How Semiconductors Shape the Next Generation of Robots

The 21st-century aspirations of flying vehicles and domestic androids have yet to materialize. But because to semiconductor developments, factory floors now show people the future.

FREMONT, CA: Robots have been used in process automation for decades and are ubiquitous in manufacturing. Then there is the issue of safety.

With the advent of collaborative robots—sometimes known as cobots—this connection is changing.

Cobots, powered by machine learning and powerful sensor technology, operate alongside humans to complete hazardous, repetitive, and complicated activities. They are reshaping the production line and may eventually change the industrial design as businesses learn how to combine human and cobot labor.

Soon, cobots will be able to work alongside people on the production floor. Some ways in which semiconductors are altering the next generation of robots are as follows:

Small size promotes autonomy: While robots used to assemble automobiles and other huge products are large and imposing, cobots entering the manufacturing environment today are smaller, lighter, more portable, and can be modified to accomplish specialized jobs. These smaller cobots are enabled by advancements in form factor, allowing more electronics into ever-smaller devices without losing power efficiency or precision.

Along with reducing the size of cobots, electronics enable the incorporation of additional processing capabilities and intelligence, allowing the machines to operate autonomously rather than under the control of a cloud or centralized processing unit.

Eventually, smaller cobots will enable manufacturers to meet specialized requests for customized items without significantly altering their manufacturing processes. Manufacturers will reconfigure cobots on a need-to-know basis to control inventory and expenses while maintaining operational efficiency.

Efficiency is enhanced through machine learning: Machine learning advancements also contribute to the expanding deployment of cobots, as they learn from people and one another. Cobots can learn jobs by seeing humans perform them, just like any human learner would. This can save time that would have been spent programming earlier. Cobots can then "teach" other cobots by distributing their newly acquired knowledge via local connections or straight to the cloud. This can save time that would have been spent programming earlier.

When deployed throughout the supply chain in inventory management, warehousing, and fulfillment, cobots will eventually manage their operations and production schedules in response to supply and demand variations.

Effective energy management increases flexibility: Cobot deployment may present distinct power supply and administration issues. Factories must ensure that their power management systems are as efficient as possible in current draw and thermal output.

Electronics generate digital "noise" that can cause magnetic fields to interfere. Managing electromagnetic interference in manufacturing is a design challenge. Other problems that semiconductor suppliers are collaborating with clients include developing flexible load management solutions and creating systems that can be implemented in existing power footprints.