Leveraging Advanced Data Analytics in enhancing productivity in the semiconductor industry

Enhanced competitiveness in the Semiconductor Industry

Semiconductors are in nearly every electronic gadget and home appliances. Semiconductor manufacturing is a complex practice involving hundreds of manufacturing phases, and is one of the most challenging businesses.

The advancement in disruptive technologies such as artificial intelligence, the internet of things (IoT), 5G, and industry 4.0 automation has created a massive demand for advanced semiconductors.

Coupled with this, huge consolidations in the semiconductor industry, unparalleled R&D spending, as well as the race for innovation among the industry’s top notched players led to an increase in productivity in the semiconductor industry.

Advanced Data Analytics – A tool for recognizing systemic factors

Employing data analytics enables semiconductors in identifying related factors such as malfunctioning tools/recipes that erode productivity and efficiency and connect parameters in real time to ensure yield enhancements and failure analysis.

The effectiveness of Advanced Data Analytics in accelerating productivity in the semiconductor industry

New techniques can go a long way in enabling companies take wise decisions by using correct, reliable, and scientific information to evaluate risks, optimize processes, and predict failure.

When used successfully, advanced analytics not only enable enhance operations and margins but also spike growth. Yet many enterprises, including several semiconductor players, have been lagging behind in embracing these techniques.

As per the revelation made by the International Data Corporation, the global pool of data is in excess of 2.8 zettabytes and expanding. However, companies use merely 0.5 percent of that ocean of information to take decisions.

Enterprises, usually, consumer-facing ones, do gather and analyze a wide range of data achieve scores of benefits. For instance, banks, insurance companies, and retailers have benefitted from insights from advanced data analytics to build continuous competitive benefits, including stronger customer relationships and enhanced operational efficiency.

Semiconductor companies have been leaders in creating and analyzing data. But a less number of them successfully applied advanced analytics to semiconductor operations, where they could enhance predictive maintenance and yield, or to R&D and sales, for improved pricing, market-entry strategies, sales-force capability, cross-selling, portfolio expansion, and other tasks.

Advanced Data Analytics’ specific capabilities in detail:

Putting Advanced Analytics to use in manufacturing

Advanced data analytics enhances significant manufacturing dimensions, covering yield, equipment availability, throughput, and operating costs. All information gathered throughout the semiconductor industry—including products, metrics for processes, and machine state will rapidly surpass terabytes of data. The semiconductor companies collect extensive in-line, end-of-line inspection, and metrology data.

A fab performs a multivariate analysis to improve condition-based monitoring—a maintenance tactic that encompasses assessing specific indicators to find out if equipment performance is coming down. Among other advantages, the analysis would enable the fab to foresee more precisely when consumables or parts will fail.

For example, fabs could bond link equipment and process-level data to inspection and metrology data to give perfect predictions about yield degradation.

Advanced Analytics in R&D

Advanced analytics turns R&D into more efficient by substituting instinct and guesswork with a fact base for decision making, thus making sure that resources are available to the right projects and used optimally throughout the project life cycle. Semiconductor companies, for instance, enhance R&D effectiveness and productivity by statically modeling the complexity of projects (like the impact of adding a specific type of resource) and working out the best staffing levels.

Crucial Factors For increasing the value of the Semiconductor Industry

Through assimilating agile development and Delivery and Acceptance (D&A) into R&D processes, semiconductor companies can place themselves for a competitive benefit through:


Time to market: Reduced design, endless integration, and validation cycles enabled by Agile and D&A.


Enhanced ROI on R&D investing: Increased utilization of R&D resources and significance of the most relevant programs.


Enhanced productivity: D&A empowering quicker cycles of learning generated from the design databases across different teams and locations.


Reduced execution risk: Utilization of common platforms result in better integration of the design databases and reduced risks of errors or delays when adding design blocks from different components.


Advanced data analytics is perceived to be the ultimate key to enhancing the overall productivity of semiconductor industry. However, the fact remains that advanced data analytics itself cannot produce miracles. For an enhanced and consistent performance, it is important that tools like IoT, big data, and advanced data analytics can be used together in a dedicated manner rather than depending on it to get the anticipated outcome.

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