Manufacturing Automation
Software around your existing plant, not a machinery replacement programme.
What is manufacturing automation?
Manufacturing automation in this sense means the software layer around production, recording output and downtime as it happens, tracking material consumption, capturing quality checks and producing the numbers a plant manager needs, without replacing machinery.
Manufacturing automation usually means robots and new machinery. That is a capital project with a long payback, and it is not what most Kenyan manufacturers need first.
The cheaper gap is information. Production is recorded on a clipboard, downtime is remembered rather than logged, and by the time a shift summary reaches a manager the reasons have blurred into everybody being busy.
Capturing what actually happened on the line, as it happens, costs a fraction of new plant and usually reveals that the constraint is not the machine anybody assumed.
Why your equipment budget is not our concern
Duara builds the software layer around production from Nairobi for food processors, packaging plants, light assembly and general manufacturing.
We do not sell machinery and we have no interest in whether you buy any. That matters because the honest answer is often that your bottleneck is changeover time or material availability rather than machine speed, and nobody selling equipment is well placed to tell you that.
Who this is for
- Production is recorded on paper
- Downtime reasons are remembered, not logged
- Nobody knows real output per shift until later
- Material variance is discovered at stock take
Industries we serve
- Food and beverage processing
- Packaging
- Plastics and moulding
- Light assembly
- Textiles and garments
- Building materials
Problems this solves
These are measurement gaps, and they are why plant decisions get made on impression rather than evidence.
- Production recorded on paper. Output is written on a clipboard and entered later, so nobody knows the real figure until the following day.
- Downtime reasons lost. A stoppage is remembered vaguely by the end of the shift, which makes the pattern invisible and the cause unfixable.
- Material variance found late. Consumption against standard is discovered at stock take, weeks after the batch that caused it.
- Quality checks on paper. Checks are recorded in a book nobody analyses, so a drift toward the limit is only noticed once it crosses.
What we deliver
Output and downtime captured at the line as they happen, material consumption tracked per batch, quality checks recorded digitally, and shift reporting produced without anybody assembling it.
Output recorded at the line as it happens
Downtime logged with its reason at the time
Material consumption tracked per batch
Quality checks captured digitally with limits
Shift reports produced automatically
Reporting on where production time actually goes
Features
- Capture at the line. Recording happens where the work does, because a figure written up later has already lost the detail that mattered.
- Downtime reasons at the moment. The reason is captured when the machine stops, which is the only point at which it is accurate.
- Batch level material tracking. Consumption against standard per batch, so variance is visible in hours rather than at stock take.
- Quality trends, not just pass and fail. Recorded measurements show drift toward a limit before it is breached.
- No machinery required. This runs on tablets and existing counters. Where a machine can be read directly we do that, and where it cannot we do not pretend otherwise.
Benefits
- The real constraint becomes visible. Downtime data usually shows the bottleneck is changeover or material rather than the machine everybody blamed.
- Variance is caught in hours. Material problems surface while the batch is still traceable rather than at the next count.
- Quality problems get predicted. A measurement drifting toward a limit is a warning; a failed check is already scrap.
- Shift reporting stops costing time. Reports arrive assembled, and they are based on what was recorded rather than what was recalled.
Technologies we use
- Line side capture. Tablet or terminal recording of output, downtime and checks at the point of work.
- Machine reading where possible. Taking counts directly from equipment that exposes them, rather than asking an operator to retype.
- Downtime coding. A short structured reason list, kept deliberately brief so it is actually used.
- Material consumption tracking. Recording issue and usage per batch against the standard recipe or bill of materials.
- Shift and OEE reporting. Producing availability, performance and quality figures from recorded events.
Operators decide whether this works. A capture step that adds thirty seconds to a cycle will be worked around, so the interface has to be faster than the clipboard it replaces.
How the process works, step by step
Manufacturing automation usually takes six to ten weeks, and it goes live on one line before anywhere else.
