Liola has developed a breakthrough technology and go-to-market product that enables semiconductor manufacturing plants (FABs) to optimize their production plans and achieve dramatically increased plant throughput.
Liola’s Exponential product is based on a breakthrough in optimization algorithms that combine a new mathematical approach with deep domain knowledge and specific characteristics of complex manufacturing environments such as semiconductor production lines. The algorithms take into account the “re-entrant” nature of the semiconductor manufacturing process and the inherent competition for resources to deliver true global FAB optimization without attempting to run through all possible paths.
Leveraging this unique technology with the Liola team’s 100 years of combined experience in the semiconductor industry, Liola’s product delivers an additional breakthrough in the form of “optimization on demand.” This groundbreaking architecture enables, for the first time, optimization of FABs on a daily basis to deal with changing conditions in near real time.
Trendlines’ director: Yosi Hazan
A typical FAB costs about $2 billion and $4 billion, uses hundreds of extremely expensive machines, and employs 2,500 people to manufacture tens or hundreds of different products. There may be up to 100,000 units in the production line at any single point in time. FAB revenues of $750 million per year mean that even a few percentage points of improvement in production will result in increased revenues of tens of millions of dollars. With such a huge capital investment on one hand, and the financial opportunity on the other hand, semiconductor manufacturers are always looking for ways to optimize their FABs to increase throughput.
With about 4,000 FABs in operation worldwide, even a conservative $250,000 annual investment in optimization per FAB, would represent a total available market of over $1 billion. However, the extreme complexity of these production lines has presented challenges to optimization solutions for over a decade.