Do the machines design themselves? The next step in digital evolution
Joseph Kenny, Vice President, Global Customer Transformation at ServiceMax, discusses the role smart machines could play in digital evolution in the future
Digital systems are becoming more and more intelligent and human personnel are expected to perform surveillance functions in the future.
Whether it’s hardware, software, peripherals or research and development on product improvements, more and more machines are designing themselves – and it won’t be long before they fix themselves. . The rapid advance of digital transformation is changing the way manufacturers, developers and designers work.
google already uses machine learning to help design its next generation of machine learning chips. The algorithm designs are “comparable to or better than” those created by humans, Google engineers say, but can be generated much, much faster. According to the tech giant, a job that takes months for humans can be done by AI in less than six hours. Interestingly, the method Google used to achieve this was gamification, essentially giving its software the task of finding the chip configuration that produced the most productive result.
On the software side, Lancaster University UK Remarks that: “Researchers are developing artificially intelligent computer systems that can design and assemble themselves to perform better than the best man-made systems. Disrupting the traditional software development process, the newly launched research project will bring computers to the fore – allowing them to autonomously self-assemble their algorithms to complete tasks in the most efficient way – reducing running costs and energy consumption.” Again, setting parameters based on gamification concepts, programs will go through countless configuration cycles to see which provides the most desirable results based on desired outcomes.
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This level of productivity improvement will create an inescapable market dynamic. Competitors will adopt or become irrelevant. Leveraging the iterative capabilities of machine learning will be a game-changer for every equipment manufacturer, leading to faster, far less expensive, and far more accurate hardware and software development in the future. But where does that leave the human element in design, development and service?
Humans will most likely move from production to supervising and playing the role of conductor. When it comes to service, technicians of the future will most likely interface with assets, relying on asset data (currently underutilized and undermonetized) and results from AI programs to troubleshoot and determine the most effective actions to repair equipment much more quickly and efficiently than before. AI programs, communicating through IoT devices, will inform service technicians of asset status in the field; what maintenance should be carried out and when; and what is the expected time to failure, allowing for more accurately planned predictive maintenance and a more efficient maintenance program. This will not only increase uptime, but also direct technicians with the right skills to specific tasks for better planning and field utilization.
Whatever your vision, the future of equipment design, manufacturing and maintenance will be very different from what it is today. As I write this, thanks to machine learning, intelligent machines are already doing the following:
- design material much more efficiently than people can;
- create material through 3D printing;
- build better software, faster than human workers can;
- analyze failures and recommend repairs/parts without human intervention;
- plan the most efficient route for repair technicians.
The future of machine design and manufacturing seems to be firmly in the hands of machines.