Increased demand for smart manufacturing due to epidemic!

Have you ever heard of Industry 4.0? Hannover Messe, where this phrase was first used in 2011, was originally going to be held on April 20th this year, but it was delayed until July due to the spreading of COVID-19. Meanwhile, a Gartner report indicated that the global manufacturing supply chain was impacted by the pandemic; the shortage of factory labors caused production and capacity to drop at least 20%, and this highlighted the risk of countries relying too much on China’s manufacturing. This drove the urgent demand for smart manufacturing by enterprises.

So what exactly is Industry 4.0, smart manufacturing, and smart factory? Now follow CloudMile and learn how to implement AI to achieve smart manufacturing at once!

What is Industry 4.0, smart manufacturing, and smart factory?

The phrase “Industry 4.0” was first used at the Hannover Messe exhibition in Germany in 2011; two years later, it was used even more popularly by the German government. As AI and Internet of Things (IoT) flourished, it accelerated the global manufacturing industry’s pursuit of digital transformation, integrated thinking, data analysis and information security maintenance trends, and also contributed to the fourth industrial revolution that swept the world.

And what is smart manufacturing? Smart manufacturing is a technology-driven approach; it uses cloud, IoT, big data management, and smart automated equipment to help manufacturers respond swiftly to market demands.

Smart factory is the realization of the smart manufacturing approach; its five key features include connected, optimized, transparent, proactive, and agile maintenance modes. It is actually implemented by applications including collaborative robots, unmanned trucks, and supply chains that are managed by IoT sensors etc.

Benefits brought by smart manufacturing: Increased yield and agile manufacturing

Smart manufacturing provides many benefits starting from the source of the manufacturing value chain – research and development to production, then sales and logistics, customer experience, all the way down to the final link – after-sale services. Take connected factory machines for example, every equipment is connected through internet connection; not only can managers control and monitor production operations from remote locations, the machines can also send abnormality reports automatically to increase product yield. It also reduces the resource and time needed for manual inventory debugging, and so lowering operating costs.

A research report published by Deloitte in 2019 also indicated that companies that transformed into smart factories and smart manufacturing earlier on gained considerable amounts of benefits, including factory output, factory capacity utilization, and labor productivity etc.; they grew an average of 10% in three years. And that’s not it; it is estimated that by 2022, the labor productivity of these companies will increase another 2% and reach 12%. To sum it up, a smart system that is flexible and can be optimized continually can help manufacturers quickly adapt to market changes and accelerate innovation.

Smart manufacturing success stories! Contributed to both high-end manufacturing and epidemic prevention

According to this report, the leader in wafer manufacturing, Taiwan Semiconductor Manufacturing Company (TSMC), had started implementing big data analysis, machine learning, and AI technologies etc. since 2011. In 2016, they initiated a deep machine learning project and had successfully developed smart diagnosis engines and advanced data analysis platforms after that, and even further developed an exclusive set of process precise control systems that reduced the production cycle progress by at least 50%.

Generally speaking, TSMC optimized the process and yield of the machines through machine learning and other technologies; for process control and analysis systems, they anticipated problems they may face when entering advanced processes, and further achieved the task of completing mass production within the shortest time. They also developed precision equipment matching and yield mining analysis modules etc. that are able to reduce process variations and potential yield loss to a minimum.

As the epidemic spreads, smart manufacturing also contributed towards the epidemic prevention; for example, robots were able to cope with the problem of massive labor shortages in supply chains. This report indicated that a Danish company UVD Robots ApS launched mobile robots to help disinfect hospitals and wards, and a Canadian drone company DDC also used drones to deliver medicine and other related supplies.

Using both Cloud and AI, CloudMile assists in agile transformation for manufacturers

Comprehensively speaking, CloudMile can help manufacturers realize the following two major goals:

1. Help manufacturers lighten their infrastructure

2. Help manufacturers deploy automation comprehensively through machine learning and deep learning, and perform minimum feasibility assessment and verification for improving process yield or identification rate.

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