Process Drift Analysis

See how work is performed, identify meaningful process variations and discover which methods produce the best outcomes.

Understand How Work Is Performed

Detect Process Drift

Identify when execution departs from expected, historical, or best-performing patterns, including skipped, reordered, and repeated steps.

Compare Execution Patterns

Reveal how the same processes differ across cycles, shifts, lines, products, and facilities.

Separate Helpful from Harmful Variation

Determine which execution patterns improve or negatively affect quality, rework, cycle time, throughput, and safety.

Strengthen Standard Work

Turn proven process patterns into better SOPs, targeted reinforcement, and scalable best practices.

See How Work Varies. Standardize What Works.

FAQ: Process Drift Analysis

What is Process Drift Analysis?

Process Drift Analysis uses AI and vision intelligence to understand how manufacturing processes are performed and identify variations such as skipped steps, sequence changes, repeated actions and additional motions.


Is every deviation a problem?

No. Some variations may create risk, while others may represent a better method. DeepHow helps connect variations with manufacturing outcomes to determine which patterns should be corrected or standardized.


How can Process Drift Analysis improve quality?

It can connect execution patterns with defects, rework, inspection results and first-pass yield to identify process variations associated with quality outcomes.

Can it help improve SOPs? 

Yes. Manufacturers can use observed execution patterns to determine whether existing SOPs reflect the safest, most efficient and most reliable way to perform the work.


How is it different from Live SOP Verification?

Live SOP Verification provides immediate feedback while work is being performed. Process Drift Analysis examines execution patterns over time to identify drift, compare methods and improve the standard itself.


Find the Process That Produces the Best Outcome

Understand process variation, improve standard work and scale proven methods across your operations.

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