Brenno Castrillon Menezes

Pós-doutorado

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Participação em eventos

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Orientou

Produções bibliográficas

• ALQASHOUTI, NOOF M. ; Yaqot, Mohammed ; Menezes, Brenno C. . Online Learning and Teaching during the COVID-19 Pandemic in Higher Education in Qatar. Sustainability , v. 16, p. 2265, 2024.

• AL-BANNA, ADNAN ; YAQOT, MOHAMED ; Menezes, Brenno C. . Investment strategies in Industry 4.0 for enhanced supply chain resilience: an empirical analysis. COGENT BUSINESS & MANAGEMENT , v. 11, p. 2298187, 2024.

• AHMEDNOOH, MAHMOUD ; MENEZES, BRENNO . Blend Scheduling Solutions in Petroleum Refineries towards Automated Decision-Making in Industrial-like Blend-Shops. PROCESSES , v. 12, p. 561, 2024.

• RAHMAN, MD. HABIBUR ; MENEZES, BRENNO CASTRILLON ; BALDACCI, ROBERTO . Exploring the role of blockchain technology, warehouse automation, smart routing, and cloud computing in logistics performance. PRODUCTION & MANUFACTURING RESEARCH , v. 12, p. 2393614, 2024.

• Franzoi, Robert E. ; Menezes, Brenno C. ; KELLY, JEFFREY D. ; GUT, JORGE A.W. ; GROSSMANN, IGNACIO E. . Large-scale optimization of nonconvex MINLP refinery scheduling. COMPUTERS & CHEMICAL ENGINEERING , v. 186, p. 108678, 2024.

• RAHMAN, MD. HABIBUR ; MENEZES, BRENNO CASTRILLON ; AL AMIN, MD. . Determination of optimal depot location for a capacitated vehicle routing problem (CVRP) based on gross vehicle weight. International Journal Of Systems Science-Operations & Logistics , v. 11, p. 2339385, 2024.

• AL-BANNA, ADNAN ; YAQOT, MOHAMED ; MENEZES, BRENNO . Roadmap to digital supply chain resilience under investment constraints. PRODUCTION & MANUFACTURING RESEARCH , v. 11, p. 2194943, 2023.

• ALTHABATAH, AREEJ ; Yaqot, Mohammed ; MENEZES, BRENNO ; KERBACHE, LAOUCINE . Transformative Procurement Trends: Integrating Industry 4.0 Technologies for Enhanced Procurement Processes. Logistics-Basel , v. 7, p. 63, 2023.

• ALQASHOUTI, NOOF ; Yaqot, Mohammed ; Franzoi, Robert E. ; Menezes, Brenno C. . Educational System Resilience during the COVID-19 Pandemic-Review and Perspective. Education Sciences , v. 13, p. 902, 2023.

• AL-BANNA, ADNAN ; RANA, ZAID ASHRAF ; Yaqot, Mohammed ; MENEZES, BRENNO . Interconnectedness between Supply Chain Resilience, Industry 4.0, and Investment. Logistics-Basel , v. 7, p. 50, 2023.

• Yaqot, Mohammed ; Menezes, Brenno C. ; KELLY, JEFFREY D. . Real-time coordination of multiple shuttle-conveyor-belts for inventory control of multi-quality stockpiles. COMPUTERS & CHEMICAL ENGINEERING , v. 178, p. 108388, 2023.

• AL-BANNA, ADNAN ; RANA, ZAID A. ; YAQOT, MOHAMED ; Menezes, Brenno C. . Supply Chain Resilience, Industry 4.0, and Investment Interplays: A Review. PRODUCTION & MANUFACTURING RESEARCH , v. 11, p. 1, 2023.

• NABIL, DEWAN HAFIZ ; RAHMAN, MD. HABIBUR ; CHOWDHURY, ALTAF HUSSAIN ; MENEZES, BRENNO CASTRILLON . Managing supply chain performance using a real time Microsoft Power BI dashboard by action design research (ADR) method. COGENT ENGINEERING , v. 10, p. 1, 2023.

