Toyota’s estimate that factory automation could require 400,000 robots puts the scale of manufacturing’s next chapter into perspective. It also raises a question every manufacturer should be asking: How will all of that intelligence work together?

The challenge is, an individual machine’s success does not automatically translate into a better-running factory. A robot can execute its task perfectly but still contribute to a production bottleneck, or be impacted by another robot’s poor task-execution or malfunction. In terms of factory work, moving parts more quickly doesn’t expedite the process if the next station cannot accept them.

That’s why context is key. A robot needs information about the conditions affecting its work: equipment availability, material flow, quality requirements and changing production priorities. Without that context, manufacturers risk recreating familiar automation silos with much more sophisticated technology.

However, that orchestration is only the starting point. When machines share data, they also need to share an understanding of what that data means for production. A signal that a station has stopped should inform decisions upstream and downstream, rather than remain trapped inside one application.

Manufacturers should build those connections into their automation plans from the very start. Defining the production goal, identifying  which systems need to share information, and establishing how people and machines should respond when conditions change deserves just as much attention as selecting the robot itself.

For every deployment, manufacturers must ask the practical question: If this machine encounters a delay, who needs to know, and what should happen next?

The opportunity ahead is enormous, and realizing it will require intelligence that reaches beyond individual tasks. The true measure of progress is whether the whole factory performs better.

Tim Juan, NEXCOM IoT automation solution head