NAGARE AI brings production monitoring to the cameras already on your line. Measure cycle times, reveal brief stoppages and compare actual work with your standards, so teams can address lost time while the shift is still running.
Production monitoring should explain where time goes between the start and finish of a job. A slow handoff, repeated adjustment or short wait can disappear inside the shift average. By the time a supervisor investigates, the line has moved on and the evidence is gone.
NAGARE turns visible actions and station activity into a record of how work actually runs. Measure the cycle, compare it with the agreed standard and review the footage behind a delay, so improvement starts with a specific operation.
From a single work cell to comparable shifts, start with the measurements your team can act on. Each application uses the agreed camera coverage, event definitions and production context.
Measures how long each defined operation takes, so variation is visible beyond the shift average.
Turns visible work into timed activity evidence for reviewing methods and removing avoidable delays.
Flags short interruptions and waiting periods that can disappear from manual production logs.
Compares observed work with the agreed standard for the same product, operation and method.
Brings the agreed measurements together so teams can compare shifts and investigate recurring losses.
Start with the stations and losses that matter most. We check camera coverage, define what each event means and validate the timing against your process before the team relies on the dashboard.
Choose the stations, define cycle boundaries and check that the cameras can see the actions and handoffs you need to measure.
Use representative footage from your line. Agree the activity labels, timing thresholds, standards and product context with your production team.
Compare measured events with reviewed footage, confirm the dashboard definitions and establish how supervisors will investigate exceptions.
Bring your cycle targets and recurring delays. We will scope the measurements on your line.
Get In TouchPlatform benchmarks; outcomes depend on the application, baseline and deployment scope.
Manual studies, machine signals and video each reveal a different part of the process. Add visual evidence where the numbers need context, then use the same definitions to compare performance across shifts.
Production monitoring tracks how work progresses on a factory floor so teams can identify losses and compare actual performance with expectations. For this NAGARE application, the focus is visible work: cycle durations, idle periods and differences from agreed standards. Camera evidence helps a supervisor investigate an exception instead of relying only on a count or an end-of-shift explanation.
For a defined operation, cycle time measurement subtracts the recorded start timestamp from the finish timestamp. Keep those event boundaries consistent across repeated cycles. Cycle time analysis then examines the distribution, recurring delays and differences between comparable runs. A machine cycle, operator work sequence and complete line cycle are different measurements, so agree which one the dashboard represents.
Common tools include a stopwatch, observation sheet, process recording and time study software. A time and motion study combines duration with an examination of how the work is performed. NAGARE uses visible actions and station events to support that measurement. Engineers still define the method, validate the observations and decide which changes are practical for the production environment.
A video time study can provide evidence of an operation when the relevant actions and cycle boundaries are visible. Camera angle, lighting, frame rate and obstructions affect what can be measured reliably. During scoping, review representative footage from the actual station, including normal variation. Existing cameras are assessed for suitability before coverage and timing expectations are agreed.
No. Idle time monitoring shows when defined activity is absent; it does not establish the cause by itself. An operator may be waiting for material, a machine or a downstream handoff. Review the surrounding footage and production context before deciding on corrective action. The useful question is what prevented work from continuing and whether that interruption can be removed.
Micro-stoppage detection flags visible interruptions that meet an agreed duration and event definition. The shortest reliable interval depends on camera coverage, image quality, frame rate and the activity being measured. Validate the threshold on representative examples, including normal pauses and genuine interruptions. This avoids treating every brief movement change as lost production or overlooking recurring stops.
Standard time comparison needs a current reference for the same operation, product and working method. Compare equivalent cycle boundaries and account for agreed allowances, planned pauses and abnormal events. NAGARE supplies observed timing evidence; your engineering team owns the standard. Review any mismatch before changing a target, especially after tooling, material presentation or product variants change.
No. Production line monitoring through cameras adds evidence about visible work and delays. An MES also manages activities such as orders and execution records, while complete OEE requires agreed availability, performance and quality inputs. Define the data exchange during deployment. Camera observations can complement existing systems, but the page's scoped applications do not imply a complete MES replacement.
Useful shop floor analytics shows the agreed cycle durations, idle periods and deviations with station, shift and product context. A supervisor should be able to move from a recurring exception to the relevant evidence. Keep metric definitions consistent and show the observation period, so teams do not compare a short sample with a full shift or unlike operations.
Use production analytics to compare equivalent periods before and after the change, holding the product and operation definitions consistent. Review cycle variation and recurring interruptions alongside output and quality measures from the relevant systems. A faster observed operation is useful only if the improvement persists and does not move the delay elsewhere or introduce a new quality problem. Keep the original baseline and review the same observation window on each shift after the change.
NAGARE supports on-premises edge processing for manufacturing video analytics. Deployment starts with camera suitability, representative training footage and agreed event definitions. Configure access, retention and integration requirements with the team responsible for the site. The platform baseline is 120 minutes of training footage and a four-week deployment timeline; the final scope depends on the stations and operating conditions.
Bring your cycle targets and the delays your reports cannot explain. We will map how NAGARE can measure the work on your line.
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