Brenno Castrillon Menezes

Pós-doutorado

Formação complementar

Idiomas

Áreas de atuação

Grande área: Engenharias / Área: Engenharia Química / Subárea: Tecnologia Química/Especialidade: Petróleo e Petroquímica.

Grande área: Engenharias / Área: Engenharia de Produção / Subárea: Pesquisa Operacional/Especialidade: Programação Linear, Não-Linear, Mista e Dinâmica.

Grande área: Ciências Exatas e da Terra / Área: Matemática / Subárea: Matemática Aplicada/Especialidade: Matemática Discreta e Combinatória.

Grande área: Ciências Exatas e da Terra / Área: Ciência da Computação / Subárea: Metodologia e Técnicas da Computação/Especialidade: Linguagens de Programação.

Participação em eventos

Participação em bancas

Comissão julgadora das bancas

Orientou

Foi orientado por

Produções bibliográficas

• Menezes, Brenno C. ; KELLY, JEFFREY D. ; LEAL, ADRIANO G. ; LE ROUX, GALO C. . Predictive, Prescriptive and Detective Analytics for Smart Manufacturing in the Information Age. IFAC-PAPERSONLINE , v. 52, p. 568-573, 2019.

• JOLY, M. ; ODLOAK, D. ; MIYAKE, M. Y. ; MENEZES, B. C. ; KELLY, J. D. . Refinery production scheduling toward Industry 4.0. Frontiers of Engineering Management , v. 5, p. 202-213, 2018.

• KELLY, JEFFREY D. ; Menezes, Brenno C. ; GROSSMANN, IGNACIO E. . Successive LP Approximation for Nonconvex Blending in MILP Scheduling Optimization Using Factors for Qualities in the Process Industry. INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH , v. 57, p. 11076-11093, 2018.

• ASSIS, LEONARDO S. ; CAMPONOGARA, EDUARDO ; Menezes, Brenno C. ; GROSSMANN, IGNACIO E. . An MINLP formulation for integrating the operational management of crude oil supply. COMPUTERS & CHEMICAL ENGINEERING , v. 123, p. 110-125, 2018.

• SONG, YINGKAI ; MENEZES, BRENNO C ; GARCIA-HERREROS, PABLO ; GROSSMANN, IGNACIO . Scheduling and feed quality optimization of concentrate raw materials in the copper refining industry. INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH , v. 57, p. 11686-11701, 2018.

• MENEZES, BRENNO C. ; KELLY, JEFFREY D. ; GROSSMANN, IGNACIO E. ; VAZACOPOULOS, ALKIS . Generalized Capital Investment Planning of Oil-Refineries using MILP and Sequence-Dependent Setups. COMPUTERS & CHEMICAL ENGINEERING , v. 80, p. 140-154, 2015.

• MENEZES, BRENNO C. ; MORO, LINCOLN F. L. ; LIN, WHEI O. ; MEDRONHO, RICARDO A. ; PESSOA, FERNANDO L. P. . Nonlinear Production Planning of Oil-Refinery Units for the Future Fuel Market in Brazil: Process Design Scenario-Based Model. Industrial & Engineering Chemistry Research , v. 53, p. 4352-4365, 2014.

• KELLY, JEFFREY D. ; MENEZES, BRENNO C. ; GROSSMANN, IGNACIO E. . Distillation Blending and Cutpoint Temperature Optimization Using Monotonic Interpolation. INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH , v. 53, p. 15146-15156, 2014.

• MENEZES, BRENNO C. ; KELLY, JEFFREY D. ; GROSSMANN, IGNACIO E. . Improved Swing-Cut Modeling for Planning and Scheduling of Oil-Refinery Distillation Units. Industrial & Engineering Chemistry Research , v. 52, p. 18324-18333, 2013.

