Agricultural Machinery Maintenance via Predictive Spare Part Delivery

Solution Overview

Problem

Agricultural working machines often experience downtime due to unpredictable component failures and long spare part delivery times, leading to economic inefficiencies and potential damage to other components, as existing methods like regular maintenance and precautionary replacements are not optimal.

Innovation Solution

A method that combines operational data with logistics data to determine the probability of failure and damage, initiating targeted delivery routines for spare parts to service points, reducing the need for large spare part inventories and minimizing downtime by predicting and preparing for likely failures.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If regular maintenance and precautionary replacement of components are performed, then the operational readiness of agricultural machinery is improved, but the economic efficiency deteriorates due to unnecessary replacement of still-functioning parts and extended downtime

Engineering Contradiction:

Improveoperational readinessVSAvoideconomic efficiency

Core Design Contradiction:

ReliabilityVSProductivity

Solution Approach 1:

The system performs preliminary analysis of operating data to predict component failures before they occur. By analyzing trends in operating data and comparing with historical failure patterns, the system initiates spare part delivery routines in advance, allowing maintenance to be performed at the optimal moment rather than through routine scheduled maintenance or reactive replacement.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system continuously monitors operating data from agricultural machinery and uses this feedback to update failure probability assessments. The analysis routine compares current operating conditions with historical data and adjusts predictions accordingly, enabling dynamic optimization of maintenance timing based on actual component condition rather than fixed schedules.

Inventive Principle:

Principle #23Feedback

2Quantity of substance

If spare parts are delivered on demand to service points, then the need for large spare part inventories is reduced, but the point of failure and delivery time cannot be accurately predicted

Engineering Contradiction:

Improvespare part inventoryVSAvoidfailure prediction accuracy

Core Design Contradiction:

Quantity of substanceVSMeasurement precision

Solution Approach 1:

The system performs preliminary analysis of operating data to predict component failures before they occur. By analyzing trends in operating data and comparing with historical failure patterns, the system initiates spare part delivery routines in advance, allowing maintenance to be performed at the optimal moment rather than through routine scheduled maintenance or reactive replacement.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system replaces traditional mechanical inventory management with an information-based prediction system. Instead of relying on physical stockpiling or experience-based estimates, the system uses automated analysis of operating data, logistics data, and failure patterns to precisely predict when and what components will fail, substituting data-driven insights for conventional inventory approaches.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

3Reliability

If components are replaced as a precaution before harvest season, then the risk of failure during harvest is reduced, but functional components are discarded unnecessarily

Engineering Contradiction:

Improveoperational readiness during harvestVSAvoiddiscarded functional components

Core Design Contradiction:

ReliabilityVSLoss of substance

Solution Approach 1:

The system performs preliminary analysis of operating data to predict component failures before they occur. By analyzing trends in operating data and comparing with historical failure patterns, the system initiates spare part delivery routines in advance, allowing maintenance to be performed at the optimal moment rather than through routine scheduled maintenance or reactive replacement.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system changes the decision parameter for component replacement from fixed time-based schedules to condition-based predictions. By continuously monitoring operating parameters and comparing them against failure thresholds derived from historical data, the system determines the optimal replacement moment based on actual component condition rather than arbitrary time intervals, preventing premature replacement of functional components.

Inventive Principle:

Principle #35Parameter changes

Data Source

PatentEP3738421B1Method for maintaining and/or repairing an agricultural work machine

Publication Date: 2023.05.31 CLAAS SELBSTFAHRENDE ERNTEMASCHINEN GMBH

Figure 1

AI summary

The invention relates to a method for the maintenance and/or repair of an agricultural machine (1), wherein, in an analysis routine based on operating data of the agricultural machine (1), a probability of failure duration and/or a probability of damage of the agricultural machine (1) and/or a component (4) of the agricultural machine (1) is determined, and wherein, based on the analysis routine, in order to reduce the probability of failure duration and/or the probability of damage, a delivery routine is initiated comprising the delivery of a spare part (7) corresponding to a component (4) of the agricultural machine (1) to a service point (8) assigned to the agricultural machine (1).