Semiconductor applications are increasing worldwide, and they are the go-to material for many technologies, such as integrated chips, diodes, transistors, etc. Without these components, devices we use every day, such as smartphones, laptops, game consoles, microwaves, refrigerators, digital cameras, televisions, washing machines, LED bulbs, etc., cannot function.
As technology advances, so will semiconductor applications. The first generation of semiconductor materials was bulky. Advanced fabrication methods can now produce thin semiconductor films that can be used to build these technologies.
In this article, we will show how industry 4.0 technology solutions like the digital twin can play an important role in the semiconductor industry, especially in manufacturing processes like chemical vapor deposition (CVD).
In the next section, we discuss the scope of industry 4.0 technology solutions in the semiconductor industry, what digital twin technology is, and some of its applications in the semiconductor industry. Furthermore, you can also learn about implementing digital twin for predictive maintenance.
Table of Contents
Microprocessors are integral components of everyday objects – home appliances, laptops, and even the cars we drive. The US accounts for 85% of the chip design market but only 12% of the semiconductor manufacturing market. In Sep 2022, the US Dept. of Commerce released its plan to allocate $50 Bn from the CHIPS Act to support chip R&D in the US and subsidize chip plant construction. Intel Corp. plans to spend $20 Bn to build the largest silicon manufacturing site in the world in Ohio and make it operational by 2025. Similarly, Samsung plans to build a $17 Bn chip plant in Texas and make it functional by 2024.
Current investments in artificial intelligence (AI) and machine learning (ML) aim to boost efficiencies in the semiconductor industry to unprecedented levels. Technologies such as digital twins can vastly speed up the chip design and manufacturing process and help strike a balance between demand and supply.
Digital twin technology allows chip manufacturers to improve performance without disrupting full-capacity operations. Industry leaders like Applied Materials, Bosch, and LAM Research are already using machine learning models that are more accurate and exponentially faster than conventional simulations.
AI is disrupting the semiconductor manufacturing industry by driving significant improvements in throughput, quality, and yield. Digital twin modeling can streamline the chip fabrication design and production process, reducing the dependence on physical prototyping.
A digital twin is a digital simulation of a real-world system, process, or product. It is a digital representation or a virtual model of a physical object. It comprises data and possesses the ability to monitor the object.
Combining the physical and the virtual worlds allows system monitoring and data analysis to mitigate problems before they occur. It also helps with planning by using simulations, developing new opportunities, and preventing downtime.
Simply put, a digital twin is an end-to-end virtual manifestation of something that exists in the real world. Using sensors to collect data in real-time from a physical item, the digital twin acts as a bridge between the real and the digital worlds.
Digital twin technology can help develop semiconductors even before the manufacturing stage. It can help designers build the best product by simulating tedious roadblocks that can disrupt production schedules in advance.
Semiconductor systems are in high demand and short in supply. Streamlining its design process and making it more productive can thus prove invaluable. Following are some of the ways digital twins can help:
While digital twins cannot eliminate the need for physical prototypes, they can minimize them, accelerating decision-making and cutting costs. Designers can discuss virtual options with their teammates from remote locations.
Businesses can also use digital twins to make presentations to clients without face-to-face meetings and get immediate feedback. Customers get an accurate representation of the semiconductor system under development, enhancing experience and satisfaction.
In the connected vehicle industry, digital twin helps simulate and verify system-on-chip (SoC) and subsystem designs, assisting designers in understanding what’s working and assessing room for improvement. It can show a chip’s estimated power, generating insights on performance metrics before production.
Mini wave soldering, an automated soldering option, is an easily reproducible method and produces high-quality solder joints. The earliest design phases do not involve soldering procedure decisions. A digital twin can help plan and meet production deadlines without encountering slowdowns.
Designers can use digital twins to examine a semiconductor’s lifecycle from the early stages without waiting for a manufacturing plant to begin production. This delivers insights that can improve all production stages of a semiconductor system.
