A new rule prioritizing product delivery to the eligible terminal closest to the one being curren... more A new rule prioritizing product delivery to the eligible terminal closest to the one being currently served reduces total accumulated idle volume by about 40% and decreases the number of cut operations. Different priority arrays lead to different delivery schedules, strongly affecting cost-efficiency of the solution achieved. Prioritizing nearest-to-refinery terminals, for instance, may reduce the total volume of segments stopped, but the number of stripping operations will surely increase. Prioritizing the farthest terminals, however, may increase the number and volume of pipeline stoppages. Part 1 of this series (OGJ, Aug. 1, 2011, p. 98) discussed development of the discrete event simulation system on “Arena.” This concluding second part applies the system tomanagement of a real-world products pipeline with a single input and multiple delivery points. The approach described allows use of emerging simulation- based optimization tools to improve performance of the resulting schedules. Future work will focus on developing efficient priority rules combined with heuristic search and rigorous formulations to find cost-efficient and robust solutions for detailed scheduling of multiproduct pipeline networks with different configurations.Fil: Cafaro, Vanina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Desarrollo Tecnológico Para la Industria Química (i); Argentina. Universidad Nacional del Litoral; ArgentinaFil: Cafaro, Diego Carlos. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Desarrollo Tecnológico Para la Industria Química (i); Argentina. Universidad Nacional del Litoral; ArgentinaFil: Mendez, Carlos Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Desarrollo Tecnológico Para la Industria Química (i); Argentina. Universidad Nacional del Litoral; ArgentinaFil: Cerda, Jaime. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Desarrollo Tecnológico Para la Industria Química (i); Argentina. Universidad Nacional del Litoral; Argentin
2021 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)
The supply of materials, equipment and services is an important logistic process for upstream ope... more The supply of materials, equipment and services is an important logistic process for upstream operations in the oil and gas industry. Sizing fleets to timely supply resources is critical to keep rigs running and wells producing. This work presents a novel mixed integer linear programming formulation to address the fleet sizing and contracting problem under uncertainty. A two-stage stochastic optimization approach is proposed, providing a rigorous treatment of the uncertainty associated with the demand of vehicles and availability from suppliers. The mathematical formulation aims to determine the optimal fleet size and contract agreements such that the service level accomplished over the time horizon meets the minimum expected total cost, including contract fees and penalties for the unsatisfied demand. A real-world study case is solved and discussed to draw interesting conclusions.
This work presents the development and application of an advanced modelling, simulation and optim... more This work presents the development and application of an advanced modelling, simulation and optimization-based framework to the efficient operation of the Automated Wet-etch Station (AWS), a critical stage in Semiconductor Manufacturing Systems (SMS). Principal components, templates and tools available in the Arena ® simulation software are used to achieve the best representation of this complex and highly-constrained manufacturing system. The major aim of this work is to provide a novel computer-aided tool to systematically improve the dynamic operation of this critical manufacturing station by quickly generating efficient schedules for the shared processing and transportation devices. This model presents a flexible structure that can be easily adapted to emulate random scenarios with uncertain processing and transfer times. A user-friendly interface for dealing with real-world applications in industry is also introduced.
The management of oil-product pipelines represents a critical task in the daily operation of petr... more The management of oil-product pipelines represents a critical task in the daily operation of petroleum supply chains. Efficient computational tools are needed to perform this activity in a reliable and costeffective manner. This work presents a novel discrete event simulation system developed on Arena ® for the detailed scheduling of a multiproduct pipeline consisting of a sequence of pipes that connect a single input station to several receiving terminals. The pipeline is modeled as a non-traditional multi-server queuing system involving a number of servers at every pipe-end that perform their tasks in a synchronized manner. Based on priority rules, the model decides which server should dispatch the entity waiting for service to the associated depot. Each priority rule can lead to a different delivery schedule, which is evaluated by using several criteria. Combined with optimization tools, the proposed simulation technique permits to easily manage real-world pipelines operations wi...
