Smart manufacturing in the semiconductor industry is one of the latest concepts that has immense potential to revolutionize the manufacture of semiconductors. While it is yet to be widely adopted by companies, it holds the key to improving efficiency, delivering higher yields, and paving the way for semiconductor innovation.
We’ll discuss what smart manufacturing is, how concepts like smart factories will change the way semiconductor devices are manufactured, and how the industry as well as consumers can benefit from it.
What Is Smart Manufacturing?
The concept of smart manufacturing is not limited to the semiconductor industry but is a change that other industries in manufacturing are all attempting to embrace. Manufacturing always received new life whenever significant technological leaps were made throughout history. We saw this during the original industrial revolution with the introduction of steam-powered machines. The second one was with electricity, the telegraph, and the modern production line. The third industrial revolution which was known as the ‘Digital Revolution’ introduced computer processing into the mix.
We are now at the fourth industrial revolution, or ‘Industry 4.0’ where technologies like smart sensors connected through Internet-of-Things (IoT), artificial intelligence-powered big data analytics, human-machine interfaces, autonomous robotics, and simulation systems play key roles in transforming traditional manufacturing systems. Under the Industry 4.0 framework, smart manufacturing aims to use these technologies to monitor the products in real-time decisions to carry out these improvements, autonomously if possible.
The ‘Smart Fab’ or smart factory is the result of applying these smart manufacturing principles to the semiconductor manufacturing industry. It is an approach where all current systems like the Manufacturing Execution System (MES), the Facility Monitoring and Control System (FMCS), and the Enterprise Resource Planning (ERP) system, would be integrated together.
Smart manufacturing is expected to improve the efficiency of manufacturing processes and make them more transparent, responsive, safer, and more reliable. Manufacturing companies in the semiconductor industry also hope to improve their yield, and ultimately produce better semiconductor devices through smart manufacturing.
Why The Semiconductor Manufacturing Industry Should Adopt Smart Manufacturing Systems
There are plenty of new growth opportunities for semiconductor companies engaged in manufacturing. Interestingly, many of the technologies that drive smart manufacturing like the Internet of Things, artificial intelligence, and cloud computing are growth areas themselves. Semiconductors for smartphones drive the most revenue, and although growth is slowing due to high penetration, it is expected to get a boost when 5G technology becomes more widely adopted.
Due to the growing usage of artificial intelligence and deep learning applications, semiconductors used in memory, storage, and logic chips are in high demand. This segment of the market is growing five times faster than the rest currently. When looking at the sheer volume, the fastest growing are the smart sensors used in IoT. Finally, the automotive industry is expected to drive growth when self-driving cars become more popular.
With growth expected to increase, the semiconductor industry needs to adopt smart manufacturing methods to maintain a steady supply for a variety of reasons.
Need For Device Level Track And Trace
Industries like automotive, medical, defense, and aerospace require integrated circuits to perform within a narrow range of parameters for obvious reasons. These buyers require tracing of the genealogy for every integrated circuit from manufacturing to system integration. This type of device-level tracking presents massive amounts of data that the current generation of Manufacturing Execution Systems (MES) are simply not equipped to handle.
Growing Indirect Labor Costs
About 20% of costs for semiconductor manufacturers are due to indirect labor costs. This could be due to capacity planners creating unrealistic plans because they do not have instant access to the latest data concerning new raw materials, process improvements, or new products. Some inefficiencies are created when more experienced technicians leave a company.
Engineers may currently be making their decisions based on data pulled from multiple disconnected systems. Not only is it difficult to pull data from older systems, but it is also often difficult to interpret this information, leading to flawed decisions when it comes to adjusting parameters for manufacturing equipment.
Manufacturing companies are always under pressure to improve their yield to not only meet demand but also shareholder expectations. The most advanced equipment and hard drives full of test data do not guarantee a manufacturer can improve their yield since older MES may not have the capability to analyze this data.
How A Smart Factory Can Improve Traditional Manufacturing Processes
To add smart manufacturing process methods into their fabrication plants, a semiconductor company needs to look into the following. There are both opportunities to optimize production and improve yield. There are plenty of challenges as well.
The Digital Twin Concept
A digital twin of the semiconductor fabrication plant is essentially a virtual system that can be used to run simulations. Many of the modern equipment used during production already comes with 3D models and detailed specifications of how it’s supposed to work. Engineers have also come up with models that simulate manufacturing processes. Together, these models can be utilized to simulate the flow of production, and processes within it, and forecast the results.
