Automotive manufacturing facilities are increasingly becoming data-rich environments.
Machines, processes, vehicles, tools, people, and various other elements can and do generate considerable amounts of information. Connecting up various technologies and sensors can enable the collection of that data, but what's the next step?
There is great value in the ability to process what was captured and to extract meaningful information.
We'll take a closer look at AIoT and some reasons why connected data and insights can become important enablers in modern automotive manufacturing facilities.
IoT Enables Access to the Physical World
IoT connects various elements of the physical world to applications and systems.
Within the context of manufacturing, connected devices and systems can provide insights into equipment, location, production, material flow, environment, people, and processes. IoT provides a degree of visibility.
On a fundamental level, that can support the kinds of visibility and insight that are often critically needed for operations success. The question then becomes, what can be done with connected data and information about processes?
That's where AI comes in.
AI Transforms IoT Data Into Meaningful Insights
AI enables the processing of connected IoT data and supports deeper analytics around it.
By taking information from the physical world and building up a comprehensive understanding, connected AI applications can help support operational intelligence and decision-making.
It can be helpful to conceptualize the overall flow of such an application:
Physical Assets
↓
Sensors
↓
Connectivity
↓
Data
↓
AI / ML
↓
Decision
↓
Physical Action
In many ways, that's the very essence of AIoT - the combination enables a certain degree of physical intelligence that wasn't possible before.
As mentioned, manufacturing is a profoundly complex undertaking that involves a large number of interconnected elements and processes.
It can be incredibly challenging to gain the kinds of visibility and insights needed to understand what's going on in an automotive facility. Technologies like RTLS, RFID, IoT, and others can provide the kinds of information necessary for building a coherent view of material flow, production, utilization, and processes.
For developers and architects, it's important to think of ways to combine the power of connected physical assets with applications and AI that can process that data and extract meaningful information and actionable insights.
It's something of a chicken-and-egg scenario at first glance. To get value out of AI, there's a need for comprehensive data that reflects the physical world. There's also a need for systems that can capture that information and bring it into actionable formats. How does one begin?
That has a lot to do with the underlying nature of the application and infrastructure.
One of the main challenges involves understanding the interplay, relationship, and connection methods of IT and OT components in manufacturing facilities.
There are various systems, processes, objects, and elements, including manufacturing execution systems, enterprise systems, industrial equipment, sensors, and more. If such components are compartmentalized, there's very little value in having discrete islands of information.
It's only when they can be unified and brought together that applications and analytics have the potential to do their jobs. Developers tasked with delivering connected manufacturing applications and systems need to consider many of the same concepts and approaches as with traditional applications: connectivity, data flow and pipelines, interoperability, system integration, scalability, and more.
Visibility, Intelligence, Action
IoT provides and enables visibility.
AI takes that information, uses it to support intelligent applications that, in turn, can help operational teams gain valuable insights and take meaningful actions.
Organizations considering such an approach and looking for further inspiration or ideas for modernizing automotive manufacturing and connected systems and applications might want to explore OEMNex AI . It goes more in-depth into AIoT and connected automotive manufacturing use cases.
The bottom line is AIoT is a powerful concept that helps take modern applications and operational environments to the next level.
A lot of people think of IoT as simply being about adding more sensors and connecting them to some form of an AI engine.
That's certainly a part of it, but there's also a need to think of the larger end-to-end flow and infrastructure.
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