Success stories
Predictive maintenance of cash
handling equipment at CashKeeper
Cashkeeper designs, manufactures and distributes equipment that handles cash payments. With the use of these systems, Cashkeeper’s customers are able to eliminate errors when balancing the till, avoid cashing errors, change, theft and the inclusion of counterfeit banknotes. Moreover, as the equipment is closed, there is no direct contact with coins and banknotes.
01. Challenge
To avoid this, a large number of corrective and preventivemaintenance actions were carried out. These increased costs significantly and were not efficient, as they performed tasks that the equipment did not always need and neglected other equipment that really required maintenance interventions.
The various components of these systems have a multitude of data and variables. So they sensed that these must be related to equipment failures, but they were not obvious.
Therefore, they contacted us as specialists in data analysis and Acció’s accredited advisors for Industry 4.0.
02. Solution
The system continuously captures equipment operating data (number of cycles, coin types, events, etc.) combined with other discrete data (type of establishment, its location, etc.). By using artificial intelligence algorithms, the system is able to predict the risk of breakage of the various components.
A responsive solution is available that shows the status of the equipment fleet at all times, and can provide information on the status of a specific component of a piece of equipment, as well as the level of risk of its failure.
This new system allows maintenance operators to know the real situation of all equipment and to plan their actions in order to avoid failures that limit their operation, providing significant advantages:
- Increased end-customer satisfaction, avoiding downtime and allowing you to see how your equipment is performing online.
- Cost reduction, avoiding visits and trips to teams that do not need them.
- Increased repair time in the first instance, as the operator knows in advance which component needs to be replaced.
- Analysis of business data, making it possible to establish relationships between types of establishment, types of coins and banknotes used, days of the week, etc.
03. Current scenario
The system is currently analysing close to 2,000 pieces of equipment and more than 6,000 components, significantly increasing the productivity of maintenance teams and reducing uncontrolled downtime.
It is envisaged to evolve the system to the next level, having not only predictive maintenance, but also prescriptive maintenance. It will be able to indicate, in addition to the risk of component failure, the best actions to be taken to increase component life.
