In order to cope with long-term uncertainty, what “advanced features” will future intelligent manufacturing need to unlock?
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In the movie Modern Times, Chaplin plays a worker who repeats mechanical labor day after day on the production line, almost becoming a robot. This is an aspect of the second industrial revolution (or Industry 2.0) that began in the late 19th century. The introduction of assembly line production and electrification greatly improved production efficiency and brought humans into the industrial age of large-scale machine production. In the following hundreds of years, the wave of changes in productivity and production methods around humans and machines continued to advance.
The ongoing Industrial 4.0 revolution is intended to achieve this. Its goal is to promote the digital transformation of traditional manufacturing and build smart factories that introduce IoT and AI technologies. Through the collection and analysis of big data and the use of virtual models constructed using various digital technologies, it will improve real-world production efficiency and yield, while also saving costs, improving safety and stimulating product innovation.
However, the progress and impact of the Fourth Industrial Revolution are obviously very different from the previous three. "In contrast to previous industrial revolutions, this revolution is developing at an exponential rather than linear speed," said Klaus Schwab, founder of the World Economic Forum, in his book The Fourth Industrial Revolution, because "it will not only affect what we produce and how we produce it, but also change who we are."
At the same time, in recent years, after the global pandemic, geopolitical conflicts and various uncertainties, the world has new considerations on the transformation path of smart manufacturing. Emphasis on flexible, innovative and elastic production processes and supply chain resilience have become new demands.
Obviously, the future of intelligent manufacturing is not just a simple intelligent upgrade of productivity and production methods, it is being given a richer connotation. In the face of long-term uncertainties that may arise in the future, how can we develop a smart prescription for the future through the deep integration of advanced technologies including the Internet of Things, cloud computing, artificial intelligence, virtual reality, blockchain, 5G networks, and traditional industries?
In this context, how can industrial intelligence be implemented? How can digital productivity be built? How can human intelligence and machine intelligence be integrated and collaborated?
The next step of smart manufacturing: flexibility, agility and personalization
Figure 1 (Source: freepik)
The "Just in Time" production method, which was once perfected by the manufacturing industry after long-term operation, that is, "purchasing the required number of parts when needed" and keeping inventory to extremely low or even zero inventory, has encountered unprecedented challenges in the past two or three years.
Uncertainties such as chip shortages, supply chain disruptions, and geopolitical conflicts have brought serious impacts on the manufacturing industry. Many international manufacturers have begun to consider switching to a "Just in case" production method, that is, dispersing production and increasing inventory.
According to media reports, Intel has recently made a major change in its business strategy. For more than 50 years, the global semiconductor giant has concentrated its manpower, material resources and funds on its production base in the United States and exported semiconductors to the world. Now it is trying to change its business model that has been adhered to for more than 50 years and has begun to promote factory construction in Europe and other regions in order to be closer to customers.
Since the end of the 18th century, mankind has experienced three industrial revolutions. Industry 1.0 changed the traditional manual manufacturing method with mechanization and steam engines; Industry 2.0 greatly improved production efficiency with assembly line production and electrification; Industry 3.0 applied information technologies such as automation, computers and robots to production and manufacturing.
It can be seen that from Industry 1.0 to Industry 3.0, the revolutionary turning points all come from technological innovations in the manufacturing process, which has led to a significant increase in production efficiency. However, the advancement from Industry 3.0 to Industry 4.0 is very different from the previous three. The revolution brought about by Industry 4.0 not only involves the organization and production of products, but also includes the combination of various peripheral software and hardware related to product production. It is an era of software and hardware integration that truly realizes comprehensive intelligence in all aspects of product design, product production, product recycling, product management, etc.
After the world has experienced the impact of a series of new situations such as the epidemic on the industrial industry, it is clear that the question of why we should move from manufacturing to intelligent manufacturing has changed from three years ago. In other words, what development pain points and practical problems the industry is eager to solve through intelligent manufacturing is obviously different from what it was three years ago.
In addition to improving production efficiency and reducing production costs, supply chain resilience that can cope with long-term risks and production processes that emphasize flexibility, innovation, and elasticity have become the focus of more and more manufacturing leaders. This requires a responsive flexible manufacturing system to support it, which can flexibly adjust production lines to quickly meet different order requirements.
If the focus of Industry 3.0 is on comprehensive automation, then Industry 4.0 will be further based on comprehensive intelligent interconnection. This means that we must achieve comprehensive interconnection of people, machines, objects, materials, methods, and environments, make information and data in each link more transparent, and build a new industrial production and service system with full factors, full industrial chain, and full value chain.