• Yaqot, Mohammed ; Menezes, Brenno C. ; Al-Ansari, Tareq . Roadmap to Precision Agriculture Under Circular Economy Constraints. Journal of Information & Knowledge Management , v. 1, p. 2250092, 2022.

• Franzoi, Robert E. ; Menezes, Brenno C. . Large-Scale Discrete-Time Scheduling Optimization: Industrial-Size Applications. IFAC-PAPERSONLINE , v. 55, p. 2581-2586, 2022.

• KELLY, JEFFREY D. ; Menezes, Brenno C. . Advanced Process Control Modeling from an Advanced Planning and Scheduling Perspective. IFAC-PAPERSONLINE , v. 55, p. 878-883, 2022.

• Yaqot, Mohammed ; FRANZOI, ROBERT EDUARD ; ISLAM, ASHHADUL ; Menezes, Brenno C. . Cyber-Physical System Demonstration of an Automated Shuttle-Conveyor-Belt Operation for Inventory Control of Multiple Stockpiles: A Proof of Concept. IEEE Access , v. 10, p. 127636-127653, 2022.

• ABA, MICHAEL M. ; LE ROUX, GALO A.C. ; Menezes, Brenno C. . Integrated ethanol and gasoline supply chain planning under environmental constraints: A case study of Brazil. COMPUTERS & CHEMICAL ENGINEERING , v. 164, p. 107875, 2022.

• Franzoi, Robert E. ; KELLY, JEFFREY D. ; Menezes, Brenno C. ; SWARTZ, CHRISTOPHER L.E. . An Adaptive Sampling Surrogate Model Building Framework for the Optimization of Reaction Systems. COMPUTERS & CHEMICAL ENGINEERING , v. 152, p. 107371, 2021.

• AHMAD, IFTIKHAR ; SANA, ADIL ; KANO, MANABU ; CHEEMA, IZZAT IQBAL ; Menezes, Brenno C. ; SHAHZAD, JUNAID ; ULLAH, ZAHID ; KHAN, MUZAMMIL ; HABIB, ASAD . Machine Learning Applications in Biofuels? Life Cycle: Soil, Feedstock, Production, Consumption, and Emissions. Energies , v. 14, p. 5072, 2021.

• Franzoi, Robert E. ; Menezes, Brenno C. ; KELLY, JEFFREY D. ; GUT, JORGE A.W. . A Moving Horizon Rescheduling Framework for Continuous Nonlinear Processes with Disturbances. CHEMICAL ENGINEERING RESEARCH & DESIGN , v. 174, p. 276-293, 2021.

• NAFEES, TABASSAM ; BHATTI, ADNAN AHMED ; JADOON, USMAN KHAN ; AHMAD, FAROOQ ; AHMAD, IFTIKHAR ; KANO, MANABU ; MENEZES, BRENNO CASTRILLON ; AHSAN, MUHAMMAD ; SYED, NAVEED UL HASAN . Model-Based Quality, Exergy, and Economic Analysis of Fluidized Bed Membrane Reactors. Membranes , v. 11, p. 765, 2021.

• Franzoi, Robert E. ; Menezes, Brenno C. ; KELLY, JEFFREY D. ; GUT, JORGE A. W. ; GROSSMANN, IGNACIO E. . Cutpoint Temperature Surrogate Modeling for Distillation Yields and Properties. Industrial & Engineering Chemistry Research , v. 59, p. 18616-18628, 2020.

• 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.

• WANG, BOHONG ; ZHANG, HAORAN ; YUAN, MENG ; WANG, YUFEI ; Menezes, Brenno C. ; LI, ZHONGJIE ; LIANG, YONGTU . Sustainable crude oil transportation: design optimization for pipelines considering thermal and hydraulic energy consumption. CHEMICAL ENGINEERING RESEARCH & DESIGN , v. 151, p. 23-39, 2019.

• Menezes, Brenno C. ; KELLY, JEFFREY D. ; LEAL, ADRIANO G. . Identification and Design of Industry 4.0 Opportunities in Manufacturing: Examples from Mature Industries to Laboratory Level Systems. IFAC-PAPERSONLINE , v. 52, p. 2494-2500, 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.

