Title:Implementation of Computer Vision Using Intelligent Custom Object Detection Solutions to Improve Asset, Risk and Safety Management System in Several Power Plant
Tags:Artificial Intelligence, Computer vision, Deep Learning, Enterprise Asset management, Enterprise Risk management, object detection, Power Generation and Safety management
Abstract:
PT. PEMBANGKITAN JAWA BALI as a Power Generation Company decided to facing new business horizon as the theme and also the direction to face the unprecedented business challenge in the electricity industry. We are addressing the company to takepart in the global trend through several strategic programs. Among them are asset optimization,Improving Enterprise Risk management (ERM), safety management system and enterprise asset management (EAM) trough innovation, creativity and adoption of new technology.
On other hand Computer Vision has been expanding at a rapid pace over the last decade to reach the equivalent of human vision level, even now it is possible to emulate human vision for performing complex visual tasks faster and even more effectively than humans do. This paper discusses a novel approach to implement computer vision in asset management, Risk Management, and Safety Management System to revolutionize various segments using what we called "Intelligent Customization Object Detection Solutions" that we have already developed over the last 3 years.
This approach involves enhancements for Sense (media detection), Think (Algorithm), and Act (Notification and Reporting) which can be tailored into Asset, Risk, and Safety Management System needs. The case study involves implementation on 5 different major power plants in Indonesia and more in 2022-2023 with multi-billion-dollar asset base and spread over a variety of locations.
Implementation of Computer Vision Using Intelligent Custom Object Detection Solutions to Improve Asset, Risk and Safety Management System in Several Power Plant
Implementation of Computer Vision Using Intelligent Custom Object Detection Solutions to Improve Asset, Risk and Safety Management System in Several Power Plant