The demand for semiconductor chips increased manifold owing to the ever-increasing applications of smartphones, tabs, laptops, desktops in industries such as healthcare for telehealth services; in the education sector for online teaching and instruction; and as resources/employees across the industries started working remotely. At the same time, the automotive industry is getting more and more advanced and is using hundreds of sensors to offer all the creature comforts to its consumers as they move towards building the 'connected car' experience.
In the manufacturing sector, too, the pandemic has driven home the values and virtues of setting up connected factories that enable contactless manufacturing and uninterrupted operations in the face of a crisis. All these trends in semiconductor industry show that the demand will steadily rise for semiconductor chips in the coming future. However, considering the most significant movement of the semiconductor industry, which is delivering 2X computing power while reducing the costs by half every few years, the key priority for the industry lies in finding avenues of innovation to have in line with this trend.
It is thus imperative for the industry to invest more and more in R&D to drive innovation while optimizing costs by leveraging technology like Cloud Computing.
Semiconduction Industry: Business Needs
If one accounts for the key constituents of the semiconductor industry – skilled resources, high competition, complex automation tools, data & IP, varied semiconductor industry supply chain, and low shelf-life of the designed chips; it is apparent that these constituents are highly expensive difficult to manage. Given the nature of the investments and expertise required in the industry, there are very few players in this industry. The race for excellence is fierce, and a considerable effort and investment is dedicated to driving R&D to identify areas and avenues for innovation.
Faster time to market through the acceleration of the design cycles, performance enhancements of the chips through upgrades and updates, IP protection through foolproof and flawless security systems are the top three business priorities of this industry. The chip companies invest most of their time, energy, and capital in fulfilling these priorities. However, operational priorities are equally important, such as driving efficiencies in the manufacturing process and throughput through data analytics, optimizing the operations, processes, and costs, and driving productivity through collaboration.
Visit our High-Tech page
Cloud computing provides a reliable and seamless infrastructure to address both the business and operational priorities of the semiconductor industry.
Reasons to Embrace Cloud in Semiconductor Industry
#1 Faster Time to Market and Quicker Design & Development
If we consider the ever-increasing demand from the consumers for products with higher compute powers and processing abilities, the product lifecycles have considerably reduced, and the need for semiconductor manufacturing companies to ensure faster time-to-market is growing by the day.
To this end, applying cloud computing in semiconductor industry offers scalable storage, big data analytics capabilities, and enhanced productivity with collaboration tools for reviews and feedback that enable quick product launches.
Cloud also provides a flexible, scalable, elastic, and secure infrastructure for chip designing by providing on-demand compute for EDA tools. It enables the semiconductor manufacturers to set up and access high-performance computing (HPC) power with virtual machines (VM) images, enabling quicker design and development cycles.
#2 Improvement in Foundry Operations and Yield
Cloud offers a single source of truth/data lake or repository that enables storing, processing, analyzing, and inferring the foundry's generated data. Manufacturers use these data insights for predictive performance & analytics and management of resources & semiconductor supply chain, thereby improving the production uptime and yield. It also allows for specific AI and ML use cases for fault detection in the production line using imaging techniques and smart analytics tools.
#3 Smarter Manufacturing Powered by Democratization of Data & Analytics