Automated Maintenance using machine intelligence – Overview
- Keeping issues from happening before they affect operations, processes, goods, or networks is referred to as service.
- Information is collected across time to monitor the condition of the machinery in the maintenance framework.
- The purpose of the application in maintenance automation is to quickly analyse massive amounts of real-time data in order to predict asset degradation intelligently.
- It includes being able to preserve the correct operation of their mission-critical products.
Automate Maintenance using machine intelligence – Top 4 Advantages
- Improve Productivity
- Improve Operational Efficiency
- Improve Business Efficiency
- Improving Employee Satisfaction
How have We Implemented Machine Intelligence to Automate the Maintenance Process in the Manufacturing industry?
- The Vision Intelligence enabled us to build a DIY (Do-It-Yourself) Machine Learning platform to upload images, tag components installed, and train Segmentation algorithms.
- These algorithms will assist the inspection team to automate most of the inspection, take measurements, and compile audit reports.
- Automating inspection using computer Vision Intelligence is a key differentiator amongst their competitors.
- This automation has offered tremendous value, cost-saving, and ROI for the client compared to manual inspection, which had been the industry standard.
- The inspection data can be updated and tagged, and Image segmentation models can be trained by non-technical team members easily in the web-based portal.
- Trained models can be deployed in on-premises or cloud infrastructure.
Market Size: Machine Learning in Manufacturing Industries
The global machine learning (ML) market is expected to grow from $21.17 billion in 2022 to $209.91 billion by 2029, at a CAGR of 38.8% in the forecast period