Work Machine Component Replacement Timing Using Dual Life Models
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Solution Overview
Problem
The challenge is to predict the replacement timings of components in work machines accurately, as their lead times from order to delivery are often longer than those of general-purpose machines, leading to potential operational stoppages due to delayed component delivery.
Innovation Solution
A work machine maintenance management system that includes a maintenance management database server and a control device. The system predicts replacement timings by analyzing maintenance management information, determining replacement factors, creating service life and failure models, and using these models to forecast when components need replacement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If replacement timing is predicted early, then operational stoppages can be prevented, but the complexity of the maintenance management system increases
Solution Approach 1:
The maintenance management system is segmented into multiple functional modules: a determination unit that identifies replacement factors, a service life model creation unit, a failure model creation unit, and a replacement timing prediction unit. Each module performs a specific function, allowing the complex prediction task to be divided into manageable components that can be developed and maintained independently.
Solution Approach 2:
The system performs preliminary actions by collecting and analyzing maintenance management information before replacement is actually needed. The determination unit proactively identifies replacement factors, and the model creation units prepare service life and failure models in advance, enabling early prediction of replacement timing and preventing operational stoppages.
2Measurement precision
If multiple models (service life model and failure model) are created for accurate prediction, then prediction accuracy improves, but the computational resources and time required increase
Solution Approach 1:
The system applies partial action by creating different types of models (service life model and failure model) based on the specific replacement factors identified. Not all components require both types of models - the determination unit assesses each component's replacement factors and creates only the necessary models, avoiding unnecessary computational overhead while maintaining prediction accuracy where needed.
Solution Approach 2:
The system changes parameters by using different modeling approaches for different replacement factors. Service life factors use service life models with parameters related to usage time and wear, while failure factors use failure models with parameters related to reliability and probability of failure. This parameter adaptation allows accurate prediction without uniformly applying complex models to all components.
Data Source
AI summary
Provided is a work machine maintenance management system capable of predicting replacement timing of a component of a work machine early. The work machine maintenance management system of this disclosure includes a maintenance management DB server 110 that accumulates maintenance management information of a plurality of work machines and a maintenance management control device 120 that predicts replacement timing of each component of each of the work machines based on the maintenance management information. The maintenance management information includes an actual durable period from start of use to replacement each component of each work machine. The maintenance management control device 120 includes a replacement-factor determining section 121, a service life model creator 122, a failure model creator 123, and a replacement time predictor 126. The replacement-factor determining section 121 determines whether a replacement factor of each component is a service life factor or a failure factor based on an actual durable period of each component of the plurality of work machines. The service life model creator 122 creates a service life model of the component whose replacement factor is determined to be the service life factor by the replacement-factor determining section 121. The failure model creator 123 creates a failure model of the component whose replacement factor is determined to be the failure factor by the replacement-factor determining section 121. The replacement time predictor 126 predicts the replacement timing of each component of each work machine based on the service life model and the failure model.