Instead of “internet time” we now have “pandemic time.”

The need for advanced systems to keep society functioning, manufacturing moving, and give consumers some sense of safety is immediate. Driving innovations – whether those innovations are in health care, technology or other areas of production and manufacturing – is essential to not only offset the impact of the global pandemic but stay competitive and sustainable long after the current health crisis has subsided.

Technological advancements, especially machine learning and other powerful software tools, combined with developments in nanotechnology, monitoring, and global communication networks will accelerate a profound change that will permeate all aspects of business and manufacturing.

Manufacturing systems and processes will be forever changed, and these changes will be accelerated significantly, first out of the need to address the pandemic. But those efficiencies will continue to be accelerated as modern design, product development, and manufacturing and distribution will be indelibly impacted through modern machine learning tools.

Five Years in 18 months

Machine learning, artificial intelligence and other distinct software tools and technologies (especially manufacturing nanotechnologies) were set to indelibly affect all aspects of industry. It was generally assumed we were on a five-year curve to successfully implement the best tools and make processes more efficient, informative, and effective. Now, the pandemic has driven home the need for automation and systematic tools to keep society functioning, keep manufacturing moving, and give consumers some sense of safety and confidence. More than anything, driving innovations – whether those innovations are in health care and life science, technology or other areas of production and manufacturing – are now seen as essential to not only offset the impact of the global pandemic but stay competitive and sustainable long after the current health crisis has subsided. An isolated workforce magnifies the essential and immediate need for collaborative tools, machine learning, and applications of artificial intelligence in every aspect of industry and the work environment.

Dystopian Technology to the Rescue

Is it safe?

A visit to the Tesla factory reveals an increasingly more common environment permeating factory floors globally. Many of the robots on the factory floor operate in cages, fenced off from their human colleagues. The separation prevents the machines, in their mindless routine, from harming human workers. Now factory operators do not just need to keep human workers at a safe distance from robots; they must keep them at a safe distance from each other, too. As China reboots, fences between workers are among the measures bringing factories back to life. Under a perception of safety (whether accurate or not is yet to be determined), most Chinese factories are now operating at around 80% of capacity, with Foxconn, Apple’s manufacturer in China, operating at close to 100%. This return to normal manufacturing capacity assumes that tests for the virus and chest x-rays identify risk and enable workers to return to the job without fear of COVID-19 infection. Really? The monitoring and lack of privacy approach dystopian Orwellian measures that ultimately may be ineffective. Apple reports that it is on target to deliver all the 5g iPhones it needs for an autumn launch. So, that’s that, right? What has been accomplished in China can be replicated throughout the developed world and we will soon see the back of the pandemic nightmare. Perhaps, not so fast.

Basics Still Work – But We are Busier Innovating

Many of the measures that made China’s great reopening possible were boring but important changes to existing protocols; more hygiene measures, more separation between workers, screening, testing, and monitoring. But, ultimately, that may be the sideshow as the pandemic passes. More important changes that are fundamental and sustainable are also happening. There has also been investment in automation and remote operation that has brought forward improvements not expected for some time to come. Machine learning and other powerful software tools will enable improved manufacturing processes, better management, especially remotely, and accelerated innovation. It is reasonable to assume that what might have been expected to take five years or more, can be accomplished in less than two years now because the coronavirus has created such a sense of urgency. It is not a matter of efficiency; it is now a matter of survival.

Let’s Check That, Shall We?

Modern Chinese factories control who comes in and out with Big Brother-like detail.  Procedures identify workers, their health status, history, and many other personal metrics.  Factories use “health code” apps developed by provincial Chinese governments and run through portals inside WeChat and AliPay to determine the worker’s health status and travel history. These techniques were developed during the outbreaks of SARS and H1N1, in 2003 and in 2009, respectively. In China, the new health and safety protocols are a small incremental addition to checks and controls already in place. It allows less friction enabling manufacturers to staff factories and return to some sense of normal production. It is doubtful that these are replicable in any other manufacturing or economic setting. But there are characteristics that are transferable and transformative. Dense worker assemblies are becoming rarer, causing manufacturing processes and information exchanges about design and output to change. These software-based tools are attempting to address issues of safety as well as manufacturing efficiency. Changes required are still emerging, but one thing is clear, the working environment, even when plants are supposedly running at near full capacity, has been changed. Now, technology deployment will be accelerated to counterbalance a disruption to previously established processes.