• Menezes, Brenno C. ; KELLY, JEFFREY D. . High-quality blend scheduling solution for sizing, selecting, sequencing, slotting and spotting in the processing industries. In: Anton A. Kiss, Edwin Zondervan, Richard Lakerveld, Leyla Özkan. (Org.). Computer Aided Chemical Engineering. 1ed.: Elsevier, 2019, v. 46, p. 1813-1818.

• KELLY, JEFFREY D. ; Menezes, Brenno C. . Automating a shuttle-conveyor for multi-stockpile level control. In: Anton A. Kiss, Edwin Zondervan, Richard Lakerveld, Leyla Özkan. (Org.). Computer Aided Chemical Engineering. 1ed.: Elsevier, 2019, v. 46, p. 1153-1158.

• Menezes, Brenno C. ; KELLY, JEFFREY D. . Open-use and community-based tools for education in process system engineering: industrial applications from decision automation to data analytics. In: Anton Friedl, Jiří J. Kleme?, Stefan Radl, Petar S. Varbanov, Thomas Wallek. (Org.). Computer Aided Chemical Engineering. 1ed.: Elsevier, 2018, v. 43, p. 1705-1706.

• Menezes, Brenno C. ; KELLY, JEFFREY D. ; GROSSMANN, IGNACIO E. . Logistics optimization for dispositions and depooling of distillates in oil-refineries: closing the production scheduling and distribution gap. In: Anton Friedl, Jiří J. Kleme?, Stefan Radl, Petar S. Varbanov, Thomas Wallek. (Org.). Computer Aided Chemical Engineering. 1ed.: Elsevier, 2018, v. 40, p. 1135-1140.

• Franzoi, Robert E. ; Menezes, Brenno C. ; KELLY, JEFFREY D. ; Gut, Jorge W. . Effective scheduling of complex process-shops using online parameter feedback in crude-oil refineries. In: Mario R. Eden, Marianthi Ierapetritou, Gavin P. Towler. (Org.). Computer Aided Chemical Engineering. 1ed.: Elsevier, 2018, v. 44, p. 1279-1284.

• Menezes, Brenno C. ; GROSSMANN, IGNACIO E. ; KELLY, JEFFREY D. . Enterprise-Wide Optimization for Operations of Crude-Oil Refineries: Closing the Procurement and Scheduling Gap. In: Antonio Espuña; Moisès Graells, Luis Puigjaner. (Org.). Computer Aided Chemical Engineering. 1ed.: Elsevier, 2017, v. 40, p. 1249-1254.

• KELLY, JEFFREY D. ; Menezes, Brenno C. ; GROSSMANN, IGNACIO E. . Decision Automation for Oil and Gas Well Startup Scheduling Using MILP. In: Antonio Espuña; Moisès Graells; Luis Puigjaner. (Org.). Computer Aided Chemical Engineering. 1ed.: Elsevier, 2017, v. 40, p. 1399-1404.

• Menezes, Brenno C. ; KELLY, JEFFREY D. ; GROSSMANN, IGNACIO E. . Phenomenological Decomposition Heuristic for Process Design Synthesis of Oil-Refinery Units. In: Krist V. Gernaey; Jakob K. Huusom; Rafiqul Gani. (Org.). Computer Aided Chemical Engineering. 1ed.London: Elsevier, 2015, v. 37, p. 1877-1882.

• RANGEL, H. P. G ; LUZ, R. F ; MENEZES, B. C ; CAVALCANTE, R. M ; PESSOA, F. L. P . DESENVOLVIMENTO DE METODOLOGIA PARA SELEÇÃO DE PROJETO PARA APROVEITAMENTO DE GÁS NATURAL. In: XXII Congresso Brasileiro de Engenharia Química, 2018, São Paulo. Blucher Chemical Engineering Proceedings. São Paulo: Editora Blucher, 2018. v. 1. p. 1485.

