Why Smart Factories Still Lose Millions to Micro-Delays

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Why Do Smart Factories Lose Millions to Micro-Delays?

Smart factories lose millions because small, repeated interruptions across machines, workflows, and decisions go unnoticed and unaddressed in real time. These second-level delays go unaddressed, and accumulate across thousands of production cycles, noticeably decrease output, efficiency, and profitability. Even with automation, IoT, and AI, most systems still don’t detect these second-level delays.

The Micro-Delay Problem: Small Pauses, Massive Impact

Micro-delays persist throughout production cycles as small interruptions, creating temporary breaks in production. For the most part, they go unnoticed as there are larger breakdowns in equipment that, when compared, create a much larger problem.

Cumulatively, these small delays can lead to significant impacts.A production cycle delay of 5 to 10 seconds is still small, but across thousands of cycles each day, can lead to a dramatic drop in output.

According to studies conducted at McKinsey and Company, small operational inefficiencies and micro-delays are a large contributor to about 30 percent of the lost manufacturing capacity around the globe.

Common examples of micro-delays in manufacturing include:

Machines waiting on raw materials or parts
Operators stopping to check production instructions
Minor adjustment of machines during production cycles
Delays in production quality inspections
Lag in data sync across the manufacturing systems

These delays won’t seem large on the surface, but repeated micro-delays over the production cycle will multiply, leading to significant loss in productivity and profit.

The Visibility Gap at Machine Level

Smart factories have limited visibility into operational activities on a machine level despite numerous advancements.

Most traditional manufacturing systems only provide a broad overview of the production process. They do not provide real-time machine processes and events like micro delays. Operational data is required to expose these granular inefficiencies.