This work introduces a mixed-integer nonlinear programming (MINLP) formulation based on a hybrid ... more This work introduces a mixed-integer nonlinear programming (MINLP) formulation based on a hybrid approach, combining the potentials of slot-based and general precedence continuous-time representations. We use general precedence sequencing variables to coordinate incoming/outgoing flows to/from every tank, and simultaneously address the scheduling of a long-distance pipeline supplying crude oil batches from harbour to refinery tanks, following a slot-based scheme. The model is able to precisely monitor key component concentrations keeping oil properties within admissible ranges. One of the most important decisions is how to manage oil shipments so as to improve logistics efficiency. Results show that the use of slot-based frameworks combined with general precedence variables for sequencing tasks in linking resources yields orders-of-magnitude savings in the computational effort to reduce costs and find optimal solutions.
Fil: Cafaro, Vanina. Consejo Nacional de Investigaciones Cientificas y Tecnicas. Centro Cientific... more Fil: Cafaro, Vanina. Consejo Nacional de Investigaciones Cientificas y Tecnicas. Centro Cientifico Tecnologico Santa Fe. Instituto de Desarrollo Tecnologico Para la Industria Quimica (i); Argentina. Universidad Nacional del Litoral; Argentina
This work presents the development and application of an advanced modelling, simulation and optim... more This work presents the development and application of an advanced modelling, simulation and optimizationbased framework to the efficient operation of the Automated Wet-etch Station (AWS), a critical stage in Semiconductor Manufacturing Systems (SMS). Lying on the main concepts of the processinteraction approach, principal components and tools available in the Arena simulation software were used to achieve the best representation of this complex and highly-constrained manufacturing system. Furthermore, advanced Arena templates were utilized for modelling very specific operation features arising in the process under study. The major aim of this work is to provide a novel computer-aided tool to systematically improve the dynamic operation of this critical manufacturing station by quickly generating efficient schedules for the shared processing and transportation devices.
This work presents a two-stage stochastic programming model to optimize the expected net present ... more This work presents a two-stage stochastic programming model to optimize the expected net present value (ENPV) of CO2-EOR projects under uncertainty. The mathematical formulation relies on a multi-period planning approach aimed to find the optimal exploitation strategy for a mature oil reservoir. Given uncertain prices and productivity scenarios, the model sets the most convenient time to launch the CO2-EOR project, and establishes efficient operating conditions over the planning horizon. It determines the number of production and injection wells to operate at every period, the CO2 injection rate in every well, and the timing for maintenance and conversion tasks. The problem complexity grows rapidly with the number of wells and scenarios considered, resulting in a large-scale decision-making problem. Well productivity forecast functions are nonlinear (typically hyperbolic), yielding a mixed integer nonlinear (MINLP), nonconvex formulation. A moving horizon framework is adopted to tak...
Fil: Cafaro, Vanina. Consejo Nacional de Investigaciones Cientificas y Tecnicas. Centro Cientific... more Fil: Cafaro, Vanina. Consejo Nacional de Investigaciones Cientificas y Tecnicas. Centro Cientifico Tecnologico - CONICET- Santa Fe. Instituto de Desarrollo Tecnologico para la Industria Quimica (i); Argentina;
Fil: Cerda, Jaime. Consejo Nacional de Investigaciones Cientificas y Tecnicas. Centro Cientifico ... more Fil: Cerda, Jaime. Consejo Nacional de Investigaciones Cientificas y Tecnicas. Centro Cientifico Tecnologico Conicet - Santa Fe. Instituto de Desarrollo Tecnologico para la Industria Quimica. Universidad Nacional del Litoral. Instituto de Desarrollo Tecnologico para la Industria Quimica; Argentina
In this work, we address the scheduling of general maintenance tasks on oil and gas wells and sur... more In this work, we address the scheduling of general maintenance tasks on oil and gas wells and surface facilities, using a mixed integer linear programming (MILP) formulation. The problem involves multitask workorders with precedence relations, comprising both preemptive and nonpreemptive operations, using parallel heterogeneous resources. Crews with different capabilities and work shifts are accounted for. The model introduces novel ideas for expanding the scope of discrete-time formulations. We solve a scheduling problem that includes crew traveling decisions to minimize operational costs and production losses. Different instances of real-world examples are efficiently solved in reasonable times for the industry. Results demonstrate the benefits from optimizing the maintenance schedule of oil and gas production assets and the effectiveness of the solution approach.
