System and method for determining corrective action in enterprise wide defrost operations

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Solution Overview

Problem

Existing defrosting methods in refrigeration units are sub-optimal, leading to inaccurate defrosting instructions, inefficient operations, and failure to account for historical frost trends, often resulting in adverse effects on product quality and inefficiency, particularly in enterprise-wide implementations.

Innovation Solution

A system and method utilizing a server with thermal models and machine learning to analyze data from refrigeration units, identify defrost failure instances, and recommend corrective actions based on causal mappings between thermal features and behavior profiles, enabling proactive and accurate defrost management.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If time-based defrosting is used to ensure complete defrosting under all scenarios, then defrosting reliability is improved, but energy consumption increases and product quality deteriorates due to excessive defrosting

Engineering Contradiction:

Improvedefrosting reliabilityVSAvoidenergy consumption

Core Design Contradiction:

ReliabilityVSUse of energy by moving object

Solution Approach 1:

The system dynamically adjusts defrosting parameters (temperature thresholds, duration, intensity) based on real-time sensor data and historical trends. Instead of using fixed time-based parameters, the system modifies defrosting parameters adaptively to match actual frost conditions, ensuring complete defrosting when needed while avoiding excessive defrosting that wastes energy and harms product quality

Inventive Principle:

Principle #35Parameter changes

Solution Approach 2:

The system implements continuous feedback loops using sensors to monitor frost accumulation, temperature, and humidity conditions. This feedback informs the control algorithm to adjust defrosting timing and intensity, ensuring reliable defrosting completion while optimizing energy consumption by avoiding unnecessary defrosting cycles

Inventive Principle:

Principle #23Feedback

2Adaptability or versatility

If adaptive defrosting methods use only recent defrost cycle data, then responsiveness to recent changes is improved, but accuracy deteriorates due to failure to account for historical frost trends

Engineering Contradiction:

Improveresponsiveness to recent changesVSAvoiddefrosting accuracy

Core Design Contradiction:

Adaptability or versatilityVSMeasurement precision

Solution Approach 1:

The system performs preliminary analysis of historical frost accumulation patterns and seasonal trends before executing defrosting operations. By pre-processing and storing historical data, the system can quickly compare current conditions against historical patterns, achieving both responsiveness to recent changes and accuracy through historical context without requiring complex real-time computations

Inventive Principle:

Principle #10Preliminary action

3Productivity

If enterprise-wide defrost management is implemented to improve overall system efficiency, then productivity is improved, but system complexity increases making failure identification and corrective action determination difficult

Engineering Contradiction:

Improvedefrosting efficiencyVSAvoidsystem complexity

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The system segments the enterprise-wide refrigeration network into individual unit profiles, each with its own frost patterns, operational characteristics, and failure modes. This segmentation allows the system to manage complexity by treating each unit independently while still providing enterprise-wide oversight, making failure identification easier through unit-specific error signatures and corrective action recommendations

Inventive Principle:

Principle #1Segmentation

4Ease of operation

If existing defrosting methods are used without root cause analysis, then ease of operation is maintained, but reliability deteriorates due to inability to provide accurate corrective actions

Engineering Contradiction:

Improveoperational simplicityVSAvoidcorrective action accuracy

Core Design Contradiction:

Ease of operationVSReliability

Solution Approach 1:

The system automatically performs root cause analysis by comparing sensor data, frost patterns, and operational parameters against known failure modes and error signatures. This self-service capability enables the system to autonomously identify the underlying causes of defrosting failures and generate accurate corrective action recommendations without requiring manual intervention or complex user analysis, maintaining ease of operation while improving reliability

Inventive Principle:

Principle #25Self-service

Data Source

PatentUS12474099B2System and method for determining corrective action in enterprise wide defrost operations

Publication Date: 2025.11.18 CARRIER CORP

AI summary

A system to determine one or more corrective actions for one or more refrigeration. The system includes a server configured to generate a plurality of defrosting thermal models based on an analysis of a first set of data to generate a plurality of defrosting thermal models, determine, by the plurality of defrosting thermal models, one or more thermal features based on the first set of data and generate one or more behavior profiles associated with the one or more refrigeration units. The server is further configured to define a distinguished causal mapping between the one or more thermal features and the one or more behavior profiles and determine one or more corrective actions for each of the plurality of self-executing defrost failure instances associated with one or more refrigeration units based on the distinguished causal mapping.