• 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.

• 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.

• 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.

• Yaqot, Mohammed ; MENEZES, BRENNO ; Mohammed, Abdulfatah ; Moloney, Kim . A State-of-the-Art Review and Framework for Human-Centric Automation in Industry 5.0. IFIP Advances in Information and Communication Technology. 1ed.: Springer Nature Switzerland, 2024, v. , p. 385-400.

• Abdul Rahman, Sumaya ; Rizvi, Syeda Warisha Fatima ; Anagnostopoulos, Christos ; MENEZES, BRENNO . Exploring Corporate Social Responsibility Through Sport: A Generative AI Perspective. Communications in Computer and Information Science. 1ed.: Springer Nature Switzerland, 2024, v. , p. 398-415.

• Al-Malki, Nasser ; Yaqot, Mohammed ; Menezes, Brenno C. . Towards CO2 Reduction in Middle East: A Techno-Environmental Assessment. Computer Aided Chemical Engineering. 1ed.: Elsevier, 2024, v. , p. 2311-2316.

• Menezes, Brenno C. ; Duarte, Matheus ; Kuhn, Caiubi ; Gomes, Ana ; Yaqot, Mohammed ; Moloney, Kim . Low Concentrated P- and K-based Fertilizers for Localized Agricultural Supply Chains. Computer Aided Chemical Engineering. 1ed.: Elsevier, 2024, v. , p. 1753-1758.

• HASSAAN, SARAH ; Rahman, Sumaya A. ; BALDACCI, ROBERTO ; Menezes, Brenno C. . Personalized Supply Chain Solutions for Sustainable Fashion: Leveraging Social Media Insights and Machine Learning. Computer Aided Chemical Engineering. 1ed.: Elsevier, 2024, v. , p. 2887-2892.

• AL-BANNA, ADNAN ; Menezes, Brenno C. ; Yaqot, Mohammed ; KELLY, JEFFREY D. . Decision regression for modelling of supply chain resilience in interdependent networks: LNG case. Computer Aided Chemical Engineering. 1ed.: Elsevier, 2023, v. , p. 1113-1118.

• Ahmednooh, Mahmoud A. ; Menezes, Brenno C. ; Yaqot, Mohammed ; KELLY, JEFFREY D. . Blend-scheduling optimisation for continuous and batch mixtures: modelling and solving algorithms. Computer Aided Chemical Engineering. 1ed.: Elsevier, 2023, v. , p. 1783-1788.

• Yaqot, Mohammed ; Menezes, Brenno C. . Integrating mineral mining and metallurgical supply chains: a qualogistics approach. Computer Aided Chemical Engineering. 1ed.: Elsevier, 2023, v. , p. 1759-1764.

• FRANZOI, R. E. ; ALQASHOUTI, N. ; MENEZES, B. C . Decision-making framework for improved educational resilience under pandemic events. In: Ludovic Montastruc; Stephane Negny. (Org.). Computer Aided Chemical Engineering. 1ed.: , 2022, v. 51, p. 1681-1686.

• FRANZOI, R. E. ; AHMEDNOOH, M. A. ; MENEZES, B. C. . An industrial perspective on simulation versus optimisation decision-making capabilities. In: Ludovic Montastruc; Stephane Negny. (Org.). Computer Aided Chemical Engineering. 1ed.: , 2022, v. 51, p. 979-984.

• FRANZOI, R. E. ; MENEZES, B. C. . Towards improved scheduling: an analysis on time-steps, time-horizon, and rescheduling. In: Ludovic Montastruc; Stephane Negny. (Org.). Computer Aided Chemical Engineering. 1ed.: , 2022, v. 51, p. 1003-1008.

• YAQOT, M. ; MENEZES, B. C. ; FRANZOI, R. E. . Interplaying of industry 4.0 and circular economy in cyber-physical systems towards the mines of the future. In: Ludovic Montastruc; Stephane Negny. (Org.). Computer Aided Chemical Engineering. 1ed.: , 2022, v. 51, p. 1609-1614.

