A laptop computer on display for sale at a Lenovo Group Ltd. store in Hong Kong, China, on Saturday, May 18, 2024. Photographer: Lam Yik/Bloomberg
BEIJING: Sany Heavy Industry has integrated data from over 100 different applications into a centralised system, generating more than 1.2 trillion data points in the past year alone.
This has led to a 30% increase in efficiency, a 50% lift in production capacity, a 60% reduction in labour utility and a 30% reduction in space usage, the Chinese heavy machinery maker said.
Of course, behind these achievements is a partnership between Sany and Chinese tech company Lenovo that is leveraging artificial intelligence (AI) to optimise industrial processes and resource management.
This is part of Lenovo’s broader push to spearhead the integration of AI into traditional industries, significantly enhancing efficiency and productivity across sectors.
Through its AI technologies and comprehensive solutions, Lenovo aims to pave the way for a new era of smart transformation.
Liu Jun, executive vice-president of Lenovo Group and president of Lenovo China, said the company remains committed to its strategic vision of “Smarter AI for All”.“We want to harness the potential of AI to accelerate the smart transformation and upgrade of public organisations, large, small and medium enterprises and consumer clients,” Liu said.
According to him, the company will collaborate with partners to advance China’s push to nurture new quality productive forces and contribute to the high-quality development of the Chinese economy.
Jin Zhuanglong, minister of industry and information technology, said previously that China’s traditional industries are vast and account for over 80% of the manufacturing sector.
These include steel, nonferrous metals, petrochemicals, building materials, light industry, machinery, textiles and apparel, foods and traditional Chinese medicine.
These traditional sectors forming the foundation of the modern industrial system, are crucial for economic development and people’s livelihood, and are essential for maintaining China’s status as the world’s leading manufacturer, Jin said.
“Regardless of the present or the future, traditional industries should not be simply labelled as ‘low-end industries’ and phased out.
“We must prioritise the transformation and upgrading of traditional industries, employing a set of ‘comprehensive measures’ to accelerate their development toward higher-end, smarter and greener directions, allowing traditional industries to ‘blossom anew’,” Jin added.
That is exactly what Lenovo aims to support.
At Qingdao Special Iron and Steel Co Ltd, for instance, Lenovo’s self-developed Daystar AI vision inspection system has replaced workers who monitor production lines.
This system automatically identifies and alerts operational issues on the production line, providing high-quality monitoring and early warning capabilities without being affected by fatigue or emotional factors.Operating around the clock, the system ensures consistent and reliable supervision, highlighting the advantages of AI in maintaining quality control in manufacturing environments, Qingdao Special Iron and Steel said.
Lenovo is also leveraging technology to help the academic sector boost its efficiency.At Nanjing University, Lenovo has established the second phase of the university’s high-performance computing centre.
Over the past six years, the system has operated with a stability rate above 99% and in the past three years, the utilisation rate of central processing units has exceeded 93%.
This demonstrates the company’s capabilities in providing robust and efficient computing solutions for research and educational institutions, Lenovo said.
These examples are part of Lenovo’s broader initiative to drive functional upgrades in traditional industries through AI and data technology.
Lenovo said it is poised to capitalise on the strategic opportunities presented by the AI revolution by leveraging its strong inputs in research and development and rich experience in smart manufacturing and smart services. — China Daily/ANN