Abstract This work introduces a mixed-integer nonlinear programming (MINLP) formulation for the e... more Abstract This work introduces a mixed-integer nonlinear programming (MINLP) formulation for the efficient planning of crude oil supplies to a major refinery, through a long-distance pipeline. The proposed approach combines the potentials of slot-based and general precedence continuous-time representations to simultaneously address two problems that are typically decoupled: pipeline transportation and crude oil blending. General precedence sequencing variables coordinate incoming/outgoing flows to/from every tank, while crude oil batches are traced into the pipeline following a slot-based scheme. The model precisely monitors key component concentrations, keeping oil properties within admissible ranges. Since the proposed formulation is nonconvex, an efficient solution strategy is followed and a tailored relaxation is subsequently solved to assess the quality of the solutions achieved. Results show that the model is able to find very efficient solutions to real-world case studies in modest CPU times.
Abstract Scheduling pumping operations in multiproduct pipelines is a complex logistic task that ... more Abstract Scheduling pumping operations in multiproduct pipelines is a complex logistic task that requires efficient supporting tools. Several approaches have been proposed for solving the pipeline scheduling problem for different pipeline configurations, but up to now the problem of sizing and sequencing oil product batches moving through bidirectional pipelines could not be tackled by continuous-time representations. This work introduces a mixed integer linear programming formulation standing for the first rigorous approach effectively solving the short-term operational planning of bidirectional pipelines.
Abstract This work presents a new continuous-time mixed-integer linear programming (MILP) formula... more Abstract This work presents a new continuous-time mixed-integer linear programming (MILP) formulation for developing the detailed schedule of single-source pipelines by allowing the execution of simultaneous deliveries to multiple receipt terminals. The model takes into account strict operational constraints restricting the flow rates at different pipeline segments and the delivery rates of products into each terminal. The problem goal is to minimize the flow restart and stoppage costs through accomplishing the least number of pumping operations. The solution to a real-world case study using the proposed model presents significant reductions in the operational cost and the CPU time with regards to previous contributions, even accounting for more realistic operating conditions.
A new rule prioritizing product delivery to the eligible terminal closest to the one being curren... more A new rule prioritizing product delivery to the eligible terminal closest to the one being currently served reduces total accumulated idle volume by about 40% and decreases the number of cut operations. Different priority arrays lead to different delivery schedules, strongly affecting cost-efficiency of the solution achieved. Prioritizing nearest-to-refinery terminals, for instance, may reduce the total volume of segments stopped, but the number of stripping operations will surely increase. Prioritizing the farthest terminals, however, may increase the number and volume of pipeline stoppages. Part 1 of this series (OGJ, Aug. 1, 2011, p. 98) discussed development of the discrete event simulation system on “Arena.” This concluding second part applies the system tomanagement of a real-world products pipeline with a single input and multiple delivery points. The approach described allows use of emerging simulation- based optimization tools to improve performance of the resulting schedules. Future work will focus on developing efficient priority rules combined with heuristic search and rigorous formulations to find cost-efficient and robust solutions for detailed scheduling of multiproduct pipeline networks with different configurations.Fil: Cafaro, Vanina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Desarrollo Tecnológico Para la Industria Química (i); Argentina. Universidad Nacional del Litoral; ArgentinaFil: Cafaro, Diego Carlos. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Desarrollo Tecnológico Para la Industria Química (i); Argentina. Universidad Nacional del Litoral; ArgentinaFil: Mendez, Carlos Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Desarrollo Tecnológico Para la Industria Química (i); Argentina. Universidad Nacional del Litoral; ArgentinaFil: Cerda, Jaime. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Desarrollo Tecnológico Para la Industria Química (i); Argentina. Universidad Nacional del Litoral; Argentin
2021 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)
The supply of materials, equipment and services is an important logistic process for upstream ope... more The supply of materials, equipment and services is an important logistic process for upstream operations in the oil and gas industry. Sizing fleets to timely supply resources is critical to keep rigs running and wells producing. This work presents a novel mixed integer linear programming formulation to address the fleet sizing and contracting problem under uncertainty. A two-stage stochastic optimization approach is proposed, providing a rigorous treatment of the uncertainty associated with the demand of vehicles and availability from suppliers. The mathematical formulation aims to determine the optimal fleet size and contract agreements such that the service level accomplished over the time horizon meets the minimum expected total cost, including contract fees and penalties for the unsatisfied demand. A real-world study case is solved and discussed to draw interesting conclusions.
