The smart industrial revolution, the 4th after the mechanical, electrical, and digital ones, is a today’s process industry frontline research in terms of technology, but also in terms of the use of technology that implies in human behavior and resource issues to deploy new process-of-work. Smart operation makes use of new information and communication technologies (ICT) and advanced algorithms such as optimization, therefore there are requirements for high qualified and trained teams to handle such technologies.
Smart Process Manufacturing (SPM) also known as Industry 4.0 is an emerging field of research and refers to a design and operational paradigm involving the integration of measurement and actuation, safety and environmental protection, regulatory control, high fidelity modeling, real-time optimization and monitoring, and planning and scheduling. It is the enterprise-wide application of advanced technologies, tools, and systems, coupled with knowledge-enabled personnel, to plan, design, build, operate, maintain, and manage process manufacturing facilities, where is expected reduced costs in inventories, manufacturing, logistics, maintenance, etc.
We present several applications and opportunities of smart operations to be explored in fuels industries. These operations leverage the decision-making by (i) clustering crude oil arriving in the refineries as much as different they can be in terms of quality; and (ii) integrating cutpoint temperature optimization of the distillates (initial and final boiling points) with the final blending producing specified fuels. Other examples show ICT integrated with scheduling optimization in (i) crude-oil selection or diet; (ii) pathways for hydrocarbon movements; (iii) blendshops, and (iv) regeneration of ion exchange resins in a demineralized water facility for boiler feed water production.
The ongoing project for management of operations in Petrobras refineries will be presented. It is a panel board controlling the operations, gathering real-time information from the plant and communicating to the operators, after the mentioned optimization, what they should execute, where some of them is simply a transmission of radio frequency identification (RFID) to automatic valves.
(1) Thornhill NF, 2015. In https://workspace.imperial.ac.uk/smartops/Public/ENERGY-SMARTOPSOverview.pdf
(2) Christofides PD, David JF, El-Farra NH, Clark D, Harris KRD and Gipson JN. Smart plant operations: vision, progress and challenges. Aiche Journal, 2007, 53 (11), 2734–2741.
(3) Davis JF and Edgar TF. Smart Process Manufacturing – A Vision of the Future. In Book: Design for Energy and Environment. Ed. El-Halwagi MM, Linninger AA, 2008, 150-165.
(4) David JF, Edgar T, Porter J, Bernaden J and Sarli M. Smart manufacturing, manufacturing intelligence and demand-dynamic performance. Comput Chem Eng, 2012, 47, 145–156.
(5) Industrial Algorithms LLC., 2015. In http://pt.slideshare.net/alkis1256/ctap-imf.
(6) Kelly JD, Menezes BC, Grossmann IE. Distillation Blending and Cutpoint Temperature Optimization using Monotonic Interpolation. Ind Eng Chem Res, 2014, 52, 18324-18333.
(7) Magatão SNB, Magatão L, Neves-Jr F, Arruda LVR. Novel MILP Decomposition Approach for Scheduling Product Distribution through a Pipeline Network. Ind Eng Chem Res, 2015, DOI: 10.1021/ie5046796.
See more of this Group/Topical: Process Development Division