• FRANZOI, R. E ; MENEZES, B. C ; KELLY, J. D ; GUT, J. A. W . BLEND SCHEDULING OPTIMIZATION USING FACTORS FOR QUALITIES IN CASCADED DISTILLATION TOWERS IN CRUDE-OIL REFINERIES. In: XXII Congresso Brasileiro de Engenharia Química, 2018, São Paulo. Blucher Chemical Engineering Proceedings. São Paulo: Editora Blucher, 2018. v. 1. p. 1233.

• ABA, M ; MENEZES, B. C ; LE ROUX, G. A. C . CAPACITY PLANNING OF ETHANOL BIOREFINERIES IN BRAZIL FOR ITS FUTURE FUEL MARKET EQUILIBRIUM. In: XXII Congresso Brasileiro de Engenharia Química, 2018, São Paulo. Blucher Chemical Engineering Proceedings. São Paulo: Editora Blucher, 2018. v. 1. p. 4079.

• MENEZES, B. C ; FRANZOI, R. E ; KELLY, J. D ; GUT, J. A. W . COMPLEX PRODUCTION SCHEDULING OPTIMIZATION IN CRUDE-OIL REFINERY INDUSTRIES: MODELING, SOLVING AND HEURISTICS STRATEGIES. In: XXII Congresso Brasileiro de Engenharia Química, 2018, São Paulo. Blucher Chemical Engineering Proceedings. São Paulo: Editora Blucher, 2018. v. 1. p. 4143.

• MENEZES, B. C ; KELLY, J. D . EDUCATION IN PROCESS SYSTEMS ENGINEERING FOR PRESCRIPTIVE AND PREDICTIVE ANALYTICS IN INDUSTRY. In: XXII Congresso Brasileiro de Engenharia Química, 2018, São Paulo. Blucher Chemical Engineering Proceedings. São Paulo: Editora Blucher, 2018. v. 1. p. 4767.

• KELLY, J. D. ; MENEZES, B. C. ; ENGINEER, F. ; GROSSAMNN, I. E. . Crude-Oil Blend Scheduling Optimization of an Industrial-Sized Refinery: A Discrete-Time Benchmark. In: Foundations of Computer Aided Process Operations / Chemical Process Control, 2017, Tucson. Foundations of Computer Aided Process Operations, 2017.

• KELLY, J. D. ; MENEZES, B. C. ; GROSSAMNN, I. E. ; ENGINEER, F. . Feedstock Storage Assignment in Process Industry Quality Problems. In: Foundations of Computer Aided Process Operations / Chemical Process Control, 2017, Tucson. Foundations of Computer Aided Process Operations, 2017.

• MENEZES, B. C. ; MORO, L. F. L. ; GROSSMANN, I. E. ; KELLY, J. D. ; MEDRONHO, R. A. ; PESSOA, F. P. . PRODUCTION PLANNING OF OIL-REFINERY UNITS FOR THE FUTURE FUEL MARKET IN BRAZIL. In: XX Congresso Brasileiro de Engenharia Química, 2015, Florianópolis. Anais do XX Congresso Brasileiro de Engenharia Química. v. 1. p. 12856.

• MENEZES, B. C. ; MEDRONHO, R. A. . Fluidodinâmica e Erosão no Sistema da Válvula Main Bypass do Turboexpansor do Processo de Craqueamento Catalítico Fluído. In: XVII Congresso Brasileiro de Engenharia Química, 2008, Recife/PE. XVII Congresso Brasileiro de Engenharia Química, 2008.

• ANDRADE, B. F. ; MENEZES, B. C. ; SAKAI, P. N. ; FAVINHA, R. F. ; PAREDES, M. L. L. ; REIS, R. A. . Utilização de Viscosidade, Densidade e o Unifac-Visco para a Caracterização de Frações de Petróleo. In: Congresso Brasileiro de P&D em Petróleo e Gás, 2007, Campinas. 4º Congresso Brasileiro de P&D em Petróleo e Gás, 2007.

• MENEZES, B. C. . Estudo da Diversificação Energética das Empresas de Petróleo. In: Congresso Brasileiro de P&D em Petróleo e Gás, 2004, Salvador. 3º Congresso Brasileiro de P&D em Petróleo e Gás, 2004.

