Prepare for AI Technology | The Daily Star

Asian companies should step up efforts to adopt artificial intelligence (AI) technology that is reshaping the traditional manufacturing industry, experts said.

“AI is very important. This is the future,” said Neale G O’Connor, an expert in technology and innovation in manufacturing in China and professor of accounting at Monash University in Malaysia.

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People doubted AI could go that far, Umar Saif, founder of Survey Auto, a big data service provider using machine learning and AI technology.

“Yet AI has made notable strides in the past five to seven years around the world to find applications in services, financial services, manufacturing and supply chain,” a- he declared.

They spoke on Friday at the China Daily Asia Leadership roundtable on “The Future of AI in Manufacturing Industries”, jointly hosted by the Tianjin Municipal People’s Government Information Office, China Daily and Asia News Network.

AI refers to the simulation of human intelligence in machines programmed to think like humans and mimic their actions.

In his presentation, O’Connor said factories need a lot of effort to shift to digitizing documents from manual documentation in order to start capitalizing on the opportunities offered by AI.

He highlighted the major challenge that manufacturers face in growing and shifting to smart manufacturing.

“There is an inherited mindset. Many owners lack a strategic vision to make their factory world class and make world class products. They don’t focus on developing talents and skills. “

“What I mean is that a factory doesn’t have to be fully robotic. Instead, it can still be very labor intensive. It is simply a matter of choosing strategic parts of the production chain to digitize and collect more data.

O’Connor pointed to the concept of “cobots” to explain the impact of automation and smart manufacturing on employment.

Cobots, or collaborative robots, are robots that work with people in a shared workspace and are created to help increase productivity rather than replace human workers.

The obvious opportunities seized by industry players include predictive maintenance, fault detection, yield, line optimization, inventory and parts optimization, O’Connor said.

Wang Yu, a researcher at the College of Intelligence and Computing at Tianjin University in China, said AI has fully penetrated people’s lives and work.

It is widely used in many fields including medical treatment, agriculture, government operations, entertainment, retail, transportation, finance, and manufacturing.

“Manufacturing has the largest capacity in the market. As a result, smart manufacturing has received tremendous attention around the world.”

As all industries have suffered huge losses due to the coronavirus pandemic, they have realized the importance of AI and smart manufacturing.

Automatic production is the future of the manufacturing industry, Yu said.

As part of a survey conducted in Tianjin City last year, a questionnaire was sent to 472 companies. He found that they were paying more attention to smart manufacturing.

He attributed the changes to the pandemic and government support.

“Tianjin sees smart manufacturing as a rare opportunity for economic development. We have every reason to believe that Tianjin and the nation will soon enter an era of smart manufacturing.

Yu provided examples of manufacturing companies using AI to improve their production.

Flying Pigeon, a bicycle maker from Tianjin, took several hours to assemble a bicycle in the 1990s.

“For about eight years, Flying Pigeon has turned their manufacturing into smart manufacturing. What they can do is assemble a bicycle in 15 to 17 seconds,” Yu said.

Umar Saif said the retail market is fragmented in most parts of the world, with family-owned stores dominant due to a few large chains.

Point of sale devices are not used to collect data digitally. As a result, there is no reliable data allowing multinationals to know what people are buying and how much, and by the time they get that information, it is too late.

The forecast is based on an estimate, Saif said, calling the market bleak because there is no data on it.

“Companies could predict market demand and design the manufacturing process from production capacity to supply chain through machine learning and big data analysis from consumption data collected in mom stores and pop by distributors. “

In a pre-recorded presentation, Masahiro Nakamura, CEO of Lexer Research Inc of Japan, said, “We are rushing to AI technologies for a lot of operation, but there are different difficulties in the production process, as well as in the production. and resource management. “

Speaking as a panelist, Ly Ly Cao, reporter for Viet Nam News, said Vietnam has long been famous for its cheap labor and labor-intensive factories.

“But things are improving as industries adopt more and more high technology,” she said, adding that the government has launched policies to support companies adopting high technology.

Applying AI would require big data, and businesses can collect data from a variety of sources. But it would be a challenge to ensure the quality of the data, she said.

Chai Hua, senior business reporter for China Daily Asia Pacific, pointed out the shortage of AI talent with high university degrees and a strong willingness to devote themselves to manufacturing industries.

“We should develop talent training models and accelerate the cultivation of more AI talent in manufacturing.”

DJ Clark, multimedia director of China Daily Asia Pacific, and Pana Janviroj, executive director of Asia News Network, hosted the program.

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