Production video analytics · Productive / non-productive time measurement

Director: “Our people work more than 60% of the time.”
We measured — 36%.

We measure productive and non-productive time on the shop floor: how employees and equipment work, assembly operations, waiting and any repetitive actions. We reveal losses and growth opportunities — before changes and after implementation.

First results
1–2 weeks
Shop floor
assembly, machines, lines
No capital expense
in infrastructure
measurement result
Real productivity
36%
at work. The rest is idle time, setup, waiting
Workshop No.3 · assembly area · shift 1
2:53work
3:20idle
1:00setup
0:47empty
2:53 of productive work out of an 8-hour shift = 36%.
Problem

It looks like production is running.

No one knows exactly how much time the shop floor actually works, where the minutes of a shift are lost, and how many of them are useful work versus waiting, idle time or supporting operations.

01
How much time the shop floor actually works
02
How long each operation takes
03
How much time is spent waiting between operations
04
Where time is productive and where it is non-productive
05
Where the hidden losses are within a shift
!
On the floor everyone says: “we’re working as usual.” But the plan slips, and exactly where time is lost stays invisible.
Solution

We measure — and show it in numbers.

Not consulting. Not an audit. A concrete measurement of what really happens on the floor — with video evidence for every minute of the shift.

01

Capture

We use the existing video surveillance system on the floor and, if needed, connect to signals from the equipment.

02

Labeling

We label operations: work, waiting, setup, movement, idle, supporting actions, operator absence.

03

Calculation

Productive and non-productive time, utilization, cycle time, recurring delays.

04

Report

Where the losses are, how big they are, what they translate into in money, and what specifically to improve first.

05

Before / After

Once changes are implemented — a repeat measurement with concrete figures for productivity growth.

Case study

Out of an 8-hour shift — only 2:53 of real work.

Assembly area, ~30 workstations, semi-automatic machines. Before the measurement, the production director was certain: “our employees work more than 60%.” The measurement showed — 36%. And the specific points of loss became immediately visible.

Every figure is backed by video — any minute can be reviewed again. This is not an “expert opinion,” but a measurement of fact.

Equipment utilization
2:53 / 8:00
0 h 36% 8 h
64%
of non-productive time
5:07
of losses within the shift
30
machines on the floor
Impact

Even +5% productivity is meaningful money in the very first month.

Example: a gas boiler assembly area, 20 employees. Move the slider — see how profit grows as productivity rises.

Additional profit
+660 000 ₽
per month · with the same resources
Per year that’s +7 920 000 ₽

Calculated without adding headcount, without new equipment, without building a new workshop. Purely through more efficient use of existing time and resources.

How we’re different

We don’t promise efficiency. We show losses in numbers.

Time study by a specialist Consulting / audit Equipment sensors DRPSoft · video analytics
Time to start weeks months months 1–2 weeks
Cost to start medium high very high low
Monitoring format one-off one-off continuous, but machine only continuous: people + equipment
Sees people and operations yes (sampled) yes (sampled) no — machine only yes (entire shift)
Sees equipment indirectly indirectly yes yes
Objectivity subjective expert opinion sensor data video evidence
Result in money no rarely indirectly immediately
Stages

The diagnostic is just the entry point. From there you can build out the system.

Each step is a separate, clear stage with a measurable result. There’s no need to commit to a full “transformation” right away.

Start
Stage 1

Productive / non-productive time measurement

Measuring productive and non-productive time on the floor.

Stage 2

Root-cause analytics

Why downtime occurs, what repeats, and where the systemic losses are.

Stage 3

Recommendations

Specific process changes with their expected impact.

Stage 4

Integration

Connection to ERP, 1C, BI — shop floor data feeds into the financial loop.

Stage 5

AI and supervisor assistant

Workload forecasting, a digital assistant for the shift supervisor, and real-time recommendations.

Where the impact shows

When the diagnostic delivers value fast

There’s manual labor: assembly, machine work, or operations without equipment

The worker influences pace, idle time, waiting, setup and supporting operations.

There are repetitive operations and shifts

You can compare areas, shifts and operations — and see where time is consistently lost.

There’s a sense of losses, but no exact numbers

There’s a plan and there are deviations, but it’s unclear what exactly eats up the shift and where to start improving.

Start with a single area

We’ll measure the time losses in your production process.

A free initial consultation. We’ll show how the measurement would look on your specific shop floor and propose a work plan with a clear result and timeline.

1
Request and call
We discuss the floor, the equipment, your goals and the way of working.
2
On-site visit and capture
We connect to the existing video surveillance system, record a shift, and label operations using our methodology.
3
Report in 1–2 weeks
Figures for every operation and workstation, a map of losses and growth opportunities — in money.