Insights
In the context of the modern era, smart homes are the AI applications that come second only to smartphones and smartwatches. As the penetration rate of smart home devices increases, more and more AI-enabled devices are permeating into human life, ushering in a large-scale era of personalization. The realization of smart homes not only requires smart appliances but also sensors and energy management systems. The deployment of AI will enhance recognition and control.
The diverse application scenarios of smart homes result in a wide variety of products. Despite the vast market size, there is an issue of product ecosystem fragmentation, leading to slow deployment. This can be addressed through the integration of the smart home market via the Matter protocol. As Matter facilitates communication between different devices through software protocols, the importance of software in devices will increase with the product’s AI capabilities, catering to the demands of edge AI applications.
Although CPUs in MCUs are currently dominated by the Arm architecture, open-source RISC-V is gradually rising. In addition to its features such as customization, modularity, and cost-effectiveness, RISC-V is expected to become one of the advantages in smart home applications. It continues to gain support and application from many major manufacturers, expanding the ecosystem of the RISC-V architecture.
Because TinyML models are much smaller than general-purpose AI, they do not require a large amount of computational resources for deployment. This makes them suitable for IoT devices or smart homes that require large-scale deployment, with significant advantages in both technology and cost. Furthermore, with the diverse range of products in smart homes and the increasing demand for product functionality, the form of MCUs equipped with NPUs will become increasingly common as they adapt to the product’s uniqueness and evolve with AI integration.
In-Depth Analyses
The US ban on Chinese industries has left China struggling with a seemingly severe shortage of chips. However, China’s tech giants refuse to surrender; instead, they’re pivoting quickly to survive the game.
Since 2019, the US Department of Commerce has added Chinese leading companies like Huawei to its entity list. Restrictions were expanded in 2020 to include semiconductor manufacturing, making a huge impact on SMIC’s advanced processes below 14nm.
Starting in 2021, the US has been intensifying its control by placing more IC design houses on the list, which include Jingjia (GPU), Shenwei (CPU), Loongson Tech (CPU), Cambricon (AI), Wayzim (RF&GPS), and Yangtze (NAND Flash). Furthermore, the export of advanced EDA tools, equipment, CPUs, and GPUs to China has also been banned.
The goal of such measures is to hinder China’s progress in high-tech fields such as 5G/6G, AI, Cloud computing, and autonomous driving by eroding the dominance of its tech giants over time.
China has been aggressively pursuing a policy of domestic substitution in response to the US’s increasing control. As part of this effort, leading domestic IC design companies like Horizon, Cambricon, Enflame, Biren, Gigadevice, and Nations Technologies have been ramping up their efforts for comprehensive chip upgrades in a variety of applications.
Chinese Brands Ramping up for ASICs
There is a particularly intriguing phenomenon in recent years. Since 2019, China’s leading brands have been venturing into chip design to develop highly specialized ASICs (Application Specific Integrated Circuits) at an unprecedented speed. This move is aimed at ensuring a stable supply of chips and also advancing their technical development.
A closer look at how top companies across diverse application fields integrate ASIC chips into their technology roadmap:
China’s tech giants are leveraging advanced foundry processes, such as TSMC’s 5nm and Samsung’s 7nm, to produce cutting-edge AI chips for high-end applications like cloud computing, image coding, AI computing, and network chips.
Alibaba launched its AI chip, Hanguang 800, and server CPU, Yitian 710, in 2019 and 2021, respectively. Both chips were manufactured at TSMC’s 5nm process and are extensively used on Alibaba’s cloud computing platform.
In December 2019, Baidu released its AI chip, Kunlun Xin, which uses Samsung’s 14nm process, followed by its 2nd generation, which uses a 7nm process, for AI and image coding.
Due to the high technical threshold of SoC technology used in smartphones, mobile phone brands mainly develop their own chips by optimizing image, audio, and power processing.
In the year of 2021, Xiaomi released the ISP Surge C1, followed by the PMIC Surge P1. Vivo first released the ISP V1 in September 2021, followed by an upgraded product, V1+, in April 2022, and then V2 in November 2022.
OPPO, on the other hand, unveiled the MariSilicon X NPU in December 2021, which enhances the image processing performance of smartphones, using TSMC’s 6nm process, and later revealed the MariSilicon Y Bluetooth audio SoC TSMC’s 6nm RF process later in 2022.
The brands are focusing primarily on MCU and PMIC chips that are essential to a wide range of home appliances. They’re also incorporating SoC chips into their smart TVs.
For example, Hisense has jumped into the SoC game in January 2022 by releasing an 8K AI image chip for their smart TVs. Changhong manufactured an MCU with RISC-V architecture and a 40nm process in December 2022.
The leading companies are developing ISP and highly technical SoC chips for autonomous driving, which has resulted in a slower development process.