• FRANZOI, R. E. ; MENEZES, B. C. ; KELLY, J. D. ; SWARTZ, CHRISTOPHER L.E. . Adaptive least-squares surrogate modeling for reaction systems. In: Yoshiyuki Yamashita, Manabu Kano. (Org.). Computer Aided Chemical Engineering. 1ed.: , 2022, v. 49, p. 1705-1710.

• Al-Banna, Adnan A.M..A. ; FRANZOI, R. E. ; MENEZES, B. C. ; ROGERS, S. ; KELLY, J. D . Roadmap to digital supply chain resilience. In: Yoshiyuki Yamashita, Manabu Kano. (Org.). Computer Aided Chemical Engineering. 1ed.: , 2022, v. 49, p. 571-576.

• AL-HAMMADI, AISHA ; FRANZOI, R. E. ; IBRAHIM, O. ; MENEZES, B. C. . Surrogate modeling for mixed refrigerant streams in the refrigeration cycle of an LNG plant. In: Yoshiyuki Yamashita, Manabu Kano. (Org.). Computer Aided Chemical Engineering. 1ed.: , 2022, v. 49, p. 1795-1800.

• ALI, TASABEH ; FRANZOI, R. E. ; MENEZES, B. C. . Surrogate modeling for nonlinear gasoline blending operations. In: Yoshiyuki Yamashita, Manabu Kano. (Org.). Computer Aided Chemical Engineering. 1ed.: , 2022, v. 49, p. 1783-1788.

• MENEZES, B. C. ; Sawaly, Mohamed E.H. ; Yaqot, Mohammed ; FRANZOI, R. E. ; KELLY, J. D. . Design and operation of healthcare facilities using batch-lines: the COVID-19 case in Qatar. In: Yoshiyuki Yamashita, Manabu Kano. (Org.). Computer Aided Chemical Engineering. 1ed.: , 2022, v. 49, p. 2209-2214.

• Yaqot, Mohammed ; Menezes, Brenno C. ; Al-Ansari, Tareq . Unmanned aerial vehicles in precision agriculture towards circular economy: a process system engineering (PSE) assessment. Computer Aided Chemical Engineering. 1ed.: Elsevier, 2021, v. 50, p. 1559-1565.

• Menezes, Brenno C. ; Franzoi, Robert E. ; Yaqot, Mohammed ; Sawaly, Mohamed E.H. ; Al-Banna, Adnan A.M..A. ; Ashkanani, Salman ; KELLY, JEFFREY D. . Complementarities of part-time and full-time postgraduates in process systems engineering (PSE): when industry and academia merges. Computer Aided Chemical Engineering. 1ed.: Elsevier, 2021, v. 50, p. 2057-2063.

• Mohamed, Ahmed H.A. ; Menezes, Brenno C. ; Al-Ansari, Tareq . Interplaying of food supply chain resilience, industry 4.0 and sustainability in the poultry market. Computer Aided Chemical Engineering. 1ed.: Elsevier, 2021, v. 50, p. 1815-1820.

• Yaqot, Mohammed ; MENEZES, B. C. . The Good, the Bad, and the Ugly: Review on the Social Impacts of Unmanned Aerial Vehicles (UAVs). Lecture Notes on Data Engineering and Communications Technologies. 1ed.: , 2021, v. 127, p. 413-422.

• MENEZES, B. C. ; FRANZOI, R. E. ; Yaqot, Mohammed ; Sawaly, M. E. H. ; SANFILIPPO, A. . Advanced Analytics for Medical Supply Chain Resilience in Healthcare Systems: An Infection Disease Case. Lecture Notes on Data Engineering and Communications Technologies. 1ed.: , 2021, v. 127, p. 759-768.

• KELLY, JEFFREY D. ; Menezes, Brenno C. . Industrial Software for Computer Aided Process Engineering (CAPE) Modeling and Programming Skills Development. Computer Aided Chemical Engineering. 1ed.: Elsevier, 2020, v. 48, p. 2035-2040.