One of Bosch’s semiconductor factories in Germany uses a digital twin to help employees deal with building construction and process updates. The virtual replica of the factory comprises around 500,000 objects, aiding future production plans. In another instance, the US Dept. of Defense (DoD) uses a digital twin to validate the integrity of individual devices or an assembly of chips before putting them into weapons. DoD’s goal is to secure the nation’s microelectronics supply chain for critical infrastructure.
If designers use the digital twin to collaborate with manufacturers more frequently, it could substantially increase production levels. Simultaneously, all stakeholders would be on the same page regarding component development.
When everyone has access to the same accurate and real-time information, it eliminates issues that can create communication gaps and slow production.
In addition to the aforementioned use cases, digital twins can help transform semiconductor manufacturing processes, such as chemical vapor deposition (CVD).
In the next section, we explore this process, its role in semiconductor manufacturing, and how digital twin technology can help automate it.
Read More: 5 Ways to Improve Production Performance with Digital Twins
Chemical vapor deposition (CVD) is often referred to as a bottom-up nanofabrication technique. This is because it builds a material from scratch, depositing atom by atom on a surface, usually a metal foil. CVD is quicker than most other nanofabrication techniques but consumes a lot of energy.
The CVD process has different variations, depending on how the reactants are dissociated into a gas. However, all forms of CVD are performed in a vacuum.
The process begins by introducing the reactants into the reactor. The reactants are vaporized into gas using high temperatures, plasma, or other methods. An inert carrier gas now feeds the atoms in the gas into the reaction chamber.
Here, the atoms are deposited onto the substrate in the reaction chamber. The vaporized particles react and decompose on the surface of the substrate. This creates a chemically bonded thin film on top of the substrate.
The reaction also produces by-products desorbed from the substrate surface and removed from the reactor.
Almost all semiconductor manufacturing processes use CVD. Without this technology, most modern electronics would not exist. While there are many different methods of CVD, the following two procedures occur in nearly all CVD processes:
Manufacturers must regulate the temperature and pressure to ensure that the decomposition and combination reactions occur correctly. The change in energy allows the elemental bonds to
break and reform, similar to how water evaporates or condenses with changes in temperature and pressure.
CVD creates thin coatings of polymer chains on wafer surfaces. One of its most common applications in semiconductor manufacturing is creating integrated circuits. In solar cell production, manufacturers use CVD to grow silicon on monocrystalline silicon substrates, forming a 15–50-micron thick silicon layer.
Manufacturers also use CVD to grow 6H- and 3C- silicon carbide (SiC) on silicon wafer substrates. There are many ways to produce silicon carbide, and some methods also introduce p-type and n-type dopants into the monocrystalline SiC films.
CVD has made developing impurity-free and thick SiC crystals for electronics manufacturing much more cost-effective. With CVD, the semiconductor industry would be more productive.
This technology helps create incredibly small but powerful devices used in almost all industries.
While underway, the CVD process can face any one or more of the following challenges:
Drop in pressure
Imbalances in temperature can potentially lead to condensation, which, in turn, may result in
Flow fluctuations can
Digital twin technology can help with the real-time CVD process monitoring of the following operational KPIs:
During each of the following stages of the CVD process, a digital twin can help monitor the following data points in real-time:
| Process | Data Points to be Monitored |
| Chemical vapor reactants are fed into the reactor | Temperature, pressure, reactant flow rate |
| Gas species are dissociated by heat | Reaction time, spin speed |
| Species adsorbed on the substrate surface | Growth diagnostics |
| A chemical reaction involving absorbed species forms a solid film | Developed resist thickness & uniformity, development time |
| By-products removed from the reactor | Spray pressure |
Semiconductor manufacturers using the CVD process can enjoy the following benefits from digital twin:
Harnessing the data currently available, digital twin technology can help semiconductor manufacturers determine if their production targets are optimum. It can also help them see the consequences of a slight increase or decrease in production in real-time.
By replicating a physical system in the cloud, manufacturers can glean invaluable insights and increase their capacity significantly without incurring the risks associated with conventional methods.
Unfortunately, while some semiconductor manufacturers are creating development models using digital twins, the technology does not enjoy widespread adoption across the industry.
Thankfully, with both private and public operators realizing the potential of this technology, the digital twin promises to be a game-changer for consumers, manufacturers, and chipmakers.
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