• MENEZES, B. C. ; KELLY, J. D. ; LEAL, A. G. . Intelligent Control for Automated Cyber Physical Systems in the Mining of Minerals. In: Aachen International Mining Symposia (AIMS), 2019, Aachen. 2nd International Conference on Mines of the Future, 2019.

• MENEZES, B. C. ; KELLY, J. D. ; IKARIMOTO, C. S. ; ROUX, G. C. L. . Data-Driven Real-Time Estimation and Optimization for Integrated Pre-Heat Exchange Trains and Distillate Cutpoints in Multiple Fractionation Columns. In: AICHE Spring Meeting, 2018, Orlando. Process Control and Optimization Developments, 2018.

• FRANZOI, R. E. ; MENEZES, B. C. ; KELLY, J. D. ; GUT, J. W. . Refinery-Wide Scheduling for Optimization of Multiple Unit-Operations in the Supply, Production, and Demand Chains in Fuels, Lubes, Asphalts and Petrochemicals Industries. In: AICHE Annual Meeting, 2018, Pittsburgh. Fuels and Petrochemicals Division, 2018.

• FRANZOI, R. E. ; KELLY, J. D. ; MENEZES, B. C. ; GUT, J. W. . Advanced Data Analytics for Process-Shop Base+Delta Sub-Model Estimation in Planning and Scheduling Decision-Making. In: AICHE Annual Meeting, 2018, Pittsburgh. Data and Information Systems, 2018.

• KELLY, J. D. ; FRANZOI, R. E. ; MENEZES, B. C. ; GUT, J. W. . Planuling: A Hybrid Planning and Scheduling Optimization to Schedule Slow and Plan Fast Processes. In: AICHE Annual Meeting, 2018, Pittsburgh. Systems and Process Operations, 2018.

• FRANZOI, R. E. ; MENEZES, B. C. ; KELLY, J. D. ; GUT, J. W. . Recent Advances and New Directions for Optimization of Production Scheduling in Crude-Oil Refineries. In: AICHE Annual Meeting, 2018, Pittsburgh. Fuels and Petrochemicals Division, 2018.

• KELLY, J. D. ; MENEZES, B. C. . Decision Automation for Lubes and Asphalt Production Scheduling using MILP with Sequence-Dependent Setups and Groups. In: AICHE Spring Meeting, 2018, Orlando. Refining Track: Advanced Process Control and Optimization, 2018.

• MENEZES, B. C. ; KELLY, J. D. ; GROSSMANN, I. E. . LP Reformulation to Approximate Non-Convex Blending in MILP Scheduling Problems Using Factors. In: AICHE Annual Meeting, 2017, Minneapolis. Planning and Scheduling I, 2017.

• SONG, Y. ; MENEZES, B. C. ; GARCIA-HERREROS, P. ; GROSSMANN, I. E. . Scheduling and feed quality optimization for raw materials in the metals industry. In: AICHE Annual Meeting, 2017, Minneapolis. Industrial Applications in Design and Operations, 2017.

• MENEZES, B. C. ; KELLY, J. D. ; JOLY, M. . Scheduling Optimization for Regeneration of Ion Exchange Resin in a Demineralized Water Treatment Facility. In: AICHE Annual Meeting, 2015, Salt Lake City. Systems and Process Operations, 2015.

• MENEZES, B. C. ; KELLY, J. D. ; GROSSAMNN, I. E. ; MORO, L. F. L. ; JOLY, M. . Smart Process Operations in Fuels Industries: Applications and Opportunities. In: AICHE Annual Meeting, 2015, Salt Lake City. Innovations in Process Development, 2015.

• MENEZES, B. C. ; KELLY, J. D. ; GROSSAMNN, I. E. . Distillation Curve Optimization Using Monotonic Interpolation. In: AICHE Annual Meeting, 2014, Atlanta. Systems and Process Operations, 2014.

