The technology industry continues to be a hotbed of patent innovation. Activity is driven by the increasing demand for precision and efficiency in manufacturing, alongside the potential for substantial cost savings and improved product reliability, and growing importance of technologies such as computer vision for accurate visual inspection, machine learning models for pattern recognition, and Internet of Things (IoT) sensors for real-time data collection, collectively driving advancements in quality control AI solutions. In the last three years alone, there have been over 4.1 million patents filed and granted in the technology industry, according to GlobalData’s report on Artificial intelligence in technology: quality control AI. Buy the report here.
However, not all innovations are equal and nor do they follow a constant upward trend. Instead, their evolution takes the form of an S-shaped curve that reflects their typical lifecycle from early emergence to accelerating adoption, before finally stabilizing and reaching maturity.
Identifying where a particular innovation is on this journey, especially those that are in the emerging and accelerating stages, is essential for understanding their current level of adoption and the likely future trajectory and impact they will have.
190+ innovations will shape the technology industry
According to GlobalData’s Technology Foresights, which plots the S-curve for the technology industry using innovation intensity models built on over 1.5 million patents, there are 190+ innovation areas that will shape the future of the industry.
Within the emerging innovation stage, GenAI for design, finite element simulation, and deep reinforcement learning are disruptive technologies that are in the early stages of application and should be tracked closely. AI in EHR, intelligent predictive maintenance, and forward inferencing are some of the accelerating innovation areas, where adoption has been steadily increasing.
Innovation S-curve for artificial intelligence in the technology industry
Quality control AI is a key innovation area in artificial intelligence
Quality control AI utilizes artificial intelligence technologies to oversee and uphold product and process quality. It encompasses the application of sophisticated algorithms and machine learning methods to scrutinize data, identifying any discrepancies or imperfections that might arise during production or manufacturing. Through the automation of quality control processes, AI contributes to operational efficiency, streamlined workflows, and the enforcement of consistent quality benchmarks.
GlobalData’s analysis also uncovers the companies at the forefront of each innovation area and assesses the potential reach and impact of their patenting activity across different applications and geographies. According to GlobalData, there are 1,250+ companies, spanning technology vendors, established technology companies, and up-and-coming start-ups engaged in the development and application of quality control AI.
Key players in quality control AI – a disruptive innovation in the technology industry
‘Application diversity’ measures the number of applications identified for each patent. It broadly splits companies into either ‘niche’ or ‘diversified’ innovators.
‘Geographic reach’ refers to the number of countries each patent is registered in. It reflects the breadth of geographic application intended, ranging from ‘global’ to ‘local’.
Patent volumes related to quality control AI
|Company||Total patents (2010 - 2022)||Premium intelligence on the world's largest companies|
|Gree Electric Appliances||99||Unlock Company Profile|
|Samsung Heavy Industries||69||Unlock Company Profile|
|NIKE||50||Unlock Company Profile|
|Toyota Motor||47||Unlock Company Profile|
|Yokogawa Electric||126||Unlock Company Profile|
|Fanuc||75||Unlock Company Profile|
|ABB||74||Unlock Company Profile|
|Siemens||453||Unlock Company Profile|
|State Grid Corporation of China||836||Unlock Company Profile|
|Hitachi||448||Unlock Company Profile|
|Dell Technologies||58||Unlock Company Profile|
|General Electric||83||Unlock Company Profile|
|EssilorLuxottica||48||Unlock Company Profile|
|Honda Motor||63||Unlock Company Profile|
|China Southern Power Grid||183||Unlock Company Profile|
|Mitsubishi Electric||339||Unlock Company Profile|
|Panasonic||139||Unlock Company Profile|
|China Petrochemical||79||Unlock Company Profile|
|Omron||52||Unlock Company Profile|
|Bayerische Motoren Werke||51||Unlock Company Profile|
|Boeing||200||Unlock Company Profile|
|IBM||83||Unlock Company Profile|
|Honeywell International||91||Unlock Company Profile|
|Mitsubishi Heavy Industries||162||Unlock Company Profile|
|Inspur Electronic Information Industry||51||Unlock Company Profile|
|Toshiba||129||Unlock Company Profile|
|NEC||149||Unlock Company Profile|
|Intel||282||Unlock Company Profile|
|HD Hyundai||193||Unlock Company Profile|
|POSCO||50||Unlock Company Profile|
|Causam Energy||75||Unlock Company Profile|
|China Tobacco Yunnan Industrial||67||Unlock Company Profile|
|Omron Tateisi Electronics||99||Unlock Company Profile|
Source: GlobalData Patent Analytics
Among the companies innovating in quality control AI, State Grid Corporation of China is one of the leading patent filers. The company's patent is aimed at a method and device for processing power data. It involves creating an evaluation formula for power demand response by considering factors such as load distance, amplification index, and weight coefficient. The invention addresses issues in prior methods, offering a more stable and universally applicable evaluation approach for power demand response systems. Other prominent patent filers in the space include Siemens and Hitachi.
In terms of application diversity, Intel leads the pack, while Fanuc and Nike stood in the second and third positions, respectively. By means of geographical reach, Causam Energy held the top position, followed by Intel and Nike.
Quality control AI is of paramount importance as it revolutionizes the manufacturing process by automating the detection of defects and anomalies, ensuring higher product quality and consistency. The technology not only improves operational efficiency but also reduces costs associated with manual inspection, ultimately enhancing overall customer satisfaction and brand reputation.
To further understand the key themes and technologies disrupting the technology industry, access GlobalData’s latest thematic research report on Artificial Intelligence (AI).