This article will discuss:
- The challenges of adopting industrial cloud in facilities
- The importance of developing applicable industrial edge computing hardware for end-users
- How accurately designed industrial edge computing hardware increases the adoption rate of industrial cloud
Edge computing devices are generally devices that provide entry points into enterprise networks. This means the average router or switch used in white-collar offices is actually an edge computing device. While popular hardware may work excellently in controlled environments, it will struggle to function as industrial edge computing hardware in factories or facilities where heavy-duty equipment works round the clock or where physical contact is constant. The challenge in finding applicable, long-lasting hardware represents one of the reasons why 41% of stakeholders struggle with adopting industrial cloud within their facilities.
Understanding the challenges industries face with edge computing hardware
The task of integrating cloud computing in manufacturing or industrial processes is solely being driven by software and communication service providers. This is why all the news coming out of the industrial cloud niche is focused on 5G connectivity, OPC UA over TSN protocols, and IIoT interconnectivity. While the focus on the flashy aspects of the industrial cloud and its benefits has created a market share of $9 billion, it has relegated the hardware that will drive a more complete adoption to the background. But statistics from McKinsey show that this should not be so. This is because edge computing can potentially increase the hardware market to a value of $215 billion by 2025 if hardware design is achieved correctly.
For industrial edge computing hardware to realize its potential, the challenge of developing durable industrial hardware that can withstand the rigors of shop floor operations while delivering edge computing must be overcome. Other challenges edge computing devices face are matching functionality and durability with esthetics. A scenario that highlights this issue is the design of IoT applications and devices for industrial use. Although an app will function on the ultra-slim devices or hardware that dominate today, that device is unlikely to last for more than a year in the heat and oil dominated industrial world. This is why 37% of manufacturers struggle with cloud adoption or getting cloud solutions to function properly.
To increase the adoption rate of cloud computing and edge computing within industrial facilities, vendors and service providers must hack the development of applicable industrial edge computing hardware. Only then, will the flashy computing resources and intuitive app interfaces being developed in squeaky clean labs be easy to use or adopt across diverse manufacturing industries.
Understanding the process of designing applicable industrial edge computing hardware
To design industrial edge computing hardware that meets the challenges of industrial applications, different requirements must be taken into consideration. These requirements include:
- Durability – Once again durability must be a key consideration when designing industrial edge computing hardware. This is due to the messiness and physical attributes of shop floor operations. This means when designing hardware, it must be built with durable materials that can withstand increased temperatures, enhanced vibrations, and liquid spills. The edge hardware must also be able to function under these conditions for the long haul.
- Aesthetics and architecture – To bring computing to the deepest parts of a facility, the hardware that houses edge computing resources must be esthetically designed for integration into diverse equipment. Thus, its build is a key factor that must be considered by vendors as well as the final appearance of the industrial edge computing device. This is because commercial hardware that captivates the end-user is likely to do well in diverse markets.
- Power or energy requirements – The energy used by hardware devices adds to the total overhead cost (TOC) of running facilities. Manufacturers interested in adopting industrial cloud technology generally calculate the TOC of adoption before making a move, and energy requirements are part of the expenditure column. This is why industrial edge computing hardware should consist of ultra-low powered microcontroller units.
- Cybersecurity – Securing manufacturing data has always been a key consideration for the integration of industrial cloud within facilities. Thus both data captured by software apps and hardware devices must be secured from eavesdroppers and hackers. To mitigate security risks, the integration of hardware cryptographic accelerators or reverse-engineering firewalls must be used to circumvent cyber threats.
Buttressing the highlighted points, IDC analyst Ashish Nadkami recommends that engineers should abstain from picking custom edge hardware tied to a specific vendor’s applications or ecosystems. Instead, engineers and IT managers should focus on choosing or customizing industry-standard hardware that is durable, non-proprietary, and lasts for the long haul. The EXOR JSmart series of human-machine interfaces are examples of industrial edge computing hardware that meet these recommendations.
How applicable industrial edge computing hardware increases industrial cloud adoption rate
Aesthetically pleasing industrial edge computing hardware with intuitive user interfaces simplifies the process of capturing data and computing in diverse ways. An example is the use of 2D or 3D visualization techniques to explore captured data and relevant information. A visual representation of shop floor relationships and variables in addition to visualized instructions from centralized cloud platforms make it easy for employees to understand tasks and take action.
Visualization also simplifies the process of installing edge hardware on shop floors. Thus eliminating the difficulties many manufacturers say they experience with setting up cloud services to function as expected. The ability to integrate emerging features such as speech recognition and computer vision tools within industrial edge computing hardware will also be selling points for many manufacturers, which will lead to an increase in cloud adoption rates.
Conclusion
The positive symbiotic relationship between hardware, software and other interrelated technologies is expected to drive the adoption rate of edge computing. With the right hardware, ML, AI, computer vision, and speech recognition tools can be integrated into industrial edge computing hardware. Thus, the dynamism of edge computing provides enterprises with the opportunity to explore how emerging technologies can advance industrial processes especially with respect to the hardware community.
