The 2024 $2.9 billion machine-to-machine connections market is expected to reach $5.3 billion by 2029, a 12.7% CAGR, according the “Machine-to-machine (M2M) Connections Market” report by Markets and Markets. Add to that the forecast for global smart factory market size to reach $140.9 billion by 2027, according to the same company’s “Smart Factory Market by Component, Solution, Industry and Region” report, and it is no surprise that today’s multidisciplinary design engineers have had to adapt.
In the M2M space, growth is attributed to increasing support by the government toward M2M connections and the increasing popularity of smart cities and connected cars, according to a release. Additionally, the emergence of M2M devices in telemedicine is expected to create lucrative opportunities for the market.
The use of M2M technologies in the medical device industry can help improve patient care and advance healthcare delivery in a digitally enabled era. It also highlights the importance of data security, regulatory compliance and interoperability standards within the healthcare sector.
The increasing adoption of IoT and AI and the increased use of robots in factories are major growth factors for smart factories, according to a press release.
The top 10 major players are reported to include: ABB Ltd., Endress+Hauser AG, Emerson Electric Co., General Electric Co., Rockwell Automation Inc., Schneider Electric, Siemens AG, Mitsubishi Electric Corp., Honeywell International Inc. and Yokogawa Electric Corp.
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Effect on Today’s Design Engineers
As the industrial manufacturing segment continues to adopt IIoT and M2M technologies, processes and operations can be streamlined, potentially resulting in overall cost savings, predictive maintenance capabilities and better data analytics.
This connectedness has influenced the way that multidisciplinary engineers design today’s machines. They now consider:
- Smart connectivity—integrating sensors, actuators and communication modules that allow machines to interact with each other, share data and respond to real-time demands.
- Predictive maintenance—incorporating predictive maintenance algorithms, condition-monitoring sensors and predictive analytics tools that help with machine reliability and efficiency.
- Cybersecurity and data privacy—implementing encryption protocols, access controls and protection against cyberthreats in interconnected manufacturing environments.
- Integration or AI and automation—incorporating AI algorithms, machine learning models and autonomous control systems.
- Scalability and flexibility—designing modular, adaptable machines that can incorporate new features, upgrades and functionalities to adapt to changing requirements.
By embracing M2M technologies in machine design, today’s engineers can create intelligent, efficient and adaptable machines that drive innovation and competitiveness in today’s modern manufacturing environment.
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