Inside Singapore’s push to transform manufacturing through AI and automation

Inside Singapore’s push to transform manufacturing through AI and automation

Cost, labour, and competitive pressures push manufacturers to artificial intelligence, advanced engineering.


Visitors and exhibitors gathered around a large interactive city model at a technology and innovation exhibition, with booths showcasing AI and advanced manufacturing solutions in the background.

Visitors at the Singapore pavilion viewing a scale model of the Jurong Innovation District at Hannover Messe 2026.

At one of the world’s largest industrial trade fairs, held recently in Germany over a week in late April, the future of manufacturing was on full display.

Inside Hannover Messe’s vast exhibition grounds – spanning over 1.4 square kilometres, roughly twice the size of Bishan-Ang Mo Kio Park – robotic arms whirred through automated processes as companies pitched solutions to boost productivity and cut costs.

At the Singapore pavilion, however, the focus was less on spectacle. A model of Jurong Innovation District drew visitors to a different story: how the Republic is reshaping its manufacturing base to stay competitive in a complex and cost-pressured world.

Led by the Singapore Economic Development Board (EDB), the Singapore pavilion also featured the Agency for Science, Technology and Research (A*STAR), Enterprise Singapore, and JTC Corporation, alongside local firms showcasing solutions including AI-powered systems and robotics.

While Singapore is better known today as a financial hub, manufacturing has long been central to its economy, accounting for about 20 per cent of gross domestic product. This makes it one of the country’s largest economic sectors; the government has stated it has made a long-term decision to maintain this share.

EDB executive vice-president Cindy Koh said that Singapore’s manufacturing sector has evolved into a “diverse, technologically advanced, and globally connected” one, through consistent investments into R&D and infrastructure.

This has helped the country build leadership positions in industries such as aerospace, semiconductors, and biomedical sciences, she added.

Koh said that EDB “works closely with leading manufacturers to deepen their capabilities here”, while attracting firms to use Singapore as a base for regional and global growth.
 


Many manufacturers also base innovation and headquarters functions here, she said, creating “a diversity of career opportunities and progression pathways for Singaporeans”.

In manufacturing, the median monthly wage is more than S$6,000.
 

What’s leading transformation?

The transformation from the labour-intensive factories of early Jurong to today’s high-tech sectors has been driven by several factors.

The first is Singapore’s limited land, said JTC’s assistant chief executive Christine Wong.

JTC manages more than 80 per cent of industrial land in Singapore, in estates such as Jurong Innovation District, Jurong Island, one-north, and Punggol Digital District.

“Whatever we do on the land has to be quite value-added,” said Wong. “That’s why we focus on sectors and manufacturing activities that generate higher value.”

Another factor is jobs.

Wong said that as Singapore’s economy evolves, the focus is increasingly on creating higher-value jobs for Singaporeans.

As manufacturing becomes more sophisticated, she said, it is generating more skilled roles in areas such as automation, robotics, and smart factory operations, rather than traditional “grunt work” on production lines.

Competition in the region is also increasing.

Dr Ho Chaw Sing, executive director at A*STAR’s Science and Engineering Research Council, said Singapore therefore has to differentiate itself through higher-value manufacturing, supported by R&D, infrastructure, talent, and industry partnerships.
 

Visitors attending a Singapore exhibition booth focused on advanced manufacturing and AI, with a presentation screen, interactive displays, and industry pavilions in the background.

Attendees at Hannover Messe 2026 listen to a presentation at the Singapore pavilion on the Republic’s advanced manufacturing plans.

For companies on the ground, this shift towards higher-value, technology-driven manufacturing is already reshaping how they operate.

At precision plastic components manufacturer Sunningdale Tech, this has meant taking on more technically demanding work, particularly for the medical technology sector.

James Bywater, the company’s director of corporate strategy, marketing, and public relations, said customers increasingly require products with tighter tolerances, greater reliability, and more complex engineering specifications than in the past.

“The reliability of such products… involves a lot of engineering to make sure they can last for the patient cycle,” he said.

