Predictive maintenance is a system of remote connections that:
- makes us of artificial intelligence (AI) functionalities;
- is based on IOT Analytics, i.e. the analysis of the data generated by the network;
- uses specific software called “CMMS” – “Computerized Maintenance Management System”.
Predictive maintenance is mainly used to manage maintenance activities of plant and machinery and/or to diagnose imminent failures of plant or machinery and/or to detect the need to replace components.
Predictive maintenance allows both to reduce downtime and all those inconveniences caused by machine downtime, and to improve safety within the company.
How predictive maintenance works
Maintenance interventions are carried out through a connectivity platform, usually owned by the supplier of the plant/ machinery, by means of which the supplier accesses, controls, monitors, manages and performs technical assistance remotely using devices of any type, from laptops to smartphones.
Through such connectivity platform it is possible to remotely connect to instruments which are very heterogeneous both in terms of hardware and software, such as sensors, valves, buttons and data analysis algorithms, which interact with each other according to the logic of the Internet of Things.
The data provided by the sensors located on the machinery or on the plant line are processed by predictive algorithms of specific software that make it possible:
- to “predict” a fault;
- to intervene before it occurs;
- to carry out remote maintenance interventions, reducing machine downtime and the related costs.
The benefits of predictive maintenance
The predictive systems are able not only to detect and manage monitoring data, but also to learn from the past and experience through “machine learning” algorithms. In this way, the predictive algorithm of the artificial intelligence self-learns and continuously improves its ability to assess data and parameters which are sensitive for maintenance, making the predictive maintenance increasingly accurate and timely and reducing the number of interventions and the related costs of the maintenance department for the user of the plant or machinery.
More precisely, the benefits of the predictive maintenance systems consist in the reduction of labour costs related to the maintenance; in the reduction of production downtime; and in the reduction of the costs related to replacement of the machinery. Predictive maintenance also improves the worker safety conditions, with the reduction of the risk of accidents and a better regulatory compliance. Just as it allows the supplier to sell a maintenance service alongside the machinery or plant.
The responsibilities connected with the use of predictive maintenance and the protections to be adopted
But such a digitalization of the business processes entails wide responsibilities of both the supplier and the user of the machinery, which must be supported with the adoption of policies appropriate to, and consistent with, the laws and regulations in force.
First of all, it is necessary to introduce, within the companies, appropriate regulations on the use of these technologies, with implementation of all the security measures aimed at avoiding the risk of data theft, serious liability and heavy sanctions.
In addition, the acquisition, the knowledge and the management of a large quantity of data, by the supplier, to organize and calibrate the maintenance interventions mean that the same:
- will become aware of the data relating to the production processes and the sales volumes, with the associated implications with regards to civil and fiscal liability;
- will adopt decisions on the maintenance timings and modalities to be carried on the machinery, with the related implications on the workplace health and safety matter.
How will these liability implications be regulated?
Can the user of the machinery exempt himself from liability, passing it on to the supplier which carries out remote maintenance?
Or will both be jointly liable?
What about criminal liability?
What about liability under the Italian Legislative Decree 231/2001?