To achieve all this, there is an important basic premise: digital productivity.
Digital productivity, mining data value to fight against uncertainty
Figure 2 (Source: freepik)
Statistics from the U.S. Department of Commerce show that unplanned equipment downtime in factories accounts for about 24% of the factory's overall manufacturing costs. This unplanned downtime may be caused by unexpected equipment failures, material shortages, production line scheduling issues, and other reasons. Under the current global situation, such "accidents" may occur more frequently in the future.
In addition, inventory rationalization has always been a major management pain point for industrial enterprises, mainly due to the problem of information silos in upstream and downstream industries. The international giants such as Intel mentioned above had to abandon the once "perfect" Just in Time model for the same reason - uncontrollable factors such as geopolitics and the epidemic have further highlighted the data and information barriers of the upstream and downstream supply chains.
For a long time, industrial enterprises have relied more on work experience when formulating supply chain plans, and it is difficult for material information and product demand information to flow freely across links in the industrial chain. In addition, with the continued fermentation of supply chain cost pressure and the gradual dilution of product gross profit, enterprises are in urgent need of building upstream and downstream information circulation channels in the industrial chain, combining product demand, raw material supply and capacity allocation, scientifically and agilely adjusting production plans, improving capacity utilization, reducing inventory backlogs, improving customer satisfaction, and ensuring stable order fulfillment, thereby achieving highly agile and flexible industrial collaboration.
This is the importance of digital productivity and mining the value of data. It is the foundation for industrial manufacturing to move towards intelligent manufacturing, and it will also be an important technical means to deal with long-term uncertainties in the future.
So how to implement digital productivity?
Foxconn Industrial Internet Co., Ltd. ("IFI"), the world's leading provider of smart manufacturing and industrial Internet solutions, has refined the five elements of digital transformation with "ABCDE". A stands for Analytic or Artificial Intelligence, B stands for Big Data, C stands for Cloud Computing, D stands for domain, and E stands for evidence. A, B, and C are the basic elements of the Internet, while D and E emphasize that digital industry must be applied in specific scenarios, such as CNC, welding, assembly, packaging and other production scenarios, and there must be practical application examples.
Specifically, digital means such as machine learning, big data and automation technology can enable factories to accurately collect, analyze and transmit data, thereby providing higher efficiency, sustainability and quality control for the entire manufacturing enterprise. Digital twin technology can match the virtual and physical worlds, allowing factories to analyze data before actual production and monitor business and other background data in the system, thereby helping industrial end users achieve more optimized performance and avoid possible problems in advance. This manufacturing system in which physical devices are interconnected with the Internet can collect and analyze data, predict errors, and continuously adjust itself by incorporating technologies such as machine learning to adapt to the ever-changing environment. In this way, data truly creates value.
In addition, how to integrate human wisdom into machines and equipment is even more critical. Xiao Yong, deputy director and vice president (technology) of Ningbo Intelligent Manufacturing Technology Research Institute, explained this in a speech on the theme of industrial automation during Mouser Electronics Technology Innovation Week last year. In layman's terms, it is to refine human intelligence (referred to as "human intelligence") from implicit knowledge to explicit knowledge, model and algorithmize it, and then embed various modeled knowledge (mechanism model, data analysis model, etc.) into software, and then embed the software into the chip, and then embed the chip into a module, and then embed the module into the machine equipment, so as to give the machine a certain degree of autonomy and make the machine have a certain degree of "intelligence" (referred to as "intelligence"). "Human knowledge continues to enter the software, and the knowledge carrier has shifted from carbon-based knowledge to silicon-based knowledge, and digital productivity has surged."
In an interview with McKinsey, Zheng Hongmeng, CEO of Foxconn Industrial Internet, pointed out that digitalization usually requires not only IT but also IoT, such as machine networking. "People and machines need to have 'interaction'," he emphasized, "Why can't many companies (intelligent manufacturing) succeed? Because people and machines don't have 'interaction'."
In fact, a key point of Industry 4.0 is that "raw materials (matter)" = "information", or more broadly speaking, it is to informatize and digitize everything in the physical space, and finally realize the digitization of the entire productivity and production process, so as to realize the flow, analysis and reconstruction of data in each link, and form a unified information-physical fusion system. On this basis, coupled with the horizontal integration of the external value chain of industrial enterprises, as well as the networked and vertically integrated manufacturing system, a good information-physical system can be established to achieve self-management of production and maintenance, and quickly and effectively respond to various accidents such as supply chain problems, quality fluctuations, order changes and equipment downtime.
