Introduction
Over the last four years, President Biden’s CHIPS Act has been a subject of significant discourse in the semiconductor manufacturing industry. While most of us are familiar with its intent—to tackle supply chain vulnerabilities to bolster the production of American-made semiconductors and to revitalize America’s position as the leading semiconductor producer worldwide—a recent report indicates that many of the program's recipients are struggling to meet the goals laid out for it and is reportedly “haemorrhaging cash.” So, this begs the question: Where is it all going wrong? What will happen if the goals are not met, and how can AI optimization help these companies reach their quotas?
What are the Challenges?
The CHIPS Act's goals are not without their challenges. The expansion of semiconductor production is a costly endeavour, with numerous hurdles involved, including:
- Cost overruns
- Supply chain delays
- Shortage of talent
Cost Overruns
With costs currently ranging from $15 billion to $20 billion, constructing a semiconductor fabrication plant can be extremely costly. Overspending can be an easy trap to fall into. It has been reported that some projects cost up to 50% more than initially expected. Furthermore, a study by the Semiconductor Industry Association reported that the average cost of building a new fab has increased by over 100% in the last decade. In modern Fabs it takes over 1,200 multimillion-dollar tools to manufacture the chips, So now more than ever, overspending and underperforming are no longer an option.
Supply Chain Delays
Ever since the COVID-19 pandemic, supply chain delays have been a common occurrence. Semiconductor manufacturers are buying more materials than they need to compensate for inconsistent delivery times. The result of all this over-purchasing? A huge surplus of materials that will never get used.
Shortage of talent
As semiconductor fabs get more complex, so does the data management process holding it all together. From spreadsheet errors to notes on scraps of paper, many of these processes are stuck in the 90s. As many of the engineers from the past retire, they take valuable information with them. This information is usually not stored in a database. This example shows the clear limitations of manual workflows, which in turn cause companies to bleed millions every year.
All these factors accumulate throughout the fab construction process, resulting in overspending and straining resources and timelines. With problems mounting, shadows of doubt are being cast over the feasibility of achieving the targets set by the Biden-Harris administration. This has led many to wonder if the ambitious goals can be reached without further innovation.
What Are the Consequences of Not Meeting Goals?
While the benefits of the CHIPS Act are significant, failing to meet the quotas could lead to serious consequences. One potential consequence is the loss of government funding and subsidies, as the CHIPS Act provides lucrative financial incentives to companies that achieve key milestones in:
- Production capacity
- Technological advancement
- Job creation
If these quotas aren't met, many companies could forfeit tax breaks, grants, and financial investments.
In addition to the seizing of financial investments, the Biden-Harris administration placed a "Clawback Clause" into the act. This means that a large portion of those funds must be returned if quotas are not achieved. Inevitably, this will lead to intense financial strain on companies that invested heavily in the construction of new semiconductor fabs.
Though the biggest losers of a failed CHIPS Act stand to be the companies receiving financial investment, the government isn't void of consequences. As we know, the goal of the CHIPS Act is to revitalize domestic U.S. semiconductor production. The U.S. would be at risk of prolonging its dependency on foreign production. In addition to straining the semiconductor supply chain, it would also exacerbate U.S. foreign security concerns.
How Can AI Optimization Help?
We understand the problems and the consequences, so what are the solutions? One possible pathway to achieving these targets is AI optimization, which has the potential to revolutionize how companies approach the complex fab construction process. By reducing errors and increasing efficiency, AI could be the final step needed to reach the goals of the CHIPS Act.
Faster Design Outputs
Traditionally, the process of assessing the requirements for an advanced manufacturing facility can take as long as 12 weeks, which further strains finances and extends the margin for error. Additionally, critical information about the quantity and type of materials and equipment is generally not available until halfway through this process. AI optimization can deliver critical equipment outputs in less than a week, saving time, money, and resources.
Reduce Capital and Engineering Costs
Modern design optimization algorithms can calculate the best design for a sub-facility with minimal error. This ensures resources and equipment are used as efficiently as possible. By reducing unnecessary components, such as excess cables, companies can significantly cut capital costs across the board. From an engineering perspective, automating the advanced manufacturing facility design process enables skilled engineering talent to focus on more high-level tasks. This modern solution minimizes the need to assess and define facility requirements.
Schedule and Project Delivery Tracking
As we know, the complexity of designing and constructing a semiconductor manufacturing facility introduces many unwanted factors into play. As a result, creating an accurate and reliable schedule is notoriously difficult. AI optimization tools address some of these challenges by creating an integrated tool/facility plan for each piece of equipment, enabling engineers on the ground to focus on delivering the minimum scope required to start the manufacturing process.
Conclusion
Meeting the goals of the CHIPS Act is essential for semiconductor companies to demonstrate they are up for the challenge. However, success will remain out of reach unless these companies fully embrace innovation and automation.
Challenges such as cost overruns, poor data management, and supply chain strains jeopardize the success of every fab construction project. AI optimization offers a clear and viable solution to these costly issues, delivering faster design outputs, reduced engineering and capital costs, and improved project scheduling and tracking.
Modern problems require modern solutions, and companies must adopt these innovations to have any chance of meeting the CHIPS Act's goals. Failure to do so would result in serious consequences.
