Workplace Compliance

See where the shift actually went — without putting humans on the watching end.

Predco's computer vision turns shopfloor cameras into a productivity sensor: cycle time, dwell, idle pockets, line balance, and compliance gaps — measured continuously, without supervisor observation.

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Use caseWorkplace Compliance

Primary userProduction / IE teams

SensorsExisting CCTV

Time to live4–5 weeks

Replace with real photography for this page

Cycle accuracy ±0.8 s

Throughput +12%

01 / Why this matters

Industrial engineering can't measure what it never sees.

Time studies happen quarterly. Stopwatch-based observation is biased. Production losses get attributed to whichever cause is easiest to write down.

Stopwatch studies are sampled

A two-hour observation per station per quarter is statistically thin. The line drifts between studies — usually the wrong way.

Idle and dwell are invisible

Reports show 'production' or 'downtime'. The actual texture — micro-stops, balance loss, queue build — never surfaces.

Operators feel watched

Manual observation creates the wrong relationship. Productivity programs stall because of trust, not data.

Improvement attribution is fuzzy

After a kaizen, did throughput actually move? Without continuous baselines, the answer is opinion.

02 / How it works

Observe, measure, attribute, act.

Cameras become a continuous time-and-motion study — passive, anonymous, and 24/7.

STEP 01

Use existing line cameras

RTSP feeds from existing CCTV. No new hardware, no per-operator wearables.

STEP 02

Measure cycle, dwell, idle

Per-station, per-shift. Anonymous: counts events and durations, not individuals.

STEP 03

Surface bottlenecks

Line balance heatmaps, idle hot-spots, queue-length trends. Routed to the IE team daily.

STEP 04

Quantify every change

Every kaizen, every line rebalance — measured against a continuous baseline.

03 / Capabilities

An always-on industrial engineer.

Cycle-time measurement

Per-station cycle distribution, P50/P90/P99, drift over time.

Line balance heatmap

Spot stations starving downstream operations or building queues upstream.

Idle & micro-stop detection

Detect stops shorter than the MES threshold. The bulk of production loss lives here.

Headcount & coverage

Coverage vs plan per shift, per zone. Catch shift handover gaps.

Anonymity by design

Predco measures events and durations — not identities. Tuned for European works-council requirements.

MES & Andon integration

Push events back into MES, light Andon stacks, or Power BI.

04 / Integrates with

Industrial-engineering data, in the systems engineers already use.

Predco does not replace your MES, MOM, or ERP. It produces the high-resolution events those systems can't generate from PLC data alone.

Bi-directional MES integration (Wonderware, Rockwell FT, SAP DM)
Push events to Power BI, Tableau, Qlik
Andon stack light + MS Teams notifications
Anonymous by default — no facial identity
Works-council templates for German, French, Italian sites

Replace with: architecture / integration diagram

INTEGRATION MAP

05 / Outcomes

What customers measure

+12%

Throughput

Median across 22 deployed lines after 6 months.

−28%

Micro-stop minutes

Stops under 3 minutes are typically the biggest reclamation.

±0.8s

Cycle accuracy

Vs stopwatch validation across 1200+ cycles.

4 wks

First baseline

Production-grade baseline from sensor install.

06 / Standards & regulations

Built for the rulebooks you operate under

Out-of-the-box validation libraries for the standards manufacturers actually use.

GDPR Art. 22 (works councils)ISO 9001 — clause 9IATF 16949 — clause 9MTM-UASLean / Kaizen frameworks

07 / Powered by

The Predco products behind this solution

Available for new deployments — Q2 2026

Optimize. Predict. Prevent. Comply.

Bring AI-powered compliance to your manufacturing operations. A 30-minute call with our team — no slideware, just a working walkthrough.

Get started Talk to sales

4 hrs

Avg response time

6 wks

From kickoff to live pilot

SOC 2

Enterprise security posture