Manufacturing
& food.
Manufacturing & food
In manufacturing the starting point is comfortable and misleading at the same time: there is a huge amount of data. Instrumented machines, production reports, batch and waste records. What is almost always missing is the translation into money.
A plant knows how many times a line stopped last month, and yet it does not know what each of those stoppages cost. It knows how much waste it had, but not which product is eating the margin. It has the full breakdown history in the maintenance system, and it still services machines by the calendar rather than by their actual condition.
The result is that the decisions that move the most money rest on the experience of whoever has spent twenty years on the plant floor. When to stop for maintenance, which product to stop making, which supplier is costing more than it seems. That experience is valuable and cannot be replaced. What matters is backing that experience with up-to-date information.
All three rely on data the plant is already recording today, without installing a single new sensor.
A model built on the breakdown history, the running hours and the signals already being recorded. It ranks interventions by real risk rather than by date, and the calendar stops being in charge.
Matching plant reports against product, shift and material cost, so that every stoppage and every unit of waste has a price next to it. It is the project that turns production meetings into decisions.
Pulling together the batch trail that today is split between the ERP, the plant and paper, and making it searchable on the spot. It stops being a manual reconstruction every time someone asks.
Four steps, and the work is not in collecting the data. It is in agreeing what an hour of stopped line is worth.
Not ‘a plant dashboard’, but the stoppages on one line during a month that has already closed. A scope that production recognises on sight, because they lived through it.
Whether the stoppage is logged by the machine or noted by the operator at the end of the shift, and whether the reason comes from a fixed list or a free-text field. That decides whether the data can be grouped.
That number is not measured: it is decided, and production and finance decide it together. Without that prior agreement, each department reads the same report with a different figure.
With the history of stoppages and breakdowns already costed, condition-based maintenance and demand forecasting have something to feed on. Without the cost next to it, a model can be right and still change no decision.
All seven, in the order they usually come into a plant. Here the first four are the quick ones, because the data is already recorded and nobody has to go looking for it.
Stoppages, waste and energy use with a price next to them, by line and by product. It is the fastest project in the industry, because there is no data to go looking for.
See the product
Maintenance ranked by real risk rather than by the calendar, and demand anticipated by product. It is built on the breakdown history that is already in the system.
See the product
Plant, ERP and warehouse talking to each other, which is what it takes to pull up a batch's traceability on the spot instead of rebuilding it by hand.
See the product
Restocking raw materials, placing the supplier order and preparing the production close, with the rules agreed and a person authorising whatever falls outside them.
See the product
Technical data sheets, line procedures, quality plans and HACCP records you can question with citations, so the night shift does not depend on who they can phone.
See the product
Incident reports, spare-part orders and supplier claims handled end to end. Today it is admin work done by people on the plant floor.
See the product
The upfront assessment when there are several plants and each one records things its own way, to decide which to start with and with which number.
See the productAlmost never to start with. Most plants already record far more than they use: production reports, the maintenance system, the ERP and often the line's own PLC. The first project is done with that. If something specific needs instrumenting later, it is decided with the number in front of you, not before.
Two things change, and both matter: shelf life and traceability. In food, the batch is not just a quality record; it is a legal obligation. And waste has a shelf-life component that other industries do not have. The projects take the same form, but AI in food manufacturing has to carry the product's shelf life inside the calculation.
It will if it has dates and causes. To rank maintenance by risk you need the history of what broke, when and on which machine. The format matters less than you would think. A history where the cause was only recorded some of the time will not do.
It overlaps, but the name usually comes with a much bigger project: instrument the whole plant, connect everything and build the platform before seeing any result. We prefer the opposite order, and in this industry it is possible. One specific process, measured in money, using what is already recorded.
Someone from the plant and someone from finance or management accounting, and the second is usually the one missing. The project is about bringing physical data together with cost data, and those two live in departments that rarely meet.
It depends on the state of the data, not the industry, and in manufacturing the data is usually in good shape. What we do agree before starting is which number has to move: the cost of a stoppage, waste by product, margin by product. Without that agreement, the end of the project becomes an argument about opinions.
With one, and with the one that records best, not the one in the worst shape. The temptation is to fix the struggling plant first; the problem is that there the project turns into an instrumentation job and takes three times as long to show a number. With one plant working and the calculation already agreed, extending it to the others is a matter of connection and shared vocabulary, not of starting from scratch.
