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Wednesday 04 Mar 2020 , 3:05 pm

Advanced Analytics Saves Semiconductor Industry from Making Poor Decisions

Advanced analytics enables semiconductor companies to improve predictive maintenance and yield, Research & Development (R&D) and sales for market-entry strategies, enhanced pricing, sales force effectiveness, portfolio optimization, cross-selling, and other tasks.
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Many semiconductor companies have been practicing to generate and analyze data. But only a few have already applied advanced analytics to fab operations effectively. Traditional data analysis is based on the available information, whereas advanced analytics is based on what information is needed.

By applying advanced analytics, semiconductor companies are able to improve predictive maintenance and yield, Research & Development (R&D) and sales for market-entry strategies, enhanced pricing, sales force effectiveness, portfolio optimization, cross-selling, and other tasks.

Manufacturing

In chip manufacturing, the process gathers data on a large scale. Also, fabs gathers extensive in-line and end-of-line inspection, and metrology data. After combining this production data, advanced analytics is applied, that can improve important manufacturing dimensions involving yield, equipment availability, throughput, and operating costs.

With the collected information, fab is able to optimize planned maintenance schedule which not only decreases downtime but also reduces costs for parts and labor. Also, with the help of advanced data analysis, fab predicts failure of equipment or consumables accurately.

For semiconductor companies analysis has proved to identify the causes responsible for failures and has helped prevent yield loss in an early stage of production process.

Research and Development

Industry experts have already confirmed that most of the semiconductor companies don’t have efficient R&D operations. Mostly, teams overestimate the productivity and miscalculate the complexity of the project. At the initial stage, they don’t study the efforts and resources required, resulting in a failure to meet the time-to-market targets and struggle to meet their budget.

Advanced analytics makes R&D efficient by providing fact base to make decisions. This technique helps management to ensure that all resources are deployed to the relevant projects and used throughout the project life cycle. It also plays vital role to stream the R&D processes by optimizing product portfolios and helping business leaders to reduce costs.

Sales

Just like R&D, semiconductor companies also lack analytical accuracy while making investment decisions regarding pricing and sales coverage. Sales teams often ignore or lack critical pricing data that includes history of every customer and market segment. These teams neither concentrate on customer relationships nor focus on the trends related to product demands.

In this case, advanced analytics helps semiconductor companies to bring new rigor to pricing. By adopting a detailed analytics-based techniques—having statistical-analysis tools—clean up and analysis of large quantity of transaction data is possible. It also optimizes pricing and customer’s wish to pay. This results in an increase in capturing higher revenue without losing sales volumes.




Neha Mule

Neha writes articles on sectors including medicine, food, materials, and science & technology. A qualified statistician, she has the ability to observe and analyze the trends in global markets and write compelling articles that help CXOs in decision making. She is a bookworm and loves to read fiction, lifestyle, science and technology. Neha comes with 6 years of experience in content writing and editing that involves blog writing, preparation of study materials and OERs.

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