AUTOMOTIVE LIFE CYCLE
Calculation of remaining life and equipment health index – MHI & RUL
THE NEED _
The objective of the project is to develop an application that enables our client to manage the lifecycle of production equipment and CAPEX investments in their assembly line.
The main need is to establish an estimate of the health index of an industrial asset and its remaining useful life, based on operational data and maintenance activities, while also incorporating the user’s accumulated knowledge and experience in managing such equipment.
This information should be presented in a simple and visual application, focused on specific KPIs that support decision-making related to the lifecycle of CAPEX investments.
THE ADVANTAGES _
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Simplified visualization of “Relative Equipment Health Index” and “Remaining Useful Life” for equipment evaluation.
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Detailed information on failure modes related to equipment degradation throughout its lifecycle.
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Acquisition of operational knowledge and experience through configuration constants based on machine learning models.
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Evaluation of the actual influence of each failure mode, allowing adjustment of its constants to optimize the remaining useful life.
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Includes a simulator to predict the future evolution of the equipment based on operational data.
THE SOLUTION _
The solution consists of developing the ASSETLIFE application and adapting it to a vehicle production plant in a robotized chassis assembly area.
ASSETLIFE __
AssetLife is a web application designed to support those responsible for CAPEX investments and for the acquisition, maintenance, replacement, and decommissioning of industrial production equipment.
It relies on current data to monitor the health index and estimated remaining useful life of assets, thereby enabling informed decision-making for lifecycle management of capital investments.
AssetLife is powered by real-time operational data from the equipment and information from completed maintenance activities. It also encodes and integrates historical knowledge and accumulated experience from equipment managers to provide a comprehensive view.
Based on this information, AssetLife aims to establish simple, visual KPIs that reflect the evolution of equipment health and help prioritize actions—such as replacement investments—for assets with reduced remaining life that require urgent updates.
Additionally, a Data Simulator has been developed as a temporary alternative for real-time machine data ingestion from the plant’s MES systems.
This simulator uses historical data from the station to feed AI models and replicate the station’s historical evolution and behavior.
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