Lam Research Announces India R&D and Customer Support Expansion Plan

Lam Research Builds India Engineering Presence to Support Dholera and Future Fabs

Lam Research, whose etch and deposition equipment is present in virtually every advanced semiconductor manufacturing facility in the world, has announced a plan to establish a research and applications engineering hub in Bengaluru as a dedicated centre for India operations. The hub will employ approximately 500 engineers over a three-year hiring ramp, focusing on development of the machine learning and process control algorithms embedded in Lam's Sense.i and other intelligent process control systems, customer applications support for the Tata Dholera fab where Lam equipment is deployed, and collaborative research with Indian academic institutions including IIT Bombay and the Indian Institute of Science. The India expansion follows Applied Materials' larger commitment and ASML's engineering team doubling, reflecting a pattern of all major US and European semiconductor equipment companies deepening their India organisations in anticipation of sustained manufacturing growth.

Etch and Deposition in the Wafer Fabrication Process

Lam Research's two core product categories, plasma etch and chemical vapour deposition, are used in dozens of steps throughout the wafer manufacturing process. Plasma etch selectively removes material from wafer surfaces through chemical reactions initiated by plasma-activated gases, defining the three-dimensional structures of transistors, interconnect trenches, and contact holes. Chemical vapour deposition deposits thin film layers of materials including silicon dioxide, silicon nitride, tungsten, and high-k dielectrics onto the wafer surface to form gate insulators, spacers, and interlayer dielectrics. At 28nm and nearby nodes, the etch and deposition steps account for a large share of the total process flow steps, and Lam systems operate multiple shifts per day throughout the fab's production schedule. The quality, uniformity, and repeatability of Lam's etch and deposition processes directly determine the yield and performance distribution of the chips produced at the Dholera facility.

AI-Driven Process Control R&D Focus

Lam's Bengaluru R&D hub will focus specifically on the development of machine learning components for its intelligent process control and predictive maintenance systems. These systems use sensor data from within the process chamber, combined with historical yield and chamber performance data, to predict maintenance needs, detect process drift before it affects yield, and automatically adjust process parameters in response to subtle changes in chamber conditions. Developing these algorithms requires both semiconductor process domain expertise and machine learning engineering capability, a combination that Lam is seeking to build in India by hiring data scientists and ML engineers with strong fundamentals and training them in semiconductor manufacturing process physics. The Bengaluru team will collaborate with Lam's US and South Korean process engineering teams to validate algorithmic improvements against real process data before deployment to customer systems worldwide.

Academic Research and Ecosystem Building

The joint research programmes with IIT Bombay and IISc will focus on atomic-layer etching and atomic-layer deposition processes, which are the emerging precision process techniques required as semiconductor feature sizes continue to shrink below the 28nm nodes of India's initial commercial fabs. By investing in research on these more advanced processes now, Lam and its academic partners are building the scientific foundation that will be needed when India's semiconductor programme progresses to more advanced nodes in the second half of the decade. Lam has indicated that it intends to make research findings from these programmes available to the Indian semiconductor community through publication and workshop presentations, contributing to the broader ecosystem knowledge base rather than retaining all research value exclusively within Lam's commercial IP portfolio.