• MENEZES, BRENNO C. ; JOLY, MARCEL ; MORO, LINCOLN F. L. . Crude-Oil Scheduling Technology: moving from simulation to optimization. In: Europeam Symposium in Computer Aided Process Engineering, 2015, Copenhagen. 12th International Symposium on Process System Engineering and 25th Europeam Symposium in Computer Aided Process Engineering, 2015. p. 22-22.

• VAZACOPOULOS, ALKIS ; KELLY, JEFFREY D. ; MENEZES, BRENNO C. ; GROSSMANN, IGNACIO E. . A General Approach for Capital Investment Planning using MILP and Sequence-Dependent Setups. In: INFORMS Conference on Business Analytics & Operations Research, 2014, Boston. INFORMS B&A, 2014.

• MENEZES, B. C. ; GROSSAMNN, I. E. ; MORO, L. F. L. ; KELLY, J. D. . A Nonlinear Integrated Model for Operational Planning of Multisite Refineries. In: INFORMS Computer Science, 2013, Santa Fe. INFORMS Computer Science, 2013.

• MENEZES, B. C. ; MEDRONHO, R. A. . Fluid Dynamics and Erosion of FCC Turboexpander Main Bypass Valve System. In: ESSS South American ANSYS Users Conference, 2008, Rio de Janeiro. ESSS South American ANSYS Users Conference, 2008.

• MENEZES, B. C. ; JOLY, M. ; MORO, L. F. L. . Crude-Oil Scheduling Technology: moving from simulation to optimization. 2015. (Apresentação de Trabalho/Simpósio).

• MENEZES, B. C. ; KELLY, J. D. ; GROSSAMNN, I. E. ; MORO, L. F. L. . Distillation Blending and Cutpoint Temperature Optimization in Scheduling Operations. 2015. (Apresentação de Trabalho/Conferência ou palestra).

Outras produções

Projetos de pesquisa

• 2018 - Atual

  Plano de desenvolvimento institucional na área de transformação digital: manufatura avançada e cidades inteligentes e sustentáveis (PDIp), Descrição: Nesse projeto o IPT se propõe a abordar o tema Transformação Digital por dois eixos de pesquisa - Manufatura Avançada e Cidades Inteligentes e Sustentáveis - que se coadunam com a missão do Instituto de desenvolver e aplicar soluções tecnológicas para aumentar a competitividade das empresas e promover a qualidade de vida da população. Para tal será necessário ampliar e reforçar a capacitação material e humana do IPT para pesquisa em temas centrais dentro daqueles eixos, como, por exemplo, sistemas ciberfísicos, sensoriamento e modelagem matemática, o que se pretende atingir com a implantação do presente PDIP. Prevê-se a implementação do projeto por meio de ações em quatro instâncias: Infraestrutura, Recursos Humanos, Capacitação Digital e Geração de Protótipos a partir de atividades experimentais. Os resultados esperados pelo IPT com a implementação do PDIP são: ? Criar as bases de um polo de pesquisa em Transformação Digital tendo como instituições-âncora o próprio IPT e a Universidade de São Paulo; ? Ampliar o portfólio de pesquisa do Instituto e intensificar a interação com empresas e sociedade; ? Alterar o perfil de atividades do Instituto de modo a privilegiar a capacidade de conduzir pesquisa aplicada e gerar inovaç. , Situação: Em andamento; Natureza: Pesquisa. , Integrantes: Brenno Castrillon Menezes - Coordenador / Mario Yoshikazu Miyake - Integrante / Adriano Galindo Leal - Integrante / Alessandro Santiago dos Santos - Integrante / Zehbour Panossian - Integrante., Financiador(es): Fundação de Amparo à Pesquisa do Estado de São Paulo - Auxílio financeiro.

