Blender Sensor-Based Adaptive Control for Consistent Food Texture

Resolve Bottlenecks,
Find Innovative Solutions
Generate Solutions

Solution Overview

Problem

Existing blenders lack adaptability in processing food items, leading to inconsistent outcomes in texture and quality due to fixed operational sequences that do not account for varying conditions and consistencies of food ingredients.

Innovation Solution

A blender system equipped with sensors and a controller that detects physical properties of food items during processing, analyzes these values, and adjusts processing parameters using machine learning and artificial intelligence to achieve desired textures, such as a smoothie.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Ease of operation

If fixed operational sequences are used in blenders, then device complexity is reduced and ease of operation is improved, but manufacturing precision and reliability of food processing outcomes deteriorate

Engineering Contradiction:
Improveease of operationVSAvoidprocessing consistency
Core Design Contradiction:
Ease of operationVSManufacturing precision

Solution Approach 1:

The blender system dynamically adjusts operational parameters (speed, power, duration) based on real-time feedback from sensors monitoring food consistency, texture, and processing stage. This replaces fixed sequences with adaptive control that responds to actual processing conditions, ensuring consistent outcomes while maintaining operational simplicity through automated adjustment.

Inventive Principle:
Principle #15Dynamics

Solution Approach 2:

The system incorporates sensors that continuously monitor processing conditions and provide feedback to the controller, which then adjusts operational parameters accordingly. This closed-loop feedback mechanism ensures that the blender adapts to varying food ingredients and consistency requirements, maintaining processing precision without requiring user expertise.

Inventive Principle:
Principle #23Feedback

2Adaptability or versatility

If sensors and AI control systems are added to blenders, then adaptability and processing precision are improved, but device complexity increases

Engineering Contradiction:
ImproveadaptabilityVSAvoiddevice complexity
Core Design Contradiction:
Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The blender system performs self-diagnosis and self-adjustment through integrated sensors and AI algorithms that automatically detect food type, consistency, and processing stage. The system serves itself by making real-time operational adjustments without user intervention, thereby achieving high adaptability while keeping the user interface simple and the operational procedure straightforward.

Inventive Principle:
Principle #25Self-service

Solution Approach 2:

The control system integrates multiple functions (detection, analysis, decision-making, execution) into a single unified AI controller that handles various food types and processing requirements. This multi-functional integration achieves high adaptability across different ingredients while managing device complexity through consolidated control architecture.

Inventive Principle:
Principle #6Universality (Multi-functionality)

3Reliability

If real-time monitoring and dynamic adjustment are implemented, then processing precision and reliability are improved, but use of energy and device complexity increase

Engineering Contradiction:
ImprovereliabilityVSAvoidenergy consumption
Core Design Contradiction:
ReliabilityVSUse of energy by moving object

Solution Approach 1:

The system implements monitoring and adjustment at critical processing stages rather than continuously throughout the entire process. Sensors activate only when needed to detect food type and consistency, and dynamic adjustment is applied selectively based on processing requirements, thereby maintaining high reliability while reducing unnecessary energy consumption.

Inventive Principle:
Principle #16Partial or excessive action

Applied Scientific Principles

This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.

Function Achieved in This Case

The system enables more accurate and consistent processing of food items by dynamically adjusting blending parameters based on real-time feedback, ensuring optimal texture and quality of the final product.

Implementation Method 1

a motor or heating element, and may be referred to herein as controllable components

Methodology Applied
Scientific EffectElectromagnetic induction: Electromagnetic Induction

Implementation Method 2

the controller may receive at least one detection signals based on power consumption of the motor sensed by one or more sensors

Methodology Applied
Scientific EffectElectrical resistance measurement: Electrical Resistance

Data Source

PatentEP4505921A1Intelligent blending and user interface
Publication Date: 2025.02.12 SHARKNINJA OPERATING LLC
  • EP4505921A1 patent drawingFigure 1
  • EP4505921A1 patent drawingFigure 2
  • EP4505921A1 patent drawingFigure 3

AI summary

A food processor system includes a user interface including a plurality of indicators, the user interface configured to receive a user input. A monitoring device is configured to detect at least one property associated with processing one or more food items and generating at least one detection signal. A controller is configured to control operations of a controllable component based on receiving the at least one detection signal, identifying one or more types of food items based on the received at least one detection signal, activating of a first indicator of the plurality of indicators on the user interface, and determining of one or more food processing actions based at least in part on the identified one or more types of food items.