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Redefining Asean’s manufacturing landscape with deep learning

Tan Aik Jin
Tan Aik Jin • 5 min read
Redefining Asean’s manufacturing landscape with deep learning
A cutting-edge robotic vision sensor camera system being utilised at an intelligence factory. Photo: Zebra Technologies
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The manufacturing industry is a key pillar of economic growth and innovation in Asean, with the industry accounting for 21% of the region’s gross domestic product (GDP) and expecting to double to $1.4 trillion by 2028. The industry is expected to grow further, with technology continuing to redefine the manufacturing industry, presenting unprecedented opportunities and challenges alike. Now, more than ever, the impact of technology on the manufacturing sector is profound. Navigating these transformative trends and challenges by harnessing the power of technology is imperative for businesses to thrive in an increasingly dynamic global market. 

According to Zebra’s Automotive Ecosystem Vision Study, 73% of industry decision-makers think their business will be at a competitive disadvantage if they do not embrace more digital technologies, with “developing software expertise” cited as a top five investment priority. In Asia Pacific, manufacturers are increasingly exploring the adoption of Industry 4.0 practices to revolutionise their operations and drive cost-efficiency. A significant focus lies on empowering their workforce to bolster productivity while enhancing the efficiency and precision of their processes. While Asean manufacturing has faced stiff competition from Chinese factories in recent years, the digital technologies associated with Industry 4.0 can help Asean manufacturers overcome relatively low productivity rates to regain their position as global leaders.

An emerging technology innovation that is increasingly gaining significance is deep learning optical character recognition (OCR) software. According to the same Zebra automotive study, industrial machine vision is expected to see an 83% increase in usage between 2023 and 2027 (from 24% to 44%), according to original equipment manufacturer (OEM) decision-makers surveyed.

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