Key technologies and future trends
Figure 3 (Source: Freepik)
Smart manufacturing is a complex ecosystem that includes many cutting-edge technologies such as the Internet of Things, cloud computing, artificial intelligence, virtual reality, blockchain, and 5G networks, and involves many aspects such as perception, automation, networking, human-computer interaction, and big data. However, only a few of these technologies have matured and landed, and most are still on the eve of a large-scale outbreak.
From the perspective of technological change, the ongoing Industry 4.0 integrates sensors, machines, workpieces, industrial software, and IT systems across the entire value chain. Throughout the advancement process, the deep integration of technologies and industries, from analog to digital, from simple to complex, from centralized to distributed, as well as increasingly real-time data transmission, longer-distance seamless network connections, and digital twins, is the main technological change point.
Among them, various sensors, which are basic components on the road to Industry 4.0, are like adding "five senses" to machines, allowing them to sense the state of the environment, which is the first step to becoming an intelligent machine. With the low-cost popularization of sensors in recent years, the cost threshold for the advancement of a new round of industrial revolution has been lowered, making the "stitching" between the physical world and the digital world smoother. On this basis, physical space-time information is continuously transformed into bit data streams, and then through industrial software, artificial intelligence algorithms/computing power improvements, data and software are used to redefine the space-time performance of materials, parts, products, processes, production lines, supply chains, and systems.
Another important foundation is connectivity. Achieving seamless network connectivity over longer distances is a key technical foundation for promoting industrial intelligent applications and innovation and realizing Industry 4.0.
Taking a smart factory as an example, the value it generates depends largely on the ability to connect assets, processes, people and equipment. For example, when all production nodes and equipment applications in the factory can be interconnected to achieve remote monitoring and visibility, combined with technologies such as machine learning, it is possible to further unlock more advanced functions, such as predictive maintenance or data-driven as-a-service business models.
Deloitte's survey report pointed out that at this stage, interconnection is still the primary challenge in building smart factories. For example, in factories made of reinforced concrete, Wi-Fi signals and cellular connection signals are often unstable. Even within the same factory network, the layout, equipment and products of each facility may be unique. So how can the various machines, sensors and other equipment in the workshop be connected and work closely with each other? How can the factory achieve intelligent management of a variety of different equipment? All of this depends on powerful, stable and sensitive connection technology. The main challenges currently faced at the connection level are the complexity of industrial equipment types, communication protocols and data formats, and the lack of effective technical means to achieve low-cost and convenient connection.
What other trends should we pay attention to in the future?
Figure 4 (Source: freepik)
Research firm Gartner recently released the top ten strategic technology trends to be explored in 2023, mentioning a series of technologies related to accelerating the digital upgrade of industrial intelligence, including Digital Immune System, Industry Cloud Platforms, Wireless Value Realization, and Adaptive AI. Gartner believes that these technologies can help enterprises optimize resilience, operations or credibility, expand vertical solutions and product delivery, and explore new forms of interaction and faster response opportunities.
Zheng Hongmeng mentioned the three major directions that Foxconn should continue to focus on in the next three to five years in terms of digitalization and intelligent transformation, which may also provide a way of thinking:
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Continue to work hard on energy management . As a global manufacturing company, Foxconn Industrial Internet uses a large amount of energy for processing, so the continuous development of new energy and the digitalization of energy management are very important directions.
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Build an ecosystem as quickly as possible . Combine more supply chains and more ecosystems to make it a trend.
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Explore the space for robotized production . From the past automated production to intelligent production, it will soon turn to robotized production.
Conclusion: Rethinking the relationship between humans and machines
It is worth mentioning that in 2020, the first year of the global epidemic, the European Commission proposed the concept of "Industry 5.0". In September 2020, the European Commission released "Enabling Technologies for Industry 5.0", and then in January 2021, it released "Industry 5.0 - Towards a Sustainable, People-Oriented and Resilient European Industry".
Industry 5.0 originates from the concept of "Industry 4.0", but its revolutionary nature lies in the fact that one of the important considerations of Industry 5.0 is to open the physical interface between humans and robots. Industry 5.0 requires robots to do monotonous, dangerous, dirty and messy work, while humans do creative and interesting work, but robots are more able to understand humans' intentions and thoughts at work. This means that the intelligence of machines and humans must be deeply integrated in the future, rather than simply replaced.
Rather than simply emphasizing the pursuit of production efficiency and economic benefits, it provides a different focus - emphasizing more overall value orientation, highlighting the importance of research and innovation, and emphasizing people-oriented, sustainability and resilience to support industry in providing long-term services to mankind on a global scale.
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