This work presents the development and application of an advanced modelling, simulation and optim... more This work presents the development and application of an advanced modelling, simulation and optimization-based framework to the efficient operation of the Automated Wet-etch Station (AWS), a critical stage in Semiconductor Manufacturing Systems (SMS). Principal components, templates and tools available in the Arena ® simulation software are used to achieve the best representation of this complex and highly-constrained manufacturing system. The major aim of this work is to provide a novel computer-aided tool to systematically improve the dynamic operation of this critical manufacturing station by quickly generating efficient schedules for the shared processing and transportation devices. This model presents a flexible structure that can be easily adapted to emulate random scenarios with uncertain processing and transfer times. A user-friendly interface for dealing with real-world applications in industry is also introduced.
The management of oil-product pipelines represents a critical task in the daily operation of petr... more The management of oil-product pipelines represents a critical task in the daily operation of petroleum supply chains. Efficient computational tools are needed to perform this activity in a reliable and costeffective manner. This work presents a novel discrete event simulation system developed on Arena ® for the detailed scheduling of a multiproduct pipeline consisting of a sequence of pipes that connect a single input station to several receiving terminals. The pipeline is modeled as a non-traditional multi-server queuing system involving a number of servers at every pipe-end that perform their tasks in a synchronized manner. Based on priority rules, the model decides which server should dispatch the entity waiting for service to the associated depot. Each priority rule can lead to a different delivery schedule, which is evaluated by using several criteria. Combined with optimization tools, the proposed simulation technique permits to easily manage real-world pipelines operations wi...
This work introduces a mixed-integer nonlinear programming (MINLP) formulation based on a hybrid ... more This work introduces a mixed-integer nonlinear programming (MINLP) formulation based on a hybrid approach, combining the potentials of slot-based and general precedence continuous-time representations. We use general precedence sequencing variables to coordinate incoming/outgoing flows to/from every tank, and simultaneously address the scheduling of a long-distance pipeline supplying crude oil batches from harbour to refinery tanks, following a slot-based scheme. The model is able to precisely monitor key component concentrations keeping oil properties within admissible ranges. One of the most important decisions is how to manage oil shipments so as to improve logistics efficiency. Results show that the use of slot-based frameworks combined with general precedence variables for sequencing tasks in linking resources yields orders-of-magnitude savings in the computational effort to reduce costs and find optimal solutions.
Fil: Cafaro, Vanina. Consejo Nacional de Investigaciones Cientificas y Tecnicas. Centro Cientific... more Fil: Cafaro, Vanina. Consejo Nacional de Investigaciones Cientificas y Tecnicas. Centro Cientifico Tecnologico Santa Fe. Instituto de Desarrollo Tecnologico Para la Industria Quimica (i); Argentina. Universidad Nacional del Litoral; Argentina
This work presents the development and application of an advanced modelling, simulation and optim... more This work presents the development and application of an advanced modelling, simulation and optimizationbased framework to the efficient operation of the Automated Wet-etch Station (AWS), a critical stage in Semiconductor Manufacturing Systems (SMS). Lying on the main concepts of the processinteraction approach, principal components and tools available in the Arena simulation software were used to achieve the best representation of this complex and highly-constrained manufacturing system. Furthermore, advanced Arena templates were utilized for modelling very specific operation features arising in the process under study. The major aim of this work is to provide a novel computer-aided tool to systematically improve the dynamic operation of this critical manufacturing station by quickly generating efficient schedules for the shared processing and transportation devices.
