Predictive Maintenance System for Elevator Parameter Analysis

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Solution Overview

Problem

Conveyance system maintenance, such as elevator systems, is challenging due to the complexity of understanding operating parameters and their interdependencies, making it difficult for maintenance personnel to predict the effects of changing these parameters.

Innovation Solution

A predictive system is introduced that receives requests for analysis of changes to operating parameters, predicts the effects of these changes, and sends responses to user devices, including impact and dependency analyses, along with visual recommendations. The system is trained using engineering specifications, service records, customer complaints, and history of parameter changes, and it performs adaptive learning over time.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If maintenance personnel manually analyze operating parameters and their co-dependencies, then they can understand system behavior, but the complexity and difficulty of understanding increases significantly

Engineering Contradiction:

Improvemaintenance accuracyVSAvoidparameter understanding complexity

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

An AI predictive system is introduced as an intermediary between maintenance personnel and the complex elevator control system. The AI analyzes operating parameters, co-dependencies, and potential effects of changes, presenting simplified recommendations to maintenance staff. This mediator handles the complexity internally while providing user-friendly guidance externally.

Inventive Principle:

Principle #24Intermediary (Mediator)

Solution Approach 2:

The patent replaces manual analytical processes with an AI-based predictive system that automatically analyzes parameter relationships. Machine learning models substitute for human experts' cognitive processes, predicting outcomes of parameter changes without requiring maintenance personnel to deeply understand complex interdependencies.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Productivity

If maintenance personnel change operating parameters without prediction tools, then maintenance activities can proceed quickly, but the risk of unintended consequences increases

Engineering Contradiction:

Improvemaintenance speedVSAvoidparameter change safety

Core Design Contradiction:

ProductivityVSReliability

Solution Approach 1:

The AI predictive system performs preliminary analysis before maintenance personnel implement parameter changes. By predicting effects in advance and providing recommendations, the system enables informed decision-making that maintains both speed and safety. Maintenance staff can quickly review AI predictions and make decisions without lengthy manual analysis.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system provides feedback to maintenance personnel about predicted effects of parameter changes. This feedback loop includes information about potential unintended consequences, allowing maintenance staff to adjust their plans before implementation, thereby preventing harmful outcomes while maintaining efficient workflow.

Inventive Principle:

Principle #23Feedback

Data Source

PatentUS20250083926A1Assisted conveyance system maintenance

Publication Date: 2025.03.13 OTIS ELEVATOR CO

AI summary

A method of providing assisted conveyance system maintenance includes receiving, at a predictive system, a request for analysis of a change of an operating parameter of a conveyance system; at the predictive system, predicting an effect of changing the operating parameter of the conveyance system; and sending, from the predictive system to a user device, a response including the effect of changing the operating parameter of the conveyance system.