Smart Manufacturing

Leveraging predictive modeling and other efficiency-enhancing innovations, Digital Twins promise to optimize semiconductor design, manufacturing processes and equipment maintenance while improving overall operational efficiency.

Despite its great promise to help streamline semiconductor manufacturing, AI has largely failed to deliver on its potential despite significant investments in data infrastructure and talent. Understanding the reasons behind this failure is a critical step towards unlocking AI and associated ROI.

AI can potentially deliver the semiconductor industry operational gains of $85-$95 billion annually in earnings before interest by 2025. In reality, roughly 90% of this figure remains theoretical.

Massive capacity expansions will necessarily integrate advanced Industry 4.0 standards, practices and technology to achieve the highest possible operational efficiency and performance at the start of volume production.

A steel mill and a 200mm semiconductor fab face a similar challenge: How to improve output, whether in Tons Per Year (TPY) or Wafer Starts Per Month (WSPM), while saddled with a capital equipment footprint that cannot be readily replaced or easily expanded.

In this article, several experts weigh in on considerations for developing the smart manufacturing workforce that will help to alleviate the U.S. semiconductor manufacturing talent shortage, even as multiple, data-intensive $1 billion to $10 billion fabrication facilities come online.

From the need for more tech talent to fuel digital transformation across all industries to the great resignation and great retirement of workers en masse, the demand for tech talent continues unabated.

During their session Creating a Data Ecosystem to Enable End-to-End Advanced Predictive Manufacturing, Laura Matz of EMD & Raj Narasimhan of Micron provided a case study of their uncommon partnership in creating a shared data ecosystem to prove the advantages of advanced predictive manufacturing.

Semiconductor device manufacturers are focusing on new sensing technologies that can increase wafer throughput, reduce downtime, boost yields and drive other production efficiencies by collecting data that provides insights not previously identified.

Demand for hi-tech manufactured goods is at an all-time high and is expected to grow significantly in our new digital age, COVID-19 economy. This is especially true for semiconductor chips. Chip manufacturers have been working to meet this demand by building new factories and by optimizing...