MILPITAS, Calif. — July 23, 2020 — North America-based manufacturers of semiconductor equipment posted $2.32 billion in billings worldwide in June 2020 (three-month average basis), according to the June Equipment Market Data Subscription (EMDS) Billings Report published today by SEMI . The billings figure is 1.1 percent lower than the final May 2020 level of $2.34 billion, and is 14.4 percent higher than the June 2019 billings level of $2.03 billion.

“June billings of North America-based semiconductor equipment manufacturers continue to show signs of resilience as the world copes with new realities posed by COVID-19,” said Ajit Manocha, SEMI president and CEO. “The year-over-year billings increase points to strong fundamentals that are enabling the semiconductor industry to effectively navigate these challenging times.”

The SEMI Billings report uses three-month moving averages of worldwide billings for North American-based semiconductor equipment manufacturers. Billings figures are in millions of U.S. dollars. 

Source: SEMI ( www.semi.org ), July 2020

SEMI publishes a monthly North American Billings report and issues the Worldwide Semiconductor Equipment Market Statistics (WWSEMS) report in collaboration with the Semiconductor Equipment Association of Japan (SEAJ). The WWSEMS report currently reports billings by 24 equipment segments and by seven end market regions. SEMI also has a long history of tracking semiconductor industry fab investments in detail on a company-by-company and fab-by-fab basis in its World Fab Forecast and SEMI FabView databases . These powerful tools provide access to spending forecasts, capacity ramp, technology transitions, and other information for over 1,000 fabs worldwide. For an overview of available SEMI market data, please visit www.semi.org/en/MarketInfo .

The data contained in this release were compiled by David Powell, Inc., an independent financial services firm, without audit, from data submitted directly by the participants. SEMI and David Powell, Inc. assume no responsibility for the accuracy of the underlying data.