DAVID PARK, Vice President of Marketing, Lynceus<\/p>\n
The global semiconductor industry has experienced a robust period of growth during the past several years with demand fueled by the repercussions of the COVID-19 pandemic. Semiconductor demand was already strong due to the continuing trend of semiconductors being used in everyday devices from household appliances to cars to consumer electronics. COVID drove demand levels even higher for products that needed semiconductors. Still, the pandemic also resulted in the global semiconductor manufacturing ecosystem to slow down to a crawl for months before returning to normal operations. And the industry has been trying to catch up ever since.<\/p>\n
The semiconductor industry has historically been a cyclical business with good times and tough times, and as a result, the industry has become more guarded about overbuilding capacity. As the pandemic unfolded and semiconductor demand ramped up at an unprecedented pace, there wasn\u2019t (and still isn\u2019t) enough capacity to manufacture enough chips to meet the demand. Many foundries and IDMs (integrated device manufacturers) are building new manufacturing plants (fabs), but those will take years to come online, and all existing, mature fabs are already running 24\/7. The industry needs to look for additional ways to increase capacity in the near term. One way to achieve this goal is to apply machine learning (ML) to current manufacturing processes.<\/p>\n