Once a digital twin of the fabrication plant is established, specific parameters like the mix of products, materials, and even customer supply orders can be tweaked to run simulations. The optimum settings for new equipment and operating procedures can be discovered to improve yield. The time taken from the prototype stage to full production can be reduced as well.
A digital twin’s simulations can be further improved by feeding it data from the MES as well as maintenance, testing, and scheduling operations. This can allow manufacturers a way to understand their factory’s performance in real time. Naturally, running these digital twin simulations requires advanced computing with statistical modeling and machine learning capabilities as well as simulation software.
A Manufacturing Execution System With Improved Scheduling
The manufacturing execution system or MES of a semiconductor fabrication plant is the software that does the monitoring, documentation, and controls the entire production line from raw materials to the finished product. These systems arose as the need for compliance grew in highly regulated industries like aerospace and medical, requiring methods for traceability in case a faulty product needed to be recalled. This need exists within the semiconductor industry as well.
Conventional MES connected to scheduling systems allow for basic product planning across a scale of months or days, which gives production teams an idea of the production volume required, the deadlines to be met, as well as resources and materials needed to produce it. However, since the product mix manufactured at a plant is always changing, the production team on the current shift needs constant updates on what needs to be done. Finite production scheduling is increasingly being required at the shift or even hourly level.
With a smart manufacturing approach, new MES is being developed with built-in scheduling, unlike the older models that often had limited or zero integration with their scheduling applications. This allows for testing to be conducted without delaying ongoing production, and the production team on the current shift gets detailed views of resource constraints, priorities as well as what needs to be done at the workstation level.
The latest MES are capable of complex modeling for main production processes as well as secondary ones like managing product recipes, specifications, and equipment. When a new product or process improvement is introduced, the MES can conduct tests and track their results.
If the MES has centralized change management capabilities, the optimum workflows for these newly introduced elements can be easily rolled out to any of the relevant fabrication plants and/or production lines of the company. Smart manufacturing allows the company’s decision-makers to design and control these processes from anywhere. If a new process improvement is discovered at one factory, it can be reliably applied to another production line somewhere else.
Semiconductors and the integrated circuit made from them are growing in complexity. Real-time information is required to increase yield, make production more cost-efficient, and reduce time to market. The latest manufacturing equipment can provide these vast amounts of data gathered from sensors deployed inside them. Big data analytics are required to make sense of this data and obtain useful insights about the production line performance.
These insights can be presented to the factory engineers through dashboards that allow them to understand yield anomalies, non-conformance, and various other quality-related information. Forecasting is also possible, allowing manufacturers to perform predictive maintenance of equipment which can drastically reduce the chance of breakdowns and increase availability. Process failures can also be predicted, reducing loss of yield.
Why The Semiconductor Industry Is Hesitant
Though the technologies of the fourth industrial revolution and smart manufacturing have immense potential to improve manufacturing within the semiconductor industry, some companies are still hesitant. This is due to significant restructuring and costs combined with perceived non-benefits of smart manufacturing since there is still little information on its return on investment. Some believe that Industry 4.0 is just marketing hype.
Although smart manufacturing has not yet been fully implemented in the industry by the fabrication plants, some suppliers in the semiconducting ecosystem have already moved forward to develop the software and equipment needed to realize the potential of this concept. Siemens has application development platforms and software solutions that can allow manufacturers to fully digitize their operations. Exyte has solutions like smart sensors for preventative maintenance, real-time semiconductor cleanroom monitoring and control, and cloud-based facility monitoring.
With the relevant technologies becoming more popular, the ecosystem will continue to develop. Semiconductor manufacturers that take advantage of smart manufacturing early will gain a significant competitive advantage and be able to handle the consumer demands of the near future. For more information on industry news, check out Inquivix Technologies!
Smart manufacturing is an approach that utilizes emerging technologies like smart sensors, artificial intelligence, big data analysis, simulations, human-machine interfaces, and robotics. Real-time data is gathered, analyzed, and decision-makers are provided with recommendations to optimize production processes, and improve the yield without slowing down production.
A manufacturing execution system or MES is software that can monitor and control all production operations of a product’s journey from raw materials to a finished product.
The MES involves monitoring and controlling equipment on the production line. Enterprise Resource Planning (ERP) is software used for scheduling and inventory management.