Condition monitoring coupled with a Predictive Maintenance strategy helps the Food & Beverage industry to optimise their labelling and other packaging operations. Today, several f & b industry professionals leverage the advantage of the Internet of Things (IoT) and AI-driven technologies to minimise unexpected downtime, reduce production wastage, and enable early detection of impending failures into the machines. If implemented correctly and to its full potential, there is so much that IoT and AI-powered devices can do to increase machine efficiency and productivity in your plants.
From monitoring the health of equipment to alerting the maintenance team about abnormalities in the machines, technology powered by Niruha Systems’ empowers industrial plants to run more efficiently, reduces maintenance costs, helps to better plan the maintenance strategy, increases machine uptime and provides real-time monitoring of the machines.
Harnessing Condition Monitoring into product labelling processes increases equipment reliability
As many already know the importance of condition monitoring, improved equipment reliability and uptime are two benefits that make your manufacturing plants more productive. Product labelling is an important part of any brand as it is their identity that differentiates them from their competitors. There are various labelling processes for various products.
Let’s take a look at the labelling process of plastic bottles.
The printers take the surface of the material to start the inking process. Various methods and inks are used to create the finished label. Then the printer starts its printing process. Once done, the label rolls are loaded onto the machinery, and the cutting and labelling process starts. It is often done with glue, a task done with precision after the bottles are filled and capped. Further, the label is cut precisely, ensuring that the correct length guidelines are followed and looks the right fit.
If the above labelling process is done incorrectly because of equipment misalignment, ragged cuts, shredded label material that may damage the equipment, the manufacturers might have to stop the production line. They might have to call for a maintenance team to fix the machines or detect the root cause to prevent future machine failures. But detecting failures manually can be a challenge in itself.
That’s where the deployment of Niruha Systems’ AI-powered BLE tags come into play for asset management.
Niruha Systems’ BLE product – cod enables the food & beverage industry to capture real-time mechanical data and provides vibration monitoring of temperature, humidity, shock and pressure of your critical equipment. It performs analysis on machine health and detects anomalies at an early stage.
Prominent benefits of BLE cod to ensure clean cuts and label variations
One of the most critical aspects of the labelling process is clean cuts. On average, if the machines are labelling more than 800 labels, the appointed personnel need to ensure that the machinery edge is sharp and the equipment is correctly aligned. Manual detection of faulty labelling can take a while before the inspection is done, and in that time, a pile of defective products are sitting in the waste line.
Similarly, what if the roll of material runs out? When you add the new one, you see the problems start to occur. Who do you blame? What caused the issue? The new roll or the old one, and why? Can manual inspection help you get the answers that you are looking for? No. However, compact-sized BLE cod can.
- It is an automative device that captures defects through sensors.
- Detects uneven label cut, lack of sharpness in the machinery, misalignment of the equipment, etc.
- Alerts are sent to the officials regarding unlabelled bottles and wear and tear of the materials
- Early diagnosis of the cutter drums that start to wear down because of consistently working for hours
- Every diagnosis is captured on the dashboard to ensure machine reliability and uptime
- cod will also alert you bad roll that increased vibrations in the equipment
- Enhances machine performance by providing prescriptive actions regarding the differences in the ink dye component.
Leveraging condition monitoring extended with predictive analytics in manufacturing plants can certainly help you produce quality products and increase machine uptime which then reduces maintenance costs! Be it any industry, Niruha Systems’ offers innovative industry solutions to you who want to transform conventional manufacturing plants into smart manufacturing plants!