Even products that appear simple often require highly consistent manufacturing processes, particularly in medical applications where there is very little room for failure, Bywater added.

In one project, Sunningdale redesigned the production process for contact lens packaging, doubling the number of parts produced for each moulding cycle from 48 to 96, and enabling output of up to one million parts a day, while reducing costs and reliance on labour.

The company is working with A*STAR on an AI-powered defect-detection and inspection system to improve quality and consistency while reducing manual inspection work.

Beyond boosting productivity, some companies are trying to make manufacturing processes more intelligent and responsive.
 


For Paeonia Innovations, this means giving manufacturers real-time visibility into production processes – something previously difficult to achieve at scale.

It has developed a miniaturised sensing device that analyses molecular-level changes during production, allowing manufacturers to detect issues and make adjustments before batches are completed.

One use case involves monitoring the cleaning of pharmaceutical manufacturing vessels, helping firms avoid over-cleaning – which wastes time, energy, and solvents – while shortening production cycles.

Such delays can be costly in industries such as pharmaceuticals, where contamination or process deviations may only be detected at the end of the manufacturing cycle.

“That’s US$10 million (S$12.7 million) down the drain, easily,” said Paeonia’s chief executive Lennon Lee.
 

Hurdles

But the transition is not without its challenges.

Speakers at a panel discussion at Hannover Messe noted that manufacturers in ASEAN continue to struggle to scale advanced manufacturing solutions, often because of concerns over returns on investment.

However, Tan Ser Hean, managing director of Singapore-based precision engineering firm Abrasive Engineering, said that investing in research and development (R&D) is a long-term plan.

“You will never get immediate results,” he said. “If you want immediate results, then you go and buy off-the-shelf technology.”

But such solutions offer little differentiation, he warned, as “everybody has already done it”, and firms that rely on them risk falling behind competitors that develop their own capabilities.

For Abrasive, this meant investing years into developing its own industrial surface treatment technologies. It worked with research institutes such as A*STAR to accelerate development timelines and expand its range of offerings, helping place it among a relatively small group of specialised global players in the field.

The approach has paid off: Abrasive’s turnover has risen by about 40 per cent since stepping up its R&D efforts over the past decade, with profits increasing in tandem.
 

Building Singapore’s advanced manufacturing ecosystem

Yet, even companies willing to invest heavily in R&D can struggle to deploy AI, robotics, and automation technologies at scale across factory operations.

Dr Wang Wei, deputy executive director at A*STAR’s Singapore Institute of Manufacturing Technology and Advanced Remanufacturing and Technology Centre, said this is often due to reasons such as fragmented and inconsistent factory data – making effective AI model training challenging – as well as shortages of talent with expertise in both AI and manufacturing.

“These gaps are precisely what A*STAR wants to bridge, by helping manufacturers translate promising technologies into practical solutions for the factory floor,” said Dr Wang, who is also the R&D centre director at the Sectoral AI Centre of Excellence for Manufacturing.

To support manufacturers in scaling these technologies, agencies such as JTC and A*STAR are building ecosystems that bring manufacturers, researchers, and technology providers closer together.
 


JTC’s Wong said that newer industrial districts such as Jurong Innovation District were designed not simply as factory zones, but as ecosystems that cluster manufacturers alongside research institutes, universities, and solution providers.

Meanwhile, A*STAR’s Dr Ho, who is also chief executive officer of the National Additive Manufacturing Innovation Cluster, said the agency works with companies to co-develop technologies that can be integrated into real production environments.

This includes supporting knowledge transfer and capability building through researcher secondments and industry partnerships.

“The challenge is no longer just proving that an innovation works in a controlled setting, but ensuring it can perform at scale without disrupting output, quality, and safety,” said Dr Ho.

“What has changed is not just the technology, but the ecosystem around adoption; with stronger platforms, engineering practices, and partner networks to support deployment at scale.”
 

Source: The Business Times © SPH Media Limited. Permission required for reproduction.

Related Content

Subscribe Icon
The latest business insights and news delivered to your inbox
Subscribe now