While many Industrial IoT initiatives start out successful in a pilot project, things become much harder when it's time to scale up. While it's one thing to connect a few devices, scaling to hundreds or thousands is another matter altogether.
It's not about adding more hardware. It's about creating a design that can scale up without making things complicated.
In this article we'll discuss five key principles to consider when developing an Industrial IoT solution.
Design with Objectives in Mind
Technology is there to solve business problems.
But before deciding on the technologies and solutions to use, it's important to define the objectives you have in mind and be able to measure them. Here are some examples of such objectives:
- Reduce equipment downtime
- Improve OEE (Overall Equipment Efficiency)
- Reduce energy usage
- Improve visibility into production process
- Improve maintenance planning
The objective is crucial for determining the kind of data that needs to be collected and analyzed.
Make Sure You Have Data Standardization from the Start
As you deploy industrial Internet of Things (IoT) more widely, inconsistent naming conventions and data formats can create problems very fast.
Standardized names for sensors, assets, measurement units, and times can increase interoperability and make it simpler to do analyses later on.
Structured data will be much easier to integrate when you add dashboards, AI models, or reports.
Disconnect Devices and the Business Logic
A common mistake in the architecture of industrial Internet of Things is to connect devices too closely to application logic.
In practice, it is better to consider connectivity as a different layer.
A good architecture usually consists of the following:
- Devices and sensors
- Connectivity layer
- Data processing platform
- Applications
- Analytics and visualization
Design Your System with Cybersecurity in Mind
As your industrial system becomes increasingly connected, cybersecurity must become an integral part of your design.
The following is considered best practice:
- Device authentication
- Encryption
- Access controls
- Firmware updates
- Network segmentation
- Monitoring
It is much harder to implement security retroactively than to design it in.
Design For Scalability
Even if an initial deployment involves just one production line, it's important to plan for eventual growth.
Questions worth asking include:
- Will the system accommodate future additions without major redesign?
- Will the protocols allow for future devices to communicate?
- Can more data be added to the system without issues?
- Is it simple to add new analytics functionality?
Thinking about potential future growth in advance will prevent costly redesigns down the road.
Final Thoughts
It's crucial to design Industrial IoT as an operation platform rather than a technology project that is only going to last in the short term.
Those who focus on standardization, modularity, security, and scalability will have the best chance at adopting future technologies such as AI, predictive maintenance, digital twin technology, and advanced analytics.
Readers interested in industrial IoT architecture, AI, and smart manufacturing can find technical analysis from Aperture Venture Studio.
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