• 2018 - Atual

  From Biological Platforms to Biorefineries, Descrição: A radical change in production paradigms is needed to face prospects for the exhaustion of the sources of some strategic raw materials and for important environmental issues. This project proposes a new model for the development of processes and products based on sustainability premises, on the use of biological conversion platforms and on a multi-scale approach of the industrial project. This model is based on: - The new concept of biological platforms based on the flexibility to satisfy the needs for biosynthesis of different bioproducts; - Introducing environmental performance goals in the process at an early stage, such as the process conceptual design; - Integrate the different scales of metabolic modeling, process synthesis and strategic planning in a multi-scale framework; The main objective of this project is to have the technological mastery in Systems Biology and the integration of different scales in the design of processes and products aiming to consolidate a national multidisciplinary group integrating Biologists and Chemical Engineers. The multiplication of this new industrial paradigm for the Brazilian society will permit the extension of the biorefinery concept and increase the value of renewable raw materials of which Brazil is a producer per excellence.. , Situação: Em andamento; Natureza: Pesquisa. , Alunos envolvidos: / Mestrado profissional: (4) / Doutorado: (3) . , Integrantes: Brenno Castrillon Menezes - Integrante / Galo Carrilllo Le Roux - Coordenador., Número de produções C, T & A: 1

• 2017 - 2019

  Multi-Unit Data-Driven Real-Time Estimation and Optimization for Complex Process Industry Problems, Descrição: This work uses actual process or operating data with reduced or relaxed-ordered models (ROM) to solve industrial RTO applications of multiple units. Based on the widespread success of model predictive control (MPC) using linear finite impulse or step response dynamic models and quadratic programming (QP) solvers with bias-updating usually configured for a single continuous-process, optimizing the steady-state gains of multiple continuous-processes is straightforward and can have significant payback if this strategy is engineered properly. In the proposed multi-unit data-driven RTO strategy (MU-DD-RTO), the setpoints are determined considering an on-line measurement feedback to incrementally situate the plant/sub-plant to a more profitable operating or processing space. The MU-DD-RTO formulation considers steady-state gains of multiple continuous-processes in a linear programming (LP) for solving on-line (real-time, closed-loop) and in-line (real-time, open-loop) applications and relies on steady-state detection (SSD), steady-state data reconciliation (SSDR) and steady-state gain estimation (SSGE) before doing the steady-state gain optimization (SSGO). We also include nonlinear (NLP) problems in RTO applications around the crude-oil distillation unit (CDU) for a) preheating trains of heat exchangers and b) cutpoint optimization.. , Situação: Concluído; Natureza: Pesquisa. , Alunos envolvidos: Doutorado: (1) . , Integrantes: Brenno Castrillon Menezes - Coordenador / Galo Carrilllo Le Roux - Integrante., Número de produções C, T & A: 1

• 2016 - 2017

  Complex Crude-Oil Refinery Scheduling, Descrição: The project in collaboration with SK Innovation solves the crude-oil blend scheduling involving raw material supply, storage and feed tank operations and the CDU production. Marine vessels supplying a crude-oil refinery with different quality raw materials produce the main CDU distillates: fuel gas (FG), liquid petroleum gas (LPG), light naphtha (LN), heavy naphtha (HN), kerosene (K), light diesel (LD), heavy diesel (HD) and atmospheric residuum (AR). Crude-oils vessels unload the raw material to storage tanks during a time window depending on the arrival time to the refinery. These crude-oils from the storage tanks are then blended into feed or charging tanks in order to feed the CDUs with a desired final blended composition. Given arrival times of marine vessels as well as their amounts and component concentrations, capacity limits of tanks, flow rate limitations, quantities and qualities of initial inventories, bounds on components concentration in CDU and a time horizon, the objective is to determine the setup and amounts of the crude-oil movements in order to maximize the gross margins of the CDU distillates. Adding to the last developments, a) the Feedstock Storage Assignment to cluster similar quality crude-oils when moving them from external supply sources to shared storages and b) the Crude-Oil Blend Scheduling to generate MILP+NLP pairs of solutions to iteratively reduce the multi-stage MILP-NLP gap, an LP reformulation proxies or approximate NLP quality constraints in the MILP stage using what are called "factors". It uses equality balance constraints for each property (factor) between the storage and feed tanks, using slacks or surpluses to guarantee the balance. The desired specifications to select those storage tanks logistically feasible in the MILP problem, provides guidance to assign the storage tanks with lower slacks and surpluses in the logistics optimization. This potentially reduces the MILP-NLP gap as more quality optimization information is programmatically transferred to the logistics optimization. If the quality information is neglected in the MILP problem, several degenerated binary solutions can be found, all with the same MILP objective for different sets of storage to feed tanks assignment, which unfortunately increases the time to reduce the MILP-NLP gap.. , Situação: Concluído; Natureza: Pesquisa. , Integrantes: Brenno Castrillon Menezes - Integrante / Jeffrey D Kelly - Integrante / ignacio E Grossamnn - Coordenador / faramroze engineer - Integrante., Número de produções C, T & A: 9

