Anylogic bank model tutorial software#

Anylogic bank model tutorial software#

The interface of the software solution allowed the planners to adjust model parameters, such as associated costs, weather conditions impeding some processes, resource availability timetables, and prioritization rules. The simulation-based resource optimization used algorithms to allocate resources to work orders and complete these work orders the fastest possible way. The solution developed by Simcastia was based on an AnyLogic maintenance process simulation model and custom optimization algorithms.

Resource-related costs (both regular and extra work hours).

Wells’ production loss costs, including unplanned and scheduled interruptions in operations.

The costs calculated in the model included: All of these elements were modeled as agents with unique properties and behavior patterns. The simulation model included sites with GIS-referenced locations, preventive and corrective work orders consisting of multiple tasks, and resources (staff and equipment) with skills and working hours. They chose AnyLogic simulation software for its unique flexibility, which allowed them to model specific resource behaviors and custom process rules. Simcastia consultants developed a simulation-based optimization solution to manage this complexity. To manage an oil field maintenance system that included many interacting parts, custom policies, constraints, and time-dependent events, using spreadsheets and analytical optimizers was not sufficient. System interface: resource availability screen. The pilot project was carried out for Rincón de los Sauces, an oil field located in Neuquén, Argentina, with 700 wells (including water injection and oil wells), about 100 working crews, and more than 100 weekly maintenance orders. YPF approached Simcastia, the simulation and optimization business unit within Continente Siete (an Argentinian business data science company), to develop a tool for scheduling, resource optimization and project management at all YPF facilities.

This prevented them from creating optimal schedules, resulting in downtime losses and inefficient resource utilization. Multiple planners were assigning tasks for multiple teams without proper coordination between each other. The main problem was that the scheduling process was decentralized, with planners independently allocating hundreds of work orders each month. The analysis showed that the root cause of inefficiencies was the lack of a robust maintenance scheduling process. YPF was aiming to reduce its costs associated with oil wells’ maintenance downtime and equipment breakdown.

Project Management: Distribution of Tasks. As the third largest company in South America, YPF employs 72,000 people directly and indirectly, and holds 92 production blocks and 48 exploration blocks in basins around the country. YPF is the largest oil and gas company in Argentina, with a 43% market share in oil and gas production, and 58% in gasoline.