• Menezes, Brenno C. ; KELLY, JEFFREY D. ; Al-Ansari, Tareq . Livestock Production Planning with Batch-lines in the Agriculture Industry. Computer Aided Chemical Engineering. 1ed.: Elsevier, 2020, v. 48, p. 463-468.

• 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.

• KELLY, JEFFREY D. ; Menezes, Brenno C. . Industrial Modeling and Programming Language (IMPL) for Off- and On-Line Optimization and Estimation Applications. Springer Optimization and Its Applications. 1ed.: Springer International Publishing, 2019, v. , p. 75-96.

• 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.

• Yaqot, Mohammed ; Menezes, Brenno C. ; MOHAMMED, A. ; MOLONEY, K. . A State-of-the-Art Review and Framework for Human-Centric Automation in Industry 5.0. In: IFIP Advances in Information and Communication Technology, 2024. IFIP Advances in Information and Communication Technology.

• RAHMAN, S. A. ; RIZVI, S. W. F. ; ANAGNOSTOPOULOS, C. ; Menezes, Brenno C. . Exploring Corporate Social Responsibility Through Sport: A Generative AI Perspective. In: Communications in Computer and Information Science, 2024. Communications in Computer and Information Science, 2024.

• Menezes, Brenno C. . Towards CO2 Reduction in Middle East: A Techno-Environmental Assessment. In: ESCAPE, 2024, Firenze. Computer Aided Chemical Engineering, 2024.

• Menezes, Brenno C. . Low Concentrated P- and K-based Fertilizers for Localized Agricultural Supply Chains. In: ESCAPE, 2024, Firenze. Computer Aided Chemical Engineering, 2024.

• Menezes, Brenno C. . Personalized Supply Chain Solutions for Sustainable Fashion: Leveraging Social Media Insights and Machine Learning. In: ESCAPE, 2024, Firenze. Computer Aided Chemical Engineering, 2024.

• Menezes, Brenno C. ; AHMEDNOOH, M. A. . Ethanol Increase in Gasoline and its Impacts in Manufacturing and Supply Chains. In: ESCAPE, 2024, Firenze. Computer Aided Chemical Engineering, 2024.

• MÉNDEZ, CARLOS ; MENEZES, BRENNO CASTRILLON ; CONTESTABILE, MARCELLO ; BIÇER, YUSUF . HYDROGEN MOBILITY FOR QATAR: A COMPARISON BETWEEN CONVENTIONAL, ELECTRIC AND HYDROGEN FUEL CELL VEHICLES USING LIFE CYCLE COST ANALYSIS. In: SDP 2024, 2024, Seville, 2024. p. 347.

• RAHMAN, MD. HABIBUR ; MÉNDEZ, CARLOS ; BALDACCI, ROBERTO ; Menezes, Brenno C. . Towards sustainable transportation: hydrogen?s evolution in road freight transportation and its adoption in the Gulf-Europe transportation corridor. In: 2024 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM), 2024, Bangkok. 2024 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM), 2024. p. 0363.

• BAHAMEISH, BEDOOR ; Yaqot, Mohammed ; MENEZES, BRENNO . Supplier Segmentation in Large Enterprises: A Supervised Machine Learning Approach. In: 2024 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM), 2024, Bangkok. 2024 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM), 2024. p. 1469.

• Yaqot, Mohammed ; ALBANNA, ADNAN ; MENEZES, BRENNO . Practical Roadmap to Precision Agriculture Considering Circular Economy Constraints. In: 2023 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM), 2023, Singapore. 2023 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM), 2023. p. 0880.

• RAHMAN, MD. HABIBUR ; Yaqot, Mohammed ; Menezes, Brenno C. . Towards Circular Economy in Manufacturing Industries Based on Industry 4.0 Technologies. In: 2023 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM), 2023, Singapore. 2023 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM), 2023. p. 1502.

• YAQOT, M. ; MENEZES, B. C. . Integrating mineral mining and metallurgical supply chains: a qualogistics approach. In: 33rd European Symposium on Computer Aided Process Engineering, 2023, Athens. 33rd European Symposium on Computer Aided Process Engineering, 2023. v. 52. p. 1759-1764.