This work presents a two-stage stochastic programming model to optimize the expected net present ... more This work presents a two-stage stochastic programming model to optimize the expected net present value (ENPV) of CO2-EOR projects under uncertainty. The mathematical formulation relies on a multi-period planning approach aimed to find the optimal exploitation strategy for a mature oil reservoir. Given uncertain prices and productivity scenarios, the model sets the most convenient time to launch the CO2-EOR project, and establishes efficient operating conditions over the planning horizon. It determines the number of production and injection wells to operate at every period, the CO2 injection rate in every well, and the timing for maintenance and conversion tasks. The problem complexity grows rapidly with the number of wells and scenarios considered, resulting in a large-scale decision-making problem. Well productivity forecast functions are nonlinear (typically hyperbolic), yielding a mixed integer nonlinear (MINLP), nonconvex formulation. A moving horizon framework is adopted to tak...
Fil: Cafaro, Vanina. Consejo Nacional de Investigaciones Cientificas y Tecnicas. Centro Cientific... more Fil: Cafaro, Vanina. Consejo Nacional de Investigaciones Cientificas y Tecnicas. Centro Cientifico Tecnologico - CONICET- Santa Fe. Instituto de Desarrollo Tecnologico para la Industria Quimica (i); Argentina;
Fil: Cerda, Jaime. Consejo Nacional de Investigaciones Cientificas y Tecnicas. Centro Cientifico ... more Fil: Cerda, Jaime. Consejo Nacional de Investigaciones Cientificas y Tecnicas. Centro Cientifico Tecnologico Conicet - Santa Fe. Instituto de Desarrollo Tecnologico para la Industria Quimica. Universidad Nacional del Litoral. Instituto de Desarrollo Tecnologico para la Industria Quimica; Argentina
In this work, we address the scheduling of general maintenance tasks on oil and gas wells and sur... more In this work, we address the scheduling of general maintenance tasks on oil and gas wells and surface facilities, using a mixed integer linear programming (MILP) formulation. The problem involves multitask workorders with precedence relations, comprising both preemptive and nonpreemptive operations, using parallel heterogeneous resources. Crews with different capabilities and work shifts are accounted for. The model introduces novel ideas for expanding the scope of discrete-time formulations. We solve a scheduling problem that includes crew traveling decisions to minimize operational costs and production losses. Different instances of real-world examples are efficiently solved in reasonable times for the industry. Results demonstrate the benefits from optimizing the maintenance schedule of oil and gas production assets and the effectiveness of the solution approach.
Abstract This work introduces a mixed-integer nonlinear programming (MINLP) formulation for the e... more Abstract This work introduces a mixed-integer nonlinear programming (MINLP) formulation for the efficient planning of crude oil supplies to a major refinery, through a long-distance pipeline. The proposed approach combines the potentials of slot-based and general precedence continuous-time representations to simultaneously address two problems that are typically decoupled: pipeline transportation and crude oil blending. General precedence sequencing variables coordinate incoming/outgoing flows to/from every tank, while crude oil batches are traced into the pipeline following a slot-based scheme. The model precisely monitors key component concentrations, keeping oil properties within admissible ranges. Since the proposed formulation is nonconvex, an efficient solution strategy is followed and a tailored relaxation is subsequently solved to assess the quality of the solutions achieved. Results show that the model is able to find very efficient solutions to real-world case studies in modest CPU times.
Abstract Scheduling pumping operations in multiproduct pipelines is a complex logistic task that ... more Abstract Scheduling pumping operations in multiproduct pipelines is a complex logistic task that requires efficient supporting tools. Several approaches have been proposed for solving the pipeline scheduling problem for different pipeline configurations, but up to now the problem of sizing and sequencing oil product batches moving through bidirectional pipelines could not be tackled by continuous-time representations. This work introduces a mixed integer linear programming formulation standing for the first rigorous approach effectively solving the short-term operational planning of bidirectional pipelines.
Abstract This work presents a new continuous-time mixed-integer linear programming (MILP) formula... more Abstract This work presents a new continuous-time mixed-integer linear programming (MILP) formulation for developing the detailed schedule of single-source pipelines by allowing the execution of simultaneous deliveries to multiple receipt terminals. The model takes into account strict operational constraints restricting the flow rates at different pipeline segments and the delivery rates of products into each terminal. The problem goal is to minimize the flow restart and stoppage costs through accomplishing the least number of pumping operations. The solution to a real-world case study using the proposed model presents significant reductions in the operational cost and the CPU time with regards to previous contributions, even accounting for more realistic operating conditions.
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Papers by Vanina Cafaro