Made in China? Try made in Nigeria, Poland, and the US

China’s sovereign wealth fund recently tapped Goldman Sachs to help invest as much as $5 billion in the US manufacturing industry. Large trends are influencing this decision.

China is no longer the cheap place to manufacture it once was. Hourly manufacturing wages in China have risen by an annual average of 12% since 2001. China is making big strides to improve productivity through advanced technology, but still has just 30 robots per 10,000 workers in manufacturing, compared with Japan’s 323.

To catch up, China has been shifting its global investments from raw materials to manufacturing. Privately owned Chinese companies are making more than 150 investments a year in Africa’s manufacturing sector, up from just two in 2000, according to the Chinese Ministry of Commerce.

But by 2020, the world’s most competitive manufacturing economy won’t be China — but the U.S., followed by China, Germany, Japan, and India, according to global manufacturing executives. How are the rest of these countries making it happen? Strong investments in talent and technology.

Try our Model Factory simulator to see AI and IoT in action

Manufacturing companies have traditionally been slow to react to the advent of digital technologies like intelligent robots, Internet of Things, and artificial intelligence.

To stay (or get) innovative, companies need to embrace new ways of thinking about manufacturing and operations — thus reducing downtime, improving process and product quality, and optimizing product development.

Operations and equipment optimization in the factory setting can generate up to $3.7T of value in 2025, according the McKinsey Global Institute.

The most competitive companies are those that innovate and find new insights at their plants. That’s where Industry 4.0 and cognitive manufacturing — and their abilities to process mountains of data — come in.

“Manufacturers are sitting on a goldmine of data,” said Jiani Zhang, Watson IoT Director of Product Management.

IBM’s Model Factory Simulator

IBM’s Model Factory Simulator

“We hear from customers that their machines have been spitting out data for decades, but they didn’t know what to do with it.”

Manufacturers use cameras for quality control, Zhang said, but “all that tells you is if a product is a ‘pass’ or ‘not pass.’ We can do so much more with those pictures.”

“What kind of defect was it? Does it need to be scrapped or can it be reworked? All the image data is stored and they are not taking advantage of it.”