• 2016 - 2017

  Scheduling and Feed Quality Optimization for Raw Materials in the Metals Industry, Descrição: The project considers scheduled arrival of ships carrying solid concentrates, internal logistics, blending operations, and concentrate smelting. The raw materials are initially received at the port, where they are stored at warehouses and a first mixing step takes place. The mixed materials are sent to the processing facility through a river transportation system. Once the mixtures are received at the production facility, several conveyor belts deliver them to the smelter together with other non-concentrate materials. To solve the problem we develop a multi-period Mixed-Integer Non-Linear Programming (MINLP) model that includes several special features. First, special mixing rules are modeled for small ships and conveyor belts, which introduce non-convex bilinear terms. Second, variations in the concentration of the mixture are undesirable in the smelting process for operational stability. For this reason, penalties are considered for variations in the concentration; they provide a balance between profit and operational stability. In addition to upper bounds for concentrations in the final feed blend, which are common in crude oil scheduling problem, interdependency constraints based on individual element concentrations are considered in our model. As the large scale non-convex MINLP is prohibitively expensive to be solved by global optimization solvers and non-convexities can make a local non-linear solver fail in finding feasible solutions or lead to suboptimal solution, we implement a decomposition scheme for the MINLP formulation representing the quantity-logic-quality phenomena. The propose a two-stage solution approach that involves solving a Mixed-Integer Linear Problem (MILP) that relaxes the non-convex constraints, and a Non-Linear Problem (NLP) that fixes discrete decisions. Several solution strategies, such as rolling horizon, convex relaxations, and heuristics for finding feasible solutions have been implemented to avoid infeasibilities and to reduce the gap between the MILP and NLP problems.. , Situação: Concluído; Natureza: Pesquisa. , Integrantes: Brenno Castrillon Menezes - Integrante / ignacio E Grossamnn - Coordenador / yingkai song - Integrante / pablo garcia-herreros - Integrante., Número de produções C, T & A: 2

• 2015 - 2017

  Integration Strategies for Multi-Scale Optimization in the Oil-Refining Industry, Descrição: The work introduces a generic modeling that can be used for planning (strategic, tactical and operational), scheduling and data-driven RTO. Heuristic strategies to handle with such complicated problem involve a) hierarchical decomposition (HDH) for coordination and collaboration among levels and entities of decision, and b) phenomenological decomposition (PDH) for solving the quantity and logic variables and constrains in a first stage, by neglecting the nonlinearities, and the quantity and quality variables and constrains in a second stage, by fixing the logic variables, and then an iterative procedure integrates the results of both solution until convergence. Decisions from a superior level are updated in the inferior level as an order in a feedforward direction and key indicators from inferior or same levels are informed in a feedback direction to the superior decision-making. The recent work introduces a quantitative analysis of an enterprise-wide optimization for operations of crude-oil refineries considering the integration of planning and scheduling to close the decision-making gap between the selection and procurement of raw materials or feedstocks and the operations of the production scheduling. From a month to an hour, re-planning and re-scheduling iterations can better predict the processed crude-oil basket, diet or final composition, reducing the production costs and impacts in the process and product demands with respect to the quality of the raw materials. The goal of this work is to interface the planning and scheduling decisions within a time-step of a week, so the delivery, storage and mixtures of crude-oil raw materials are made more accurately from the tactical procurement planning up to the blend-scheduling operations. The up-to-down sequence of solutions are integrated in a feedback iteration to both reduce time-grids and as a key indicator of performance.. , Situação: Concluído; Natureza: Pesquisa. , Integrantes: Brenno Castrillon Menezes - Coordenador / Jeffrey D Kelly - Integrante / ignacio E Grossamnn - Integrante., Número de produções C, T & A: 6