Making It Better Sooner – with Margin for Catastrophe 

The obsessive and precise standards of modern global production make it comparatively easy for factories to adapt in such ways. However well a production process is adapted, though, things can still go sideways if less cautious suppliers must shut down and the parts the factory needs from them run out. As a result, factories around the world have been stockpiling ferociously since the outbreak. Modern just-in-time manufacturing supply chains view this as heresy. What is abundantly clear is the systems were not designed to withstand stress, shortages or unforeseen pressures. Manufacturing logic, lean inventories and just-in-time systems are probably changed forever. New product development and introduction, a vital component of all business and manufacturing require coordinating remote developers and engineers and having them work closely to tweak and tune the development. These personnel are Increasingly in foreign countries and remote locations. Bringing them together is all but impossible in a closed economy, whether it’s China or the United States closing its borders. Current best practices will be almost impossible to implement.

Don’t Waste A Good Crisis

This has created outstanding opportunities for the innovators and developers of machine learning systems and processes. This technology applied to new products and systems will lead to fundamental and accelerated changes that will permeate manufacturing and industry in general. An illustrative example is a system that uses machine learning to examine images of every single item a factory makes at every single stage of its assembly. It lets users explore the causes of any flaws, thereby increasing yields and reducing wasted time, money and materials. The amount of detail captured by the system also lets engineers from client companies inspect and manage production from halfway around the world. Under COVID-19 conditions this is an essential selling point. Its attractiveness, however, will linger long after the pandemic has passed. There is no going back once innovations such as these are deployed. Another example accelerating cutting edge technology is the use of nanotechnology coatings for electronic devices allowing the inspection of work at factories (in China or anywhere) from anywhere in the world at a level of detail previously only accessible to someone on location. Manufacturing equipment is now being connected to the internet, enabling adjustments in real-time, recording the changes, and completing the product design and development loop – all remotely. Manufacturing systems and processes will be forever changed, and these changes will be accelerated significantly, first out of the need to address the pandemic. But those efficiencies will continue to be accelerated as modern design, product development, and manufacturing and distribution will be indelibly impacted through modern machine learning tools.

Now Back to that Virus

What seemed unrelated and far-fetched – that processes driving a global pandemic and the ingenuity to enable global economic production to adjust and function again come from the same microscopic perspective. COVID-19 has a profound effect on human health and the world economy. But it is essentially a manufacturing process (albeit biological), and it is profoundly changing the global manufacturing process. The virus’s nanotechnology embodied in its proteins and RNA programming is changing the manufacturing processes of companies as they focus on a microscopic scale, gather data, adjust, and refine. The pandemic is accelerating a transformation that the world’s manufacturers were undergoing already. As products become more complex and their components more minute, there comes a point when human hands and eyes cease to be useful instruments for their assembly. An example of the vanguard that will become the norm is semiconductor manufacturing – arguably the world’s most complex manufacturing operation. Chip factories have hardly felt the impact of COVID-19. This is because making and placing nanometer-scale transistors by the billions is far too complex for human minds or human hands, and so humans do not need to gather together on a shop floor to do it. The world’s leading contract manufacturer of semiconductors, TSMC, runs its most advanced facilities from central control rooms in which humans manage machines that move the silicon being engineered around in a hyperclean environment that human workers rarely visit. In Wuhan, ground zero for the pandemic, Yangtze Memory Technologies kept operating throughout the months of lockdown. All companies everywhere are trying to learn these lessons to understand how they can withstand the most impactful unforeseeable events while maintaining their businesses. While automation may be unavoidable for the most advanced products, in other manufacturing settings, the cost of modifications and re-engineering systems Is increasing, and the results highlight less efficiency from keeping people working on the floor together. People in factories will not vanish overnight. But COVID-19 has provided a spark for more factories to approach the manufacturing perfection of chip foundries. Distancing between humans and machines is likely to long outlive the disease itself and become a fundamental part of process and manufacture design everywhere. Technological advancements, especially machine learning and other powerful software tools, combined with developments in nanotechnology, monitoring, and global communication networks will accelerate a profound change that will permeate all aspects of business and manufacturing.    

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