• AL-BANNA, ADNAN ; MENEZES, B. C. ; YAQOT, M. ; KELLY, J. D. . Decision regression for modelling of supply chain resilience in interdependent networks: LNG case. In: 33rd European Symposium on Computer Aided Process Engineering, 2023, Athens. 33rd European Symposium on Computer Aided Process Engineering, 2023. v. 52. p. 1113-1118.

• AHMEDNOOH, M. A. ; MENEZES, B. C. ; YAQOT, M. ; KELLY, J. D. . Blend-scheduling optimisation for continuous and batch mixtures: modelling and solving algorithms. In: 33rd European Symposium on Computer Aided Process Engineering, 2023, Athens. 33rd European Symposium on Computer Aided Process Engineering, 2023. v. 52. p. 1783-1788.

• MENEZES, BRENNO ; Yaqot, Mohammed ; HASSAAN, SARAH ; FRANZOI, ROBERT ; ALQASHOUTI, NOOF ; AL-BANNA, ADNAN . Digital Transformation in the Era of Industry 4.0 and Society 5.0: A perspective. In: 2022 2nd International Conference on Emerging Smart Technologies and Applications (eSmarTA), 2022, Ibb. 2022 2nd International Conference on Emerging Smart Technologies and Applications (eSmarTA), 2022. p. 1.

• Yaqot, Mohammed ; Menezes, Brenno C. . Digital Trends in the Mining Industry Value Chain. In: 2022 2nd International Conference on Emerging Smart Technologies and Applications (eSmarTA), 2022, Ibb. 2022 2nd International Conference on Emerging Smart Technologies and Applications (eSmarTA), 2022. p. 1.

• MENEZES, B. C. ; KELLY, J. D. ; ELSHERIF, M. ; FRANZOI, R. E. . INDUSTRIAL MODELING AND PROGRAMMING LANGUAGE (IMPL) FOR COMPLEX DATA ANALYTICS AND DECISION-MAKING PROBLEMS. In: 11th International Conference on Theory and Practice in Modern Computing, TPMC 2022, 2022, Lisbon. 11th International Conference on Theory and Practice in Modern Computing, TPMC 2022, 2022.

• MENEZES, B. C. . Mining Process Systems in the Industry 4.0 Mandate Towards the Plant of Future. In: The 5th European International Conference on Industrial Engineering and Operations Management, 2022, Roma. Proceedings of the International Conference on Industrial Engineering and Operations Management. Michigan: IEOM Society International, 2022. p. 713.

• MENEZES, B. C. . Artificial Intelligence in Procurement: An Overview and Case Study of Qatar Foundation. In: The 5th European International Conference on Industrial Engineering and Operations Management, 2022, Roma. Proceedings of the International Conference on Industrial Engineering and Operations Management. Michigan: IEOM Society International, 2022. p. 722.

• MENEZES, B. C. . Procurement 4.0: Drivers, Challenges, Remedies, and Benefits. In: The 5th European International Conference on Industrial Engineering and Operations Management, 2022, Roma. Proceedings of the International Conference on Industrial Engineering and Operations Management. Michigan: IEOM Society International, 2022. p. 2662.

• MENEZES, B. C. . Depot Management in an ISO Tank Container Terminal: Challenges and Opportunities. In: The 5th European International Conference on Industrial Engineering and Operations Management, 2022, Roma. Proceedings of the International Conference on Industrial Engineering and Operations Management. Michigan: IEOM Society International, 2022. p. 2669.

• MENEZES, B. C. . Decision-making framework for improved educational resilience under pandemic events. In: 32nd European Symposium on Computer Aided Process Engineering, 2022, Toulouse. 32nd European Symposium on Computer Aided Process Engineering, 2022. v. 51. p. 1681.

• MENEZES, B. C. . An industrial perspective on simulation versus optimisation decision-making capabilities. In: 32nd European Symposium on Computer Aided Process Engineering, 2022, Toulouse. 32nd European Symposium on Computer Aided Process Engineering, 2022. v. 51. p. 979.

