The National Trades Union Congress (NTUC) has supported more than 500 companies with its Company Training Committee (CTC) Grant. So far, over 700 projects have been launched to help businesses boost productivity and stay competitive, according to 8World.
The CTC Grant was first launched in 2019 with $100 million in government funding. Earlier this year, Prime Minister Lawrence Wong announced another $200 million top-up to help more firms accelerate business and workforce transformation.
Nearly 10,000 workers have also benefited from the NTUC CTC Grant. On average, they received pay increases of 5% higher than their yearly increments or gained better career development opportunities. This includes professionals, managers and executives.
NTUC shared that more firms are now tapping the grant to adopt artificial intelligence (AI). One example is SBS Transit.
Using the CTC Grant, SBS Transit rolled out an automated Tyre Management System (TMS). In the past, checking each bus’s tyres took maintenance staff 30 to 40 minutes. Now, cameras and sensors scan tyre pressure, wear and tread depth automatically when buses enter the depot. An AI system then analyses the data in real time, providing faster and more accurate maintenance advice.
The system is already in place at Bedok North depot and will be extended to Seletar and Ulu Pandan depots by the end of the year. It is expected to save the company about $200,000 annually.
NTUC Secretary-General Ng Chee Meng visited SBS Transit to see the system in action. He noted that it has already saved 6,000 man-hours, and once fully rolled out, could save 12,000 man-hours while replacing time-consuming manual checks.
SBS Transit has also created a new role called Diagnostic Expert, with a clear career path. Unlike traditional maintenance staff, these specialists focus on data and technology to do their jobs. The company has hired six so far and plans to grow the team to 50.
Looking ahead, SBS Transit will test a new Under-Vehicle Scanning System at Seletar depot next year, and also start training and testing for autonomous buses.
