OEE software for Zambian plants — because "shift production off-peak" is meaningless without production data.
Copperbelt industrial users have been told to move production away from peak hours while ZESCO runs an eight-hour daily load-shedding schedule. That instruction assumes something most Zambian plants don't have: a reliable, hour-by-hour record of what each line actually produces, and what stops it. addanode puts live OEE — availability, performance and quality — with reason-coded downtime on your lines, including old machines with no digital output, and keeps recording straight through the outage.
Losses that get paid for every shift, and counted by nobody.
The stop nobody logged
A mill or filling line stops for twenty minutes. Someone fixes it, nobody writes it down, and by month-end the shortfall is explained as "a difficult month". Reason-coded downtime turns each stop into a record — duration, cause, line, shift — so the ranked list of what's actually costing you exists before the argument does.
Restart losses after every outage
With shedding running daily, a plant restarts far more often than it used to. Warm-up scrap, re-sterilisation, re-priming, product left in the line — each restart has a cost, and it repeats. Measuring it is the only way to know whether a genset, a buffer tank or a schedule change is the cheaper answer.
Changeovers guessed rather than timed
Short runs and frequent SKU changes are normal in Zambian food, beverage and packaging plants. When changeover time is a folklore number rather than a measured distribution, nobody can tell an improvement from a good day.
Four constraints we design around, not apologise for.
- Load shedding is the operating condition. ZESCO publishes eight-hour daily load-shedding schedules, and hydrology sets the relief. Our gateways are battery-buffered and log locally, so the OEE record covers the outage instead of stopping at it — and "how much did shedding cost us this month" becomes a figure rather than a feeling.
- Old machines are the majority. Most lines in Lusaka and on the Copperbelt include machines with no digital output. We read them anyway — sensors on the machine (proximity, current, photo-eye) produce genuine counts and stop events without touching the controller, and without a PLC upgrade project.
- Energy and production belong on the same picture. Zambia's electricity is the country's central industrial constraint. Once tonnage and kWh are on one platform, energy per unit produced stops being an annual estimate — the structural version of that argument is on our energy cost per tonne page, and the diesel side on generator monitoring.
- Kwacha budgets, staged scope. Deployments start with one line — the one where a stop hurts most — and extend once the first line has paid for itself. Cost bands in writing after a remote assessment; no enterprise MES licence to justify before you have any data at all.
How a first project runs: An architecture proven across Southern Africa, hardware pre-configured in Johannesburg, installation by your own electricians or contractors under live remote guidance from engineers in your time zone, and a written scope before anything is ordered. We put a number on the improvement after we've seen your stops — that figure is only worth having when it's yours.
From paper log to live OEE on one line.
1 · Pick the line that hurts
Usually the bottleneck, or the one whose stops ripple furthest. One line is enough to prove or disprove the whole idea.
2 · Count and sense
Read the PLC where one exists; add counting and state sensors where it doesn't. An operator terminal captures the reason for each stop — in the words your team actually uses.
3 · Run one month, then argue
A month of reason-coded data settles what a year of meetings couldn't. The Pareto of stops tells you where maintenance, spares and changeover work should go first.
Runs on the addaNet industrial IoT platform, alongside condition monitoring on the rotating assets that carry production. First line typically live in 2–6 weeks.
Zambian production environments — where the points go missing
| Environment | Dominant loss | First thing to instrument |
|---|---|---|
| Brewing and bottling (named client in this sector) | Micro-stops; outage restarts | Counts + run state at the filler; mains presence |
| Cement and lime | Rate below design; rare, expensive stops | Rate + kiln/mill vibration + energy per tonne |
| Sugar, grain and feed mills | Campaign-season downtime | Mill-train vibration + drier temperatures |
| FMCG and plastics | Changeovers, cycle-time creep | Cycle time per machine; genset load |
| Copper processing | Power-event losses | Mains + genset + tonnes on one record |
Where OEE lands first in Zambian manufacturing.
Milling & food processing
Maize mills, stock feed and food plants around Lusaka — throughput per hour, downtime by cause, energy per tonne of product.
Beverage & packaging
Filling and packing lines where changeovers and short runs dominate the loss profile.
Copperbelt engineering & fabrication
Job shops and mine-supply fabricators in Kitwe and Ndola — machine utilisation and job progress instead of clipboard estimates.
Building materials
Cement, blocks and steel products — batch counts, plant availability and the cost of each unplanned stop.
Agro-processing
Sugar, oilseed and grain handling — line rate against design capacity, and where the gap actually opens.
Mineral processing plants
Where the "line" is a circuit: throughput, availability and stoppage causes on mills and crushers, paired with condition monitoring.
OEE software in Zambia — common questions
What is OEE, in plain terms?
Overall Equipment Effectiveness multiplies three ratios: availability (was the machine running when it should have been), performance (was it running at rate) and quality (was the output good first time). One number that hides nothing — a plant that looks busy but scores 45% is telling you where more than half its capacity went.
Can we measure OEE on machines with no PLC?
Yes — this is the normal case in Zambia, not the exception. Counting and state sensors mounted on the machine produce real counts and stop events without touching the controller, and an operator terminal captures the reason for each stop. No controller replacement, no vendor software licence for equipment built decades ago.
Does OEE monitoring survive load shedding?
It is designed for it. Gateways run on battery buffer and log locally through the outage, then back-fill when power returns — so a shedding window appears in the record as measured downtime with a known cause, rather than as a hole in the data. That distinction is what lets you quantify what shedding costs you.
How do we use OEE data to shift production off-peak?
By knowing your hourly output profile and your restart cost. Once you can see production per hour, per line, and what each restart actually costs in scrap and warm-up, moving a run becomes an arithmetic decision rather than a gamble — including the honest case where shifting a particular process costs more than it saves.
What does OEE software cost in Zambia?
Entry deployments cover one line and are quoted as a written cost band after a free remote assessment of your equipment list. Starting from the sensors and controllers you already own keeps the hardware component down. We quote in writing before anything is ordered.
Will you promise us a specific OEE improvement?
No. Anyone quoting you a percentage before seeing your stops is selling, not engineering. What we will commit to is that after one month you will have a ranked, evidence-backed list of what is costing you capacity — and that list is what improvement is built from.
Put a number on every stop in your Zambian plant.
Tell an engineer what you run and how shedding is hitting it. We'll tell you which line to measure first — and whether it pays back.