Time Study Line Balancing and Kaizen Validation

Automates time studies and before-after validation so industrial engineers can prioritize and scale Kaizen work.

Time Study Line Balancing and Kaizen Validation
Headquarters
United States
Deployment
On-Premises, Edge/Local
Services
Installation, Managed Service, Support & Maintenance

How it works

Sense
Edge cameras continuously categorize work, wait, pick, walk, stand, unknown, sequence, cycle duration, product, station, shift, outlier, and contextual video evidence.
Connect
Installed 3D cameras process and store video locally at the edge and can integrate PLC and MES records; no universal field transport is published.
Analyze
The application compares every cycle with configured standards and golden examples, finds bottlenecks and micro-stops, supports line balancing.
Act
Prioritize Kaizen projects, redesign layouts and material flow, balance work, validate changes across shifts, standardize gains, and detect regression.

Why teams choose it

Vision data capture
Supported data exchange
Operational analytics
Operational response

About Time Study Line Balancing and Kaizen Validation

Operators responsible for assembly stations, operators, work sequences, walking paths, cycle categories, product numbers, shifts, standard work, layouts, industrial engineers, and improvement projects cannot continuously inspect every operating condition or developing fault. Periodic checks leave gaps between readings, while isolated local indicators provide limited history and context. A late response can cause downtime, safety exposure, equipment damage, or incomplete compliance evidence. Teams need timely measurements, clear exceptions, and a defined operating response.

Time Study Line Balancing and Kaizen Validation combines connected field data with application software. Edge cameras continuously categorize work, wait, pick, walk, stand, unknown, sequence, cycle duration, product, station, shift, outlier, and contextual video evidence. The application compares every cycle with configured standards and golden examples, finds bottlenecks and micro-stops, supports line balancing. Prioritize Kaizen projects, redesign layouts and material flow, balance work, validate changes across shifts, standardize gains, and detect regression.

Cost estimate

1 site, 10 assets, United States
$2,600 – $8,700
$700 – $2,400
Estimated first year, by component
$1,000 – $3,300$900 – $3,000$700 – $2,400
Hardware$1,000 – $3,300

Sensors, gateways and spare units

Installation and setup$900 – $3,000

Site survey, mounting, commissioning and configuration

Software and services, 12 months$700 – $2,400

Platform subscription, connectivity, data and support

This is an estimate by IoT Apps based on comparable deployments, not a quote from Invisible AI.
Get an estimate for your own project and invite Invisible AI to confirm a price and lead time, on this page.

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Questions and answers

What does a deployment cost?

For 1 site with 10 monitored assets in United States, IoT Apps estimates $2,600 – $8,700 in the first year and $700 – $2,400 every year after. This is an estimate based on comparable deployments, not a quote from Invisible AI.

VendorInvisible AI, United States
IndustryIndustrial & Manufacturing, Manufacturing
Use casesProcess Optimization, Condition Monitoring
DeploymentOn-Premises, Edge/Local
ServicesInstallation, Managed Service, Support & Maintenance, Data Analytics, Software Platform, System Integration
Available inUnited States

Uses this hardware

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IoT Apps is an independent platform. Listings do not imply endorsement by or partnership with the vendor. Estimates are indicative and based on comparable deployments, not on vendor quotes.