Product Mixer Simulation Articles and Tutorials
This knowledge hub contains all articles related to ProductMixer in refinery digital twin models. Explore tutorials, engineering guides, API references, blending algorithms, and practical examples for stream mixing, product blending, and refinery process simulation using the Petroleum Refining Library. More detailed information is available in our Solutions section.
First published: August 01, 2026
ProductMixer Complete Guide for Refinery Product BlendingProductMixer is an LP-based refinery product blending component for AnyLogic refinery simulation and petroleum refining digital twins. This guide provides a comprehensive overview of its operating modes, blend optimization algorithms, fuel blending properties, runtime control, performance metrics, and practical applications for refinery production planning and process optimization.
First published: July 26, 2026
LP-Based Blend Optimization in Refinery SimulationProductMixer uses linear programming (LP) to optimize refinery blending operations by determining the optimal proportions of multiple input streams while satisfying quality, capacity, and operational constraints. This guide explains the mathematical formulation, optimization workflow, supported constraints, and practical implementation of LP-based blend optimization in refinery simulation using the Petroleum Refining Library (PRL).
First published: July 29, 2026
Product Mixer Automatic Blending AlgorithmThe Product Mixer automatically determines the optimal proportions of multiple incoming streams to produce finished products that satisfy quality specifications while maximizing production or minimizing additive consumption. This article explains the operational workflow of the automatic blending algorithm used in refinery simulation and digital twin models.
First published: July 29, 2026
Mathematical Formulation of Automatic Product Blend OptimizationLearn how the ProductMixer blending optimization algorithm automatically generates linear programming (LP) models for refinery product blending. The article covers the mathematical formulation, quality constraints, objective functions, and automatic LP model generation for refinery digital twins.
First published: July 30, 2026
Fuel Blending Properties in ProductMixer: Stream and Final Product CharacteristicsProductMixer uses stream properties and finished product specifications to optimize refinery fuel blending while ensuring that every blend satisfies quality requirements. This article explains how blending properties are defined, managed, and incorporated into the optimization process.
First published: July 30, 2026
Manual Product Blending AlgorithmThe Manual Product Blending Algorithm enables users to implement custom refinery blending strategies by defining their own optimization model, objective function, and operational constraints. Unlike the built-in automatic algorithm, it provides complete control over the blending process while remaining fully integrated with the ProductMixer simulation framework.
First published: August 01, 2026
Product Mixer Performance Metrics in Refinery SimulationProductMixer Performance Metrics provide a comprehensive framework for monitoring, analyzing, and validating refinery blending operations during simulation. The ProductMixer Statistics API organizes performance metrics into five logical categories—Input, Product, Constraint, Additive, and Summary Statistics—covering material flows, product quality, additive consumption, and optimization results. Available for both Automatic Product Blending and Manual Product Blending algorithms, these statistics support refinery Digital Twins, production planning, process monitoring, and blending optimization while providing engineers with a unified interface for evaluating ProductMixer performance.
First published: August 01, 2026
ProductMixer Control in Refinery SimulationThis article describes the ProductMixer runtime control framework for refinery simulation, including configuration properties, public API methods, runtime events, and advanced customization options. It explains how engineers can configure, monitor, and control automatic and manual product blending while integrating ProductMixer with refinery optimization, production planning, and digital twin applications.