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Step 1
Free plant review
We look at how production and downtime are recorded now and what the numbers are used for.
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Step 2
One line first
A single line proves the capture design, because an interface operators reject is the failure mode that matters.
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Step 3
Downtime codes agreed
The reason list is built with supervisors and kept short, since a long list gets answered with the first option.
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Step 4
Capture running
Operators record at the line, and we watch how long it actually adds to a cycle.
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Step 5
Extended and reported
Other lines follow, and shift and OEE reporting is switched on once the data is complete.
Quality assurance and how we work
The commitments attached to putting recording into a production environment.
- We do not sell machinery. Our answer is often that the bottleneck is changeover or material rather than machine speed, and nobody selling equipment is well placed to say that.
- Capture must be faster than the clipboard. A step that adds thirty seconds to a cycle gets worked around, and we measure the added time rather than assuming.
- We start on one line. Rolling across a plant before operators have accepted the interface produces a system everybody bypasses.
- Downtime codes stay short. A long reason list gets answered with whatever is first, which produces data that looks complete and means nothing.
- We report what the data says about management. Where downtime is caused by planning or material supply rather than the line, the reporting shows it.
Frequently asked questions about manufacturing automation
Is this about buying robots?
No. This is the software layer around your existing plant. Machinery is a capital project with a long payback and it is rarely what is needed first.
Do you sell equipment?
No, and that matters. Our answer is often that your bottleneck is changeover or material rather than machine speed.
What hardware do we need?
Tablets or terminals at the line. Where a machine exposes its counts we read them directly, and where it cannot we say so.
Will operators actually use it?
Only if it is faster than the clipboard, which is why we measure the time it adds to a cycle rather than assuming it is negligible.
What if operators reject it?
That is the failure mode that matters, which is why we prove the design on one line before going near the rest of the plant.
Why keep the downtime code list short?
Because a long list gets answered with whatever is first, producing data that looks complete and means nothing.
Can it calculate OEE?
Yes, from recorded events rather than estimates, which is usually the first time the figure is trustworthy.
Does it track material usage?
Per batch against your bill of materials, so variance shows up in hours rather than at the next stock take.
Can it record quality checks?
Yes, with measurements rather than just pass and fail, so drift toward a limit is visible before it is breached.
Will it connect to our machines?
Where they expose data, yes. Plenty of older equipment does not, and we are direct about that rather than promising a retrofit.
How long before one line is live?
Six to ten weeks, with the first line proving the capture design before anything is extended.
Will production data reach our ERP?
Yes, feeding output and consumption into your existing system rather than creating a separate record beside it.
Can it handle several shifts?
Yes, with reporting by shift, which frequently shows differences nobody had quantified.
Will it show which line performs best?
Yes, on the same measures, though we would caution that comparing lines running different products needs care.
Does it help with traceability?
Yes, batch level material and output records support recall traceability, which matters most in food and pharmaceutical work.
What about maintenance?
Downtime data feeds it, and recurring stoppages on one machine are usually the clearest maintenance signal available.
Is this AI?
Very little of it. Recording and calculating have right answers, and rules are what you want on a production line.
Can supervisors change the codes?
Yes. The reason list is yours to maintain, and it should be revisited as the plant changes.
Who owns the production data?
You do. It stays in your systems, is not exported to us, and trains no public AI model.
What does manufacturing automation cost?
Line count and hardware needs determine it, quoted after the plant review.
Glossary of terms
Production terms in plain language.
- OEE
- Overall Equipment Effectiveness, combining availability, performance and quality into one figure.
- Downtime code
- The short structured reason recorded when production stops.
- Changeover
- The time to switch a line from one product to another, frequently the real constraint.
- Yield
- Good output as a proportion of material consumed.
- Bill of materials
- The standard list of inputs required to make one unit of a product.
- Variance
- The difference between standard and actual material consumption.
Related services in Automation
Talk to us about manufacturing automation
Ask your plant manager for last week downtime by reason. If the answer is an estimate, this is the gap.
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