• 2014 - 2015

  Industry 4.0, Descrição: The ever-increasing complexity of manufacturing processes has continuously rendered the short-term production scheduling (STPS) a mathematically difficult, but economically relevant decision-making process. To complicate the landscape, the challenges related to this NP-hard problem indeed goes beyond merely improving modeling techniques and algorithms. By nature, STPS is an interdisciplinary, very integrative, and collaborative activity which is highly dependent on working processes and technical education. We argue that STPS is now a major, if not the main, industrial automation challenge (and opportunity as well) for industrial engineers in an Industry 4.0 context. Industry 4.0 is about consistently intermeshing operations of the physical reality with computing and communication infrastructures in a cyber-physical environment. Robustness, autonomy, self-organization, versatility, responsiveness, self-repair, remote diagnosis, real time control, and predictability are underlying principles of production systems based on the Industry 4.0 philosophy. Understanding the organic relationship between STPS and the cyber-physical production environment in a smart scheduling frontline is, therefore, a new open question in process systems engineering. In this research, we study the current state-of-the-art in the field from an industrial perspective. Didactical examples are presented which illustrate how smart scheduling can impact the operation of high-performing oil refineries (or, more generally, the chemical process industry). We conclude that a number of issues must be timely and properly addressed by an experienced interdisciplinary consulting team aiming at overcoming the Herculean challenges related to the transition towards a new reality whose underlying principle is the Internet of Things... , Situação: Concluído; Natureza: Pesquisa. , Integrantes: Brenno Castrillon Menezes - Integrante / Jeffrey D Kelly - Integrante / Mario Yoshikazu Miyake - Coordenador / Marcel Joly - Integrante., Número de produções C, T & A: 2

• 2008 - 2014

  Quantitative Methods for Strategic Investment Planning in the Oil-Refining Industry, Descrição: The strategic investment model is integrated with the operational model from where hydrocarbon processing and blending nonlinearities can give rise to non-convex mixed integer nonlinear problems if a full space model is solved for the strategic and the operational levels simultaneously. Different modeling strategies to tackle the large scale and complex oil-refining asset expansion problem are addressed such as (i) the multisite aggregate capacity approach, (ii) the generalized capital investment planning (GCIP) model with project stages using sequence-dependent changeover concepts from production scheduling, and (iii) the phenomenological decomposition heuristic (PDH) to separate the integer/discrete and nonlinear variables. In terms of oil processing, two new distillation methods in a planning and scheduling environment are proposed. The first is an improved swing-cut modeling, which uses an interfacial property-based linear interpolation to predict quality corrections for the light (upper) and heavy (lower) swing-cut streams using the crude-oil assay distribution curves in pseudocomponents, hypotheticals or micro-cuts discretized into 10ºC increments for example. The second is the distillation curve adjustment or shifting modeling to optimize distillate stream temperature cutpoints using monotonic interpolation. , Situação: Concluído; Natureza: Pesquisa. , Integrantes: Brenno Castrillon Menezes - Coordenador / Ricardo de Andrade Medronho - Integrante / Jeffrey D Kelly - Integrante / ignacio E Grossamnn - Integrante / Lincoln F L Moro - Integrante / fernando l P Pessoa - Integrante., Número de produções C, T & A: 9