• MENEZES, B. C. . Towards improved scheduling: an analysis on time-steps, time-horizon, and rescheduling. In: 32nd European Symposium on Computer Aided Process Engineering, 2022, Toulouse. 32nd European Symposium on Computer Aided Process Engineering, 2022. p. 1003.

• MENEZES, B. C. . Interplaying of industry 4.0 and circular economy in cyber-physical systems towards the mines of the future. In: 32nd European Symposium on Computer Aided Process Engineering, 2022, Toulouse. 32nd European Symposium on Computer Aided Process Engineering, 2022. p. 1609.

• MENEZES, B. C. . Adaptive least-squares surrogate modeling for reaction systems. In: 32nd European Symposium on Computer Aided Process Engineering, 2022, Toulouse. 32nd European Symposium on Computer Aided Process Engineering, 2022. p. 1705.

• MENEZES, B. C. . Roadmap to digital supply chain resilience. In: 14th International Symposium on Process Systems Engineering, 2022, Kyoto. 14th International Symposium on Process Systems Engineering, 2022. p. 571.

• MENEZES, B. C. . Surrogate modeling for mixed refrigerant streams in the refrigeration cycle of an LNG plant. In: 14th International Symposium on Process Systems Engineering, 2022, Kyoto. 14th International Symposium on Process Systems Engineering, 2022. p. 1795.

• MENEZES, B. C. . Surrogate modeling for nonlinear gasoline blending operations. In: 14th International Symposium on Process Systems Engineering, 2022, Kyoto. 14th International Symposium on Process Systems Engineering, 2022. p. 1783.

• MENEZES, B. C. . Design and operation of healthcare facilities using batch-lines: the COVID-19 case in Qatar. In: 14th International Symposium on Process Systems Engineering, 2022, Kyoto. 14th International Symposium on Process Systems Engineering, 2022. p. 2209.

• Yaqot, Mohammed ; Menezes, Brenno C. . Unmanned Aerial Vehicle (UAV) in Precision Agriculture: Business Information Technology Towards Farming as a Service. In: 2021 1st International Conference on Emerging Smart Technologies and Applications (eSmarTA), 2021, Sana'a. 2021 1st International Conference on Emerging Smart Technologies and Applications (eSmarTA), 2021. p. 1.

• Franzoi, Robert E. ; ALI, TASABEH ; AL-HAMMADI, AISHA ; Menezes, Brenno C. . Surrogate Modeling Approach for Nonlinear Blending Processes. In: 2021 1st International Conference on Emerging Smart Technologies and Applications (eSmarTA), 2021, Sana'a. 2021 1st International Conference on Emerging Smart Technologies and Applications (eSmarTA), 2021. p. 1.

• HASSAAN, SARAH ; Yaqot, Mohammed ; Menezes, Brenno C. . The Digital Economy of Crowdsourcing: Crowd Shipping Model as E-Business. In: 2021 1st International Conference on Emerging Smart Technologies and Applications (eSmarTA), 2021, Sana'a. 2021 1st International Conference on Emerging Smart Technologies and Applications (eSmarTA), 2021. p. 1.

• ABUDALU, MUSTAFA ; Menezes, Brenno C. ; AL-FAGIH, LULUWAH ; Yaqot, Mohammed . Poverty in the Gaza Strip: Empowering the Unskilled Workforce to Utilize International Crowdsourcing Markets and Platforms. In: 2021 1st International Conference on Emerging Smart Technologies and Applications (eSmarTA), 2021, Sana'a. 2021 1st International Conference on Emerging Smart Technologies and Applications (eSmarTA), 2021. p. 1.

• ABUDALU, MUSTAFA ; AL-FAGIH, ZAID ; FAGIH, LULUWAH AL ; MENEZES, BRENNO . Emergency Department: Reducing waiting time for lower acuity patients. In: 2021 6th International Conference on Smart and Sustainable Technologies (SpliTech), 2021, Bol and Split. 2021 6th International Conference on Smart and Sustainable Technologies (SpliTech), 2021. p. 1.

