LET AI DO
Unlock Human Potential
Repetitive tasks are estimated to cost businesses as much as 19 working days per year per employee. 90% talented engineers get stuck in mundane and repetitive tasks. Disengagement of talent costs the global economy $8.9 trillion each year.
Reduce Human Errors
80% of manufacturing defects are due to human error, found by a study published in the International Journal of Engineering Research and Applications. 23% of the unplanned downtime in the manufacturing sector is caused by human errors. Some studies suggest that human error is a causal factor in a significant portion of accidents, with estimates ranging from 70-90%.
Prevent Work Injuries
Every year, over a million U.S. workers are injured on the job. In 2022 alone, employers reported 5,486 fatal occupational injuries and 1,483,400 nonfatal injuries and illnesses that caused an employee to miss at least a day of work. These incidents resulted in roughly 75 million lost workdays, imposing an estimated total cost of $167 billion in 2022.
Save Operating Costs
Manufacturing errors and unplanned downtime are potentially very costly, with one report finding that manufacturers lost $1 trillion in manufacturing failures accounting for 11% of their yearly turnover. Equipment failure accounts for 42% of unplanned downtime costs. It is estimated that unplanned downtime costs manufacturers up to $50 billion per year. Moreover, the facility staff is exposed to greater safety risks, which can translate to even greater financial losses.
Accelerate Technology R&D
To deliver quick new product development, R&D engineers need to design vast amount of experiments to establish statistical correlations and conduct the next experiment. R&D teams are also under constant pressure handling massive high-dimensional data, variables and parameters through a large number of assumptions and unknown scenarios. All theses key activities need to be accelerated to deliver a fast R&D cycle.
Gain High Production Yield
In semiconductor industry, stochastic defects can degrade the production yield drastically and cost billions. It's required to focus more on sophisticated metrology, process optimization, equipment reliability, and material quality to understand the root cause of the defects to gain high yield.
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