AI-based Machine Status Analysis
MPDV Mikrolab GmbH
Analyzing Unproductive Times with Artificial Intelligence (AI)
What conditions make your machines particularly productive? What can you do to reduce unproductive times and to increase productivity? Today, the factors influencing productivity are as diverse that conventional statistical analyses usually do not achieve the desired results.
The mApp AI-based Machine Status Analysis uses two basic components to reveal where and when your machines are unproductive:
- a broad basis of historical data
- AI-based algorithms analyzing the data
Use this mApp to get to know the length of time a specific machine status takes compared to the total production time and which combinations of production resources (e.g., machine, tool, material, article) have a particularly positive or negative impact. Display this distribution of machine statuses over time and discover the extensive analysis options available. This allows you to identify trends and verify if the measures you take to reduce unproductive times are efficient.
Your Benefits
Use the mApp AI-based Machine Status Analysis to identify the influencing factors and their combinations leading to unproductive times and to take appropriate countermeasures. The integrated trend analysis helps you track the effectiveness of these measures.
Technical information
The mApp AI-based Machine Status Analysis is part of the HYDRA X categories Resource Management and AI Suite.
The mApp uses data of the Virtual Production Reality (ViPR) of MPDV's Manufacturing Integration Platform (MIP).
AI-based Machine Status Analysis in the MIP ecosystem
Knowing how productive machines are is key in the Smart Factory. MPDV also offers the following mApps:
- Machine Status Analysis: Extensive evaluations of historical machine data
- Machine Performance KPIs: Calculating KPIs, like the OEE.
- AI-based Machine Performance Analysis : Analyzing machine performance with AI.
- AI-based OEE Analysis : Analyzing the OEE with AI.
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