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Manufacturing Post-Covid

SOURCE:PowerArena

When Covid-19 hit us in 2020, the manufacturing industry faced a series of challenges, such as supply chain disruption, labor shortage, high demand fluctuation, and travel restrictions. Companies adopted digital transformation technologies to be agile and fight against rapid changes happening across the globe. In many ways, Covid-19 accelerated the developments happening at Industry 4.0, and brought long-term growth to the companies.

Beyond the four walls: remote working and monitoring

Companies used to monitor the production processes on-site. However, due to travel restrictions and distancing requirements, they moved towards remote monitoring. Using sensors or PLC(programmable logic controller), factories can collect manufacturing data automatically. This helps managers and industrial engineering teams to improve production efficiency even when they are not on the shop floor. However, attaching sensors to operators and every single component of a labor-intensive assembly lins is simply impractical.

To solve this problem, PowerArena uses cameras powered by AI deep learning and computer vision technologies to tracks operators’ performance and effeciency. Delivering 24/7 real-time production reports, PowerArena spots line bottlenecks and helps factory managers to make line improvement decisions anytime and anywhere.

Respond to uncertainty:  AI-driven decision making and production optimization

A Harris Poll survey revealed that the manufacturing industry accelerated AI adoption in the face of COVID. 64% of manufacturers adopted AI to assist day-to-day operations. AI application in the manufacturing industry is moving from pilot purgatory into a new golden age.

AI is applied in various fields in the manufacturing industry, including demand forecasting, quality inspection, and supply chain management. Take demand forecasting as an example. Using AI machine learning can help make decisions more efficient. Analyzing not only internal sales and supply data but also external factors such as economic index and upstream/downstream changes, AI can better predict demand, thereby helping production and logistic planning.

PowerArena also applies AI to help on production decision making by tracking operator’s motions and alerting SOP mistakes immediately. Also, new operators can pick up skills through past video records. Not only does our technology avoid human error, but it also generates real-time production reports. Speeding up process improvement, PowerArena helps the production line to be agile and respond quickly to changes in the pandemic.

Obstacles and challenges of adopting new technologies

When adopting new technologies in the pandemic, companies may encounter a variety of problems. For example, some companies find the move of data to the cloud for remote work is a large risk in terms of information security. Alternatively, there may be issues of procuring technical talent, as it is difficult to cultivate an experienced AI team in a short time. In addition there may be issues of financial liquidity as companies may be unable to pay for technologies all at once. SaaS(Software as a Service) stands out when it comes to resolving these issues, because SaaS allows for outsourcing of skilled talent and financially viable periodic payments.

At the end of the day, companies undergo digital transformation to survive. According to a survey by Mc. Kinsey, companies who have successfully scaled industry 4.0 technologies found themselves better positioned for the pandemic. The survey attributed this success to the high adaptability of digital tools. Furthermore, the pandemic has forced companies to immediately examine their digital tools and IT infrastructures. As for companies that have not engaged in digital transformation, they find themselves with limited resilience. This global crisis has alerted us to drive for digital transformation and bring about industry 4.0.

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