Page 26 - 360.revista de Alta Velocidad - Nº 5

Coca, Marcos

Since its very beginning, railway maintenance has evolved at a pace marked by technology
innovations integrated in rail and infrastructure equipment as well as the set of methods and
tools acquired by the industry. However just in the third quarter of the twentieth century
electronic and communication systems burst into the railway industry to accompany and mark
the future of this activity.
An important milestone which is part of this Third Industrial Revolution or era of automation is
the incorporation of digital systems. The leap from analog to digital control systems, apart from
improving accuracy and response times in the regulation of systems, significantly increased the
diagnostic capacity by progressively developing controllers and interfaces capable of managing
larger volumes of information per unit-time and to extend the scope of connected devices at
even increasingly competitive costs of acquisition and operation. Even though it was a real
source of improvement for railway maintenance execution, the processing and communication
speeds already achieved could not lead to real-time data sharing and remote systems diagnosis.
At this time we navigate within the Fourth Industrial Revolution [Industry 4.0 or Connected
Industry], reaching outstanding levels of computing power, intelligence and development
of communication systems, including wireless, which are allowing to an unprecedented
qualitative leap in the execution of maintenance operations and in the organization of the
railway maintenance activity.
Opportunities are extraordinary: from planning the execution of the maintenance activity in
advance after predicting the future behavior of the systems, to considering the results of
previous decisions and feed the process through Machine Learning and Artificial Intelligence,
and to detect new business opportunities or optimization possibilities benefitting our clients or
the company itself from massive data analysis [Big Data].

But the advantages also bring important challenges to be mastered so that the introduction of
the new technology adds real added-value to the maintenance activity and does not become
a mere digital showcase. The vertiginous technological development puts on the table an
enormous volume of data provided by the equipment that needs to be interpreted, filtered
andtransformed into useful information for decision making, and which in turn encourages
the continuous appearance of data analysis tools which must be observed. On the other
hand, this scenario provides complementary information to the maintainer (service demand,
infrastructure status, environmental parameters, etc.) that may imply new opportunities or
changes in maintenance management models. This requires adequate skills and competencies:
from the global vision necessary to direct investments in digital transformation, to the ability to
interpret the technical and operational data available to transform them into useful information
for business decisions.
Currently more than 50% of the companies adopting Internet of Things are not sure of the
return of their investment. New technologies are routinely evaluated and deployed in such a
fragmented way that it is not possible to assess in advance the joint effect of their integration.
27% of companies are not sure of the questions they should ask around data, and 31% do not
store the information that is generated. This indicates that the level of maturity is not yet high
and we are only at the beginning of the learning curve.
How the organization adapts itself to this new scenario, how information is shared, how
resources are organized, and how processes are designed to make operational decisions reliable
and efficient enough will be key to the success of the system, and in any case the possible
solution to the challenges posed.

1. Technological offer

The market is currently able to provide technological gadgets to particular users or companies

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