Maintenance Component Management Device for Dynamic Inventory Estimation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current maintenance component management methods rely on statistical estimates that do not consider the actual operating state of machines, leading to inaccurate stockpiling of maintenance components, resulting in inefficiencies and wastefulness.
Innovation Solution
A maintenance component management device and method that acquires and analyzes operating state information from multiple machines to calculate the necessary number of maintenance components based on factors like load, environment, and usage time, allowing for precise estimation and reduced errors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If maintenance components are stockpiled based on past statistical information and experience, then maintenance components are available for supply, but the precision of estimation is poor and excessive stockpiling occurs
Solution Approach 1:
The system collects actual operating state information from multiple machines and feeds it back to the estimation process. The operating state acquisition unit continuously gathers data on machine usage, and this feedback is used to dynamically adjust and improve the accuracy of maintenance component demand predictions, replacing static historical estimates with dynamic real-time data-driven predictions.
Solution Approach 2:
The system changes the estimation parameters from static historical statistics to dynamic operating state parameters. By incorporating real-time parameters such as machine operating hours, load conditions, and environmental factors, the estimation accuracy is significantly improved while reducing unnecessary stockpiling.
2Reliability
If maintenance components are stockpiled based on past statistical information, then components are available for supply, but wastefulness is produced due to excessive stockpiling
Solution Approach 1:
The system enables self-service by allowing machines to automatically report their own operating state information. This automated data collection eliminates the need for manual tracking and provides accurate, real-time information for demand prediction, reducing both wasteful stockpiling and the need for external intervention.
Solution Approach 2:
The estimation approach changes from using static historical parameters to dynamic operating parameters that reflect actual machine usage. This parameter transformation enables more accurate demand prediction, reducing excessive stockpiling and associated wastefulness while maintaining component availability.
3Measurement precision
If determination is made for only one machine tool based on its operating information, then the arrival of maintenance period can be grasped, but it is not possible to make determination for a plurality of machines in entirety
Solution Approach 1:
The system merges the operating state information from multiple machines into a unified dataset. The operating state acquisition unit collects data from multiple machine tools, and the estimation unit processes this combined information to predict maintenance component demand across the entire machine fleet, enabling both accurate individual and collective maintenance planning.
Solution Approach 2:
The system achieves universality by creating a multi-functional estimation framework that can simultaneously determine maintenance needs for individual machines and for the entire machine fleet. The same core estimation algorithm adapts to different scopes by adjusting the input data range, providing both specific and aggregate maintenance predictions.
Data Source
AI summary
The stockpiled number of maintenance components is more appropriately managed. A maintenance component management device (15) includes: an acquisition means (151) for acquiring, from a plurality of maintenance target devices (25) requiring maintenance using a maintenance component, information representing an operating state of each of the plurality of maintenance target devices (25); and a calculation means (152) for extracting information representing a factor of a main cause for performing maintenance using the maintenance component from the information representing the operating state thus acquired, and calculating a number of the maintenance components estimated as becoming necessary in order to maintain the plurality of maintenance target devices (25), based on the information representing the factor thus extracted.