In 2020, NIO formed a semiconductor design team for Autonomous driving chips and ISP. Xiaopeng started its Autonomous driving and ISP chip R&D project in the first half of 2021. Li Auto established two subsidiaries in 2022, with a primary focus on power semiconductors and ISP chips.
Finally, BYD, which has a long history of working on MCU and power semiconductor components, also announced its entry into the autonomous driving chip market in 2022.
Navigating the US’ Tech Crackdown
So why are these brands investing so heavily in self-developed ASICs?
One reason is to avoid the risks associated with export control policies from the US and its allies. Developing their own chips would mitigate the risk of supply chain disruptions caused by potential blockades, ensuring a stable supply and the sustainability of their technology roadmap.
In addition, there are many internal incentives for these brands – for instance, companies that have self-developed chips will be eligible for more government subsidies, as this aligns with the government’s aggressive policy to foster the semiconductor industry. Brands can also reduce their reliance on external suppliers by using their own ASIC chips, which can further lower the operating costs.
Technology wise, ASIC chips allow brands to enhance the features they require and enable better integration with the software, which could provide efficiency gains at system level – similar strategies are also being employed by Google and AWS with their AI chips, as well as by Apple with its M1 SoC.
With all things considered, it is certainly possible that we will see a persistent trend of more self-developed ASIC chips made by Chinese brands, which could potentially lead to significant changes in China’s semiconductor supply chain from the ground up.
Press Releases
The global smart manufacturing market is expected to welcome a golden period of growth across five years, starting with annual revenue of US305 billion in 2021 and surpassing US450 billion in annual revenue in 2025 at a 10.5% CAGR, according to TrendForce’s latest investigations. This growth can be attributed to several factors, including the accelerating digital transformation efforts from enterprises, the increased demand from industrial automation and WFH applications, and the emergence of 5G, advanced AI technologies, and other value-added services.
Looking ahead to 2022, TrendForce believes that the outlook of smart manufacturing has evolved from such conservative strategies as improving the resilience of the manufacturing industry itself, to increasing the industry’s production capacity as well as efficiency while reducing both energy expenditure and carbon emissions. These advantages are expected to serve as the main drivers propelling the growth of the smart manufacturing market next year.
Smart manufacturing development will revolve around 5G, edge computing, and carbon footprint reduction going forward
The core feature of smart manufacturing lies in its ability to deliver instant feedback through the integration of virtual data and real, physical equipment. Hence, low latency, high security, and fast computing power have become increasingly important for smart manufacturing development, which will revolve around edge computing and 5G applications, including AR/VR, machine vision, digital twins, and predictive maintenance, all of which will experience considerable upgrades in functionality thanks to smart manufacturing.
Furthermore, as the issue of global warming gains more and more media coverage, 137 countries have now committed to achieving carbon neutrality. This pursuit of environmentally friendly outcomes is also reflected in the current state of industry 4.0 development. For instance, companies including Henkel, Johnson & Johnson, Siemens, and Tata Steel all operate manufacturing facilities that qualify them for membership in WEF’s Global Lighthouse Network. The aforementioned companies have ensured their facilities operate with optimized energy consumption, highly effective manufacturing processes, and reduced carbon emissions through the adoption of computer simulation/modeling and smart management. TrendForce expects the future design of smart manufacturing equipment and factories to center on the use of environmentally friendly IoT technologies.
Taiwanese manufacturers are likely to seize shares in the niche market in light of the rise of domestic micro-factories
It should be pointed out that the Taiwanese manufacturing industry possesses certain competitive advantages in the global market, including a highly consolidated supply chain, a relatively comprehensive smart manufacturing value chain, and the ability to deliver highly customized solutions. In particular, various Taiwanese manufacturers specialize in full-service, integrated smart solutions that feature equipment health monitoring and machine vision functionalities, thereby significantly lowering the barrier for adoption. Assuming that the domestic industry is able to continue leveraging their existing competitive advantages and furthering their current developments, TrendForce expects micro-factories to become the key factor through which Taiwanese companies can find commercial success in the global smart manufacturing industry.
Although the smart manufacturing value chain has historically had its various verticals spread throughout the world, recent trends such as a return of domestic manufacturing and tectonic shifts in the manufacturing industry have resulted in the rise of shortened supply chains as well as localized operations. These developments have led to the recent surge of micro-factories. TrendForce’s investigations indicate that, in addition to their high degree of automation and analytical accuracy, micro-factories deliver improved manufacturing outcomes while minimizing resource consumption and yielding such benefits as a flexible supply chain, lean human resources, and low initial cost. Micro-factories have already seen widespread usage in the global automotive and electronics industries in light of these benefits. Likewise, TrendForce believes that Taiwanese manufacturers of bicycle chains, steel nuts/bolts/screws, and suitcases will likely succeed in their respective niche markets by upgrading their manufacturing operation with micro-factories.