From digitalisation to predictive maintenance

Maintaining top efficiency levels on your packaging machine is vital to be able to rely on consistent and reliable performance over time.

The progress we made in our technical support offer goes hand in hand with the ongoing digitalisation process and the use of increasingly accurate data on the actual status and efficiency of each filling machine.

This has helped us introduce new services, enabling us to provide real-time remote assistance, and has already paved the way for bespoke maintenance.

In the long run, this will enable us to calculate with greater accuracy the useful life of components, significantly decrease both downtime and emergency maintenance operations, and eliminate unnecessary waste and costs.

Maintenance plays a key role in ensuring that the performance of your packaging machinery remains constant over time.

Relying on the industry expertise we have gathered over many years, we were able to develop Preventive Maintenance Plans (PMP) with detailed guidelines for scheduling interventions and replacements based on production hours.

We also created customised maintenance contracts so that our customers can personalise the level of After Sales support they wish to receive: from all-included maintenance packages to scheduled on-site visits by Galdi experts.

Digitalisation has also enabled us to introduce exclusive digital services such as MaSH, Galdi's advanced monitoring system, as well as real time remote assistance.

The goal we have been working on for some time is to provide personalised maintenance plans (PMP) based on actual component wear.

Software designed for this purpose is already at an advanced stage of development and is currently being used by our engineers to process data from various sources, including:

• Specific "meters" associated with the machine's critical components
• Technicians' activities on the machines (in the future customers will be able to actively report interventions)

Meter data is collected to get a precise measurement of the usage of single components (number of doses, caps or cartons packed).

With regular updates, the system integrates all meter and technician data. As a result, the algorithm can plan interventions based on the machine's actual conditions.

For instance, if according to your PMP, a given part is to be replaced after 1,000 hours, the software can delay or bring forward the intervention based on actual usage. On top of that, the software can group and suggest further operations to be conducted during the same intervention.

The result is truly personalised maintenance for the entire packaging line, with all the benefits this entails:

• Optimal use of a component's entire useful life.
• TCO reduction
• Better spare parts management
• Reduction in critical events requiring urgent repairs or replacements
• Increased production stability and high efficiency levels over time

Data is going to be the key in the future as well. The data gathered from single machines is already invaluable to:

• Optimise technicians' work, by tracking all machine activities
• Extract valuable data to improve the efficiency of both systems and maintenance operations (i.e.: part to be replaced within x number of hours).
• Improve design: operation data and technician reports help designers increase technical accuracy

With more data available and thanks to Machine Learning, predictive maintenance is the next step. We are getting there, by:

• Optimising sensors and creating predictive models (already completed)
• Analysing data and getting insights to refine systems (in progress)
• Implementing machine intelligence systems for adaptive and predictive maintenance (ultimate goal)

With predictive maintenance, intelligent and reliable packaging machines will be able to:

• Constantly self-monitor themselves
• Suggest timely interventions and replacements

The result? Consistent efficiency levels, maximum cost optimisation, and elimination of unforeseen events: intelligent packaging machines are indeed the future!