2024-12-26 23:49:34
Author: IBM / 2023-07-24 00:32 / Source: IBM

EGAT drives sustainable operations with IBM AI

EGAT drives sustainable operations with IBM AI

EGAT drives sustainable operations with IBM AI

BANGKOK,June 22,2022 --Electricity Generating Authority of Thailand(EGAT),an agency that oversees the Thailand'spower security under the Ministry of Energy,announced today that it has expanded the use of AI-powered asset management solutions to all power plants.

This includes its baseload and renewable power plants covering more than one million high-value assets in total. This transformation will help drive more accurate and faster power production,prediction,and planning,that can help lower the cost of power production and enable EGAT to better support the electricity price for Thailand. The increased efficiency also leads to less carbon footprint and help drive a more sustainable operations.

The integrated,single view of insights on power production and maintenance of all its power plants are keys to EGAT to move towards sustainable operations and reduce its carbon footprint in order to comply with Thailand's energy sector 'Carbon Neutrality' goal,with a balance between power production cost,impact on environment and the reliability of Thailand's power system.

Paitoon Tangjitruamboon,Assistant Governor Generation of EGAT,said"EGAT today looks not only at adopting technology to maximize efficiency and minimize capital expenditure,but also at how it can bring benefits to citizens while taking into account the sustainability aspects of asset management and reduced adverse environmental impact. Being able to reduce our power production cost enables EGAT to better support the electricity price for Thailand. In addition,the proven increased production efficiency also leads to the expanded use of IBM's AI-powered asset management system at our hydroelectric and solar power plants. This drive towards clean energy practice will help EGAT reduce carbon footprint and achieve our environmental sustainability goals."

EGAT started adopting IBM's AI-powered Maximo Enterprise Asset Management solutions in January 2021 with Triple Dot Consulting Co.,Ltd.,an IBM business partner. The integrated insights from all power plants allow EGAT to predict asset failure andmaintenance,while also managing its assets with inventory analytics. This has lowered the cost of purchasing new equipment,reduced unnecessary space utilization,and extended strategic asset lifecycles.

The virtual management of its inventory,together with the use of machine learning,allows EGAT to see health scoring and life of each component in real time,which helps minimize the unplanned downtime,disruption and asset failure. Predictive maintenance alsoleads to decreased time that EGAT's inspectors need to spend onmonitoring assets.

Surarit Wuwong,Country Manager for IBM Thailand's Technology Group,said "organizations today must be equipped with fast and accurate asset monitoring and predictive maintenance capabilities,with unified data and all the relevant devices being integrated in real time. Most importantly,sustainability aspects should be included into an investment decision. EGAT today is leading the way,not only in Thailand but also in ASEAN,with three imperatives for modern asset management: scalable,sustainable and real-time inspection and monitoring anywhere,anytime,on any device."

Extreme weather,climate action failure and human-led environmental damage were cited as the top three most likely risks for businesses over the next ten years in the World Economic Forum's Global Risks Report 2021.

About IBM Maximo Enterprise Asset Management:


IBM (NYSE: IBM) Maximo Enterprise Asset Management is today deployed across 99 countries,seven continents and used by many of the world'slargest organizations. For more information,please visitwww.ibm.com/products/maximo/asset-management.

Contact:


Paranee Reymondon


IBM Thailand Co.,Ltd.


Email:paranee@th.ibm.com

Tags: Computer Accessories Computer/Electronics Environmental Products & Services Green Technology

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