During the last decade, we witnessed the inception of Industry 4.0, or the Fourth Industrial Revolution, a now familiar term describing the evolution of manufacturing towards smart, fully connected factories leveraging digitization and the integration of cyber and physical systems.
During the last decade, we witnessed the inception of Industry 4.0, or the Fourth Industrial Revolution, a now familiar term describing the evolution of manufacturing towards smart, fully connected factories leveraging digitization and the integration of cyber and physical systems. The benefits of adopting Industry 4.0 are seen in increased speed and efficiency of development and production accompanied by higher quality products and greater customer satisfaction.
Key technologies responsible for the continued growth of Industry 4.0 include Artificial Intelligence (AI); Big Data analytics; Modeling, Simulation and Visualization (MSV); and 3D printing also known as additive manufacturing. These technologies have advanced product design and production substantially in recent years, enabling companies that use them to gain a competitive edge. They are often used in combination, for example, AI with Big Data analytics and MSV with 3D printing.
AI is the underpinning of all the other technologies above, enabling them to deliver the most value. It’s used successfully today in a wide variety of applications such as computer vision, speech recognition, natural language processing, social network filtering, machine translation, material inspection, and others. In a 2018 survey of 300 executives with large industrial companies across the world, it was found that72% of them had either deployed AI-based technology or were in the process of doing so (SAS, 2018). In 2020, one in ten enterprises were using ten or more AI applications (Columbus, 2020). Another study predicts that “by the end of2024, 75% of enterprises will shift from piloting to operationalizing AI, driving a 5X increase in streaming data and analytics infrastructures.” (Blyler, 2021). Research from Accenture suggests that AI will add approximately $3.7trillion to the manufacturing sector by 2035 (Accenture, 2018).
Likewise, the growth of connected devices has enabled today’s organizations to collect a staggering amount of data. Data can be gathered from just about anything from social media engagement and industrial equipment to GPS sensors and carbon emissions. In2018, over 50% of companies across the world had already adopted Big Data practices, with use cases found in every industry (Chuprina, 2020). Combining BigData and AI allows companies to maximize the benefits of data analytics. Augmented analytics or advanced analytics techniques have been developed to handle extremely large amounts of data, including data cleaning, storage and management, as well as data mining and warehousing. The amount of data will only continue to grow and will be accompanied by increased cloud migration (Khvoynitskaya, 2020). Another trend will be towards fast data allowing for processing in real-time streams. This means actionable data, with companies being able to make decisions and take appropriate actions much faster.