Smart manufacturing rise: The next wave of manufacturing innovation

• Author:
• Author name

  Quantumrun Foresight
• December 18, 2023

Insight summary

Smart manufacturing, blending technologies like IoT, AI, and cloud computing, is rapidly growing, expected to reach $365.22 million USD by 2028. This evolution is marked by increased digitization for enhanced productivity, with North America leading in adoption. Key developments include the use of connected devices, AI for quality and supply chain management, and advanced robotics to improve efficiency. While offering benefits like reduced waste and optimized supply chains, this shift also raises cybersecurity concerns and demands new skills in the workforce. Companies like General Electric and BMW exemplify this transition, which is set to reshape the manufacturing landscape.

Smart manufacturing rise context

Market intelligence firm ResearchandMarkets projected that the smart manufacturing industry will surge from $258.72 million USD in 2022 to $365.22 million USD by 2028. This growth is anticipated to have a compound annual growth rate (CAGR) of 6.0 percent. The manufacturing sector's drive to enhance productivity and visibility in its processes has led to increased adoption of digitization, such as data analytics, predictive maintenance, and industrial networking.

The market growth is further stimulated by the growing demand for integrated and simplified software systems over a single platform to deliver real-time information. Furthermore, the Industry 4.0 movement is facilitating the shift of industries from legacy systems to intelligent tools.

The North American region holds a significant portion of the global smart manufacturing market. This dominance can be attributed to the region's increasing adoption of industrial automation solutions, such as IoT and cloud platforms, a growing emphasis on regulatory compliances, and rising demand for software systems that reduce time and costs. However, digitization poses a significant threat of industrial espionage or sabotage. These attacks can result in economic losses, production disruptions, or even catastrophic nationwide consequences. Therefore, safeguarding manufacturing systems from cyber vulnerabilities while ensuring functionalities remain uncompromised is crucial across the entire manufacturing enterprise. 

Disruptive impact

One of the critical ways the manufacturing industry is transitioning to smart systems is through connected devices and sensors. These devices can gather data about the manufacturing process and transmit it to a central system. AI and machine learning (ML) algorithms analyze this data and provide insights into quality control, predictive maintenance, and supply chain management. By leveraging these technologies, manufacturers can quickly identify and address issues, minimize costly downtime, and adjust their processes.

Advanced robotics and automation are also being deployed to prepare factories for Industry 4.0. Robots can perform tasks that are too dangerous or repetitive for humans, improving efficiency, reducing errors, and increasing output. Finally, manufacturers are also transitioning to smart systems by adopting cloud computing and big data analytics to take advantage of real-time information.

An example of a manufacturing firm that is adopting smart systems is General Electric (GE). The company uses IoT, AI, and big data analytics to optimize its production processes across various industries, including aviation, healthcare, and energy. Automaker BMW uses robots and IoT to streamline assembly, improve quality control, and reduce downtime.

Implications of smart manufacturing rise

Wider implications of smart manufacturing rise may include: 

• The displacement of many low-skilled workers and the creation of a skills gap, as the industry demands a workforce with higher education and specialized skills.
• More business opportunities for companies that provide smart manufacturing solutions and tools.
• Reduced waste, energy consumption, and emissions.
• Increased competition among companies, leading to consolidation and mergers within the industry.
• Optimized supply chains that are less prone to disruptions but might become more susceptible to cyber-attacks.
• Human workers being reskilled to maintain machines and oversee automation initiatives.
• The increasing adoption of digital twins and private 5G networks.
• New regulations that incentivize businesses to further reduce their carbon emissions.

Questions to consider

• What challenges might businesses face when implementing smart manufacturing, and how can these be addressed?
• How can governments and policymakers further support the development and adoption of smart manufacturing?