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Take your favourite sport—hockey, soccer, baseball. A contentious goal or run is scored. Officials go upstairs to for a review of the play to decide if it will count. What will provide the strongest evidence to support their decision—a video instant replay or snapshots of a few isolated points in time?

It’s the replay, of course. Your production line can deliver this same level of actionable insight, with digital process signature analysis (also known as waveform analysis).

What is a digital process signature?

A signature is a visual representation of everything that happened to a part during a manufacturing operation. Every very process has a repeatable signature or digital “fingerprint” when compliant and under control.

Signatures are created from data collected by sensors such as load-cells, temperature, position and pressure sensors, microphones or displacement gauges at the station. The signals can be physical measurements or computed values such as horsepower or efficiency based on specific measurements and mathematical formulae. 

The digital traces represent hundreds or thousands of data points which are used at the station to provide a much more accurate pass/fail decision. The rich data is collected and can later be mined to resolve issues quickly or optimize production. Sciemetric pioneered digital signatures for use in manufacturing in the 1990s and remain at the forefront of innovation in the technology in industrial applications.

Sample digital process signature


What you can learn from a digital process signature

What can a signature tell you? Take press-fit monitoring, a common manufacturing operation, for example.

Digital signatures visualize as a waveform that combines force vs. time and distance vs. time measurements. This casts a spotlight on a number of possible issues with a part, as well as issues with the process or the machine. Any of these could result in a flawed pressing operation that leads to downstream defects.

Press defects

Catch what other test and monitoring systems miss

Digital signature technology provides the most accurate measurement at the station level to provide a picture of part and process health.

Waveform image showing good and bad parts
1: Repeatable waveforms of a healthy process producing good parts.
2: Obvious failures caught by any system.
3: Subtle failures that are missed by other systems because they meet the minimum criteria for a "pass".
These anomalies can point to process issues and/or problems with parts down the line.

Scalar data tells only part of the story

Most manufacturing data management systems collect scalar data only, limited to a few data points for each cycle of a manufacturing process or test—a handful of snapshots. This is sufficient to monitor and track the health of a production line or provide baseline traceability. But when problems arise, it just isn’t enough to quickly find and address root cause.

For Industry 4.0, front-line quality and manufacturing engineers and operators need the right data to helps them resolve issues quickly—increasing yield, cut scrap and rework rates, improve station performance, reduce downtime due to defects, etc.

Read this blog, SPC Can Catch a Problem, But Only Signature Analysis Can Fix It Fast, to learn more.

How does digital process signature analysis
help manufacturing?

Sciemetric is the only company that enables in-depth analysis and visualization of digital process signatures in manufacturing, in real-time. Our analytics tools allow users to overlay and compare digital signatures in large or small populations—from thousands of parts right down to a single part history.

According to our customers, it’s the fastest way to access and view complex data to:

  • Provide Traceability: Quickly determine the “how” and “why” of any issue that is affecting quality or compliance with customer requirements or regulatory standards.
  • Trace Root Cause: Dramatically improve defect avoidance and contain defects for a fraction of the cost of a day of lost production.
  • Improve Quality: Isolate potentially defective products by serial or batch numbers based on specific process signature symptoms, or on desired build parameters.
  • Increase Output: Overcome barriers to increased output, whether it’s related to unexpected downtime, poor FTY/FPY/FTT, or test stations that need to be optimized to keep pace with production.
  • Speed Runoff: Diagnose and address issues with calibration, alignment, pressure, angle and other parameters, to launch new machines and new lines faster.

Read our e-book, How to Put Your Manufacturing Data to Work.

E-book cover


Richard Brine CTO

Watch Sciemetric CTO Richard Brine explain how manufacturers can use signature analysis to improve leak testing and more in this video segment with Quality Digest Live