching^1,2,3. In particular, in this presentation, the cooperation between research groups at West Virginia University (WVU, USA) and Federal University of Campina Grande (UFCG, Brazil) in this area is described. Such cooperation aims to lead to a complete IIoT (Industrial Internet of Things) infrastructure connected to several dynamic process simulators (e.g., Aspen, CHEMCAD, SimCentral). With data availability from this infrastructure (at different data request points for a simulated process and in real time), Industry 4.0 aspects can be explored, such as: digital twin, machine learning, on-line data analysis, event frames and notifications, as well as topics directly linked to automatic and statistical process control, process optimization and economic analysis.

The current infrastructure envisioned for analysis involves the use of a simulation platform that represents a chemical or manufacturing plant, data processing/storage and data request points from client devices and applications. The particularly investigated simulations include a subcritical coal-fired power plant model (from WVU), an industrial process from a large Latin America Refining Company (from UFCG), as well as chemical processes from the literature. Central to this infrastructure is a database to store real-time simulation data that represent plant measurements. The database used corresponds to the OSIsoft PI historian (which is part of the PI System)¹. A Supervisory Control and Data Acquisition (SCADA) system is employed to remotely monitor and control the studied simulation through Open Platform Communications (OPC). In an analogy between the developed infrastructure and the Automation Pyramid, levels 0 (sensors and actuators) and 1 (unit automation) are represented by the dynamic simulations, level 2 (SCADA) provides the remote access to process variables and specifications by customized HMIs (Human Machine Interfaces), and level 3 (Plant Information Management System – PIMS) contextualizes the data from an asset standpoint allowing the management of analytics, event frames, notifications and system integrations with a tree view of the plant structure. The PIMS makes the data available for custom applications, thus interpreting the information and adding value to process related techniques such as predictive process control, optimization and economics analysis. Therefore, this infrastructure can provide a more realistic environment for investigating process automation and implementations under development, using desktop or web-based custom reports and dashboards for decision making at all different levels (operators, engineers or executives).

This work thus explores aspects of Industry 4.0 such as Digital Twins, Simulation, System Integration and Data Analytics using a developed infrastructure at WVU and UFCG that can be used for operator training, research and engineering classes. Additionally, it corresponds to the starting point for future research on more robust data analytics, machine learning, big data and business intelligence studies.

References

¹ E. Ruiz-Ramos, J. M. Romero-García, F. Espínola, I. Romero, V. Hernández and E. Castro, “Learning and researching based on local experience and simulation software for graduate and undergraduate courses in chemical and environmental engineering”, Education for Chemical Engineers, 21, pp 50 – 61, 2017;

² J. Uhlemann, R. Costa and J. Cl. Charpentier, “Product design and engineering — past, present, future trends in teaching, research and practices: academic and industry points of view”, Current Opinion in Chemical Engineering, 27, pp 10–21, 2020;

³ M. Teles dos Santos, A. S. Vianna Jr. and G. A. C. Le Roux, “Programming skills in the industry 4.0: are chemical engineering students able to face new problems?”, Education for Chemical Engineers, 22, pp 69–76, 2018.

⁴ PI Server. (2018 SP3). San Leandro, CA, USA. OSIsoft.