Simulation-Based Dairy Plant Dimensioning
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Solution Overview
Problem
The dimensioning of new plants for producing packaged dairy products is complex due to varied production lines, processing requirements, and the need to account for different production scenarios, often resulting in inconsistent outcomes and excessive investment costs due to oversizing.
Innovation Solution
A computer-implemented method for simulating the production process, which involves obtaining target production data, recipes, and production unit data to determine optimal combinations of production units that achieve production targets, while considering fluid communication and operational capabilities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If dimensioning relies on heuristics and intuition of process engineers, then the process can be completed with existing expertise, but the outcome varies depending on engineer experience and tends to oversize the plant
Solution Approach 1:
The patent replaces the manual heuristic-based dimensioning process with a computer simulation system that automatically calculates optimal plant configuration. The simulation software substitutes human engineers' intuition with algorithmic computation, eliminating variability in outcomes while providing precise, reproducible dimensioning results based on objective criteria rather than subjective judgment.
Solution Approach 2:
The patent creates a virtual replica of the production plant through computer simulation, allowing dimensioning to be performed on the digital model before physical construction. This virtual copy enables testing and optimization of different plant configurations without committing to actual construction, thereby improving accuracy while reducing the complexity of physical trial-and-error approaches.
2Reliability
If the plant is oversized to avoid underproduction risk, then production targets are reliably met, but investment costs increase due to excessive capacity
Solution Approach 1:
The patent applies partial action by determining the minimum necessary plant capacity required to meet production targets, rather than providing excessive capacity. The simulation identifies the optimal subset of production units and configurations that achieve the required output, avoiding the traditional approach of oversizing to ensure reliability. This enables precise matching of capacity to demand, reducing investment costs while maintaining adequate production capability.
3Adaptability or versatility
If multiple production scenarios are considered in dimensioning, then future production flexibility is improved, but the dimensioning process becomes more complex and labor intensive
Solution Approach 1:
The patent performs preliminary action by evaluating multiple production scenarios and configurations during the simulation phase before final plant construction. The software allows users to define various future production scenarios and automatically evaluates how different plant configurations perform across these scenarios. This preliminary analysis identifies configurations that are robust across multiple scenarios, enabling flexible future adaptation without requiring time-consuming re-evaluation later in the process.
Solution Approach 2:
The patent creates a universal dimensioning solution that handles multiple production scenarios simultaneously through a single simulation framework. The software is designed to evaluate diverse product types, production volumes, and operational conditions within one integrated system, eliminating the need for separate analysis processes for each scenario. This multi-functional approach maintains adaptability while significantly reducing the time and effort required compared to traditional methods.
Data Source
AI summary
A computer device implements a method of dimensioning a new plant for production of packaged dairy products by simulation. The method operates by obtaining a production target for dairy products to be produced and packaged in the production plant, by obtaining recipes for production of the packaged dairy products, where each recipe defines ingredients and recipe activities, and by obtaining production unit data that associates each of a plurality selectable production units with one or more unit activities and a production capacity. The method further performs the simulation by generating, as a function of the recipes and the production unit data, combinations of selectable production units that are connected for fluid communication and operable to perform the recipe activities of the respective recipe to achieve the production target, and evaluating the combinations for selection of at least one combination representing a plant configuration.