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[1], therefore there are requirements for high qualified and trained teams to handle such technologies[2].
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[3]. 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[4].
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[5]; and (ii) integrating cutpoint temperature optimization of the distillates (initial and final boiling points) with the final blending producing specified fuels[6]. Other examples show ICT integrated with scheduling optimization in (i) crude-oil selection or diet; (ii) pathways for hydrocarbon movements[7]; (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.
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