• MENEZES, BRENNO ; Yaqot, Mohammed ; HASSAAN, SARAH ; FRANZOI, ROBERT ; ABUDALU, MUSTAFA ; Ashkanani, Salman ; AL-BANNA, ADNAN ; AL-HAMMADI, AISHA ; ALI, TASABEH . Collective Intelligence Coordination and Cooperation in Teamed Part-Time and Full-Time Postgraduates. In: 2021 8th International Conference on Behavioral and Social Computing (BESC), 2021, Doha. 2021 8th International Conference on Behavioral and Social Computing (BESC), 2021. p. 1.

• HASSAAN, SARAH ; Yaqot, Mohammed ; Menezes, Brenno C. . Social Intelligent Computing: The Web Evolution and the Crowdsourcing Impact. In: 2021 8th International Conference on Behavioral and Social Computing (BESC), 2021, Doha. 2021 8th International Conference on Behavioral and Social Computing (BESC), 2021. p. 1.

• Rangel, H P ; MENEZES, B. C. ; PESSOA, F. L. P . Natural gas portfolio optimization for thermopower and petrochemical feeds. In: International Exergy, Energy and Environment Symposium, 2020, Doha. 12th International Exergy, Energy and Environment Symposium, 2020.

• Sawaly, M. E. H. ; MENEZES, B. C. ; Al-Ansari, T. . Vegan burger recipe optimization for meat quality nutrition in the food industry. In: International Exergy, Energy and Environment Symposium, 2020, Doha. 12th International Exergy, Energy and Environment Symposium, 2020.

• Bhatti, A. A. ; Ahmad, I. ; Hussain, A. ; MENEZES, B. C. . Simulation-based design and analysis of fluidized bed membrane reactor for naphtha reforming process. In: International Exergy, Energy and Environment Symposium, 2020, Doha. 12th International Exergy, Energy and Environment Symposium, 2020.

• Jadoon, U. K. ; Ahmad, I. ; Hussain, A. ; MENEZES, B. C. . Development of virtual sensors for prediction of flue gas composition of a cement plant using ensemble learning technique. In: International Exergy, Energy and Environment Symposium, 2020, Doha. 12th International Exergy, Energy and Environment Symposium, 2020.

• Bastida-Escamilla, E. ; Khakifirooz, M. ; MENEZES, B. C. ; Fathi, M. . CO2 emission using road gradient and real-time traffic monitoring in vehicle routing problems.. In: International Exergy, Energy and Environment Symposium, 2020, Doha. 12th International Exergy, Energy and Environment Symposium, 2020.

• Ashkanani, S. ; MENEZES, B. C. . Integration of Refinery Petroleum and Petrochemical Plants for Condensate Feedstock: Challenges and Opportunities. In: International Exergy, Energy and Environment Symposium, 2020, Doha. 12th International Exergy, Energy and Environment Symposium, 2020.

• 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.

• KELLY, J. D ; MENEZES, B. C. ; FRANZOI, R. E . Coefficient-setups for subset selection in model structure identification problems using MILP/ΜIQP. In: AICHE Annual Meeting, 2019, Orlando. AICHE Annual Meeting, 2019.

• FRANZOI, R. E ; MENEZES, B. C. ; KELLY, J. D ; GUT, J. A. W . On the design and solution of an online refinery scheduling algorithm for open-loop and closed-loop strategies. In: AICHE Annual Meeting, 2019, Orlando. AICHE Annual Meeting, 2019.

• FRANZOI, R. E ; MENEZES, B. C. ; KELLY, J. D ; GUT, J. A. W ; GROSSMANN, I. E. . Hybrid Cutpoint Optimization Using Improved Swing-Cut Method and Data Analytics for Separation of Crude-Oils in Distillation Towers. In: AICHE Annual Meeting, 2019, Orlando. AICHE Annual Meeting, 2019.

• 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. ; 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.

• 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, B. C. . Cyber-Security Challenges in Industry 4.0. In: The 5th European International Conference on Industrial Engineering and Operations Management, 2022, Roma. Proceedings of the International Conference on Industrial Engineering and Operations Management. Michigan: IEOM Society International, 2022. p. 2159.

• 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. ; 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).

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

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.

• 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

  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

• 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

• 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