Measure and control: from contactless to AI

Themes such as hygiene, speed and flexibility play an important role when it comes to efficient and reliable production in the food industry. Measurement and control technology supports the corresponding processes in the various phases of production in this regard. Contactless, safe and sometimes using the possibilities offered by the current generation of AI technology.

Measurement and control technology is a field that has long played a distinctive role when it comes to reliable, efficient and, above all, safe production. Also in the food industry. In doing so, measurement instrumentation collects the various relevant process data used by control engineering to steer these processes in the right direction. In the food industry, measuring and controlling correctly means the difference between a perfect and failed product. After all, both the right (quantities of) ingredients and, for example, process pressures and temperatures determine the quality of the final product.

Typical process parameters

Within the food industry, parameters such as pressure, temperature, level, flow, time and weight are measured during production. During quality control, color recognition and dimensions, among others, are added, while in the packaging phase, location, speed and presence are especially important.

All this data is read in by a controller and processed for subsequent steering or adjustment. In the latter case, feedback is used to ensure that processes continue to run smoothly despite small variations in ingredients, for example.

Based on the measurement data and control algorithms, valves and valves, among other things, are controlled to allow the correct amount of a particular medium or ingredient to pass through. The PLC also controls elements such as mixers, conveyors, oven heating elements or pick & place devices. When it comes to quality control, vision is an increasingly used technology because it allows non-contact recording of various characteristics ranging from dimensions and numbers to color, gloss level or the location of details.

Developments in measurement technology

One of the main differences between the food and "mainstream" industries is the high hygiene requirements. This also has an impact on measurement instrumentation for the food industry. On the one hand, these must withstand sometimes extremes such as high temperatures, acidic media or aggressive cleaning agents. On the other hand, they must not cause contamination in any way when measuring in or at the process.

One solution to combat contamination is to use non-contact measurement techniques such as radar or light. These types of measuring instruments are mainly used to measure levels, distances or presence. Non-contact measurements can also be carried out to check whether there are, for example, iron particles in the food - in order to then take measures. Depending on the application, the data from the measuring instruments is sent contactless or via well-known industrial bus systems such as IO-Link.

Control technology developments

When it comes to developments in control technology, the speed of data processing is particularly striking. Controllers are able to simultaneously process more and more data at an ever faster rate. This can contribute to higher accuracy, higher flexibility but also higher speed of production processes. The same applies to the pre-process phase in which food is prepared and to the packaging phase.

Relatively new is the application of AI especially in inspection processes. An important advantage is that it can eliminate manual inspection, which is cheaper. In addition, AI is often more accurate and does not suffer from fatigue or loss of concentration, allowing inspections to be carried out flawlessly and at breakneck speed. The data generated can also be used to optimize processes. For example, this data can indicate that there is more rejection when a certain operator stands by the machine or when there is a change of supplier. Or vice versa: on the contrary, less rejects after performing maintenance, reducing the speed of the packing machine, and so on. In this regard, the possibilities of data collection and analysis are not yet fully developed.