Nowadays competitiveness of global market pushes managers to optimize all systems involved in their organizations in order to increase global efficiency and to improve Key Performance Indicators. In maintenance context this means reduce costs by optimizing interventions and eliminating unscheduled downtimes and breakdowns. To this end maintenance strategies have evolved from standard cyclic maintenance to more advanced approaches like Condition-Based Maintenance and Predictive Maintenance approach. Even if lot of work has been done regarding these methodologies applied on machines or industrial plants, the same care is not applied to other critical devices, such as Low Voltage Circuit Breakers, for which conservative approaches are generally applied. That implies a scheduled replacement of devices could occur with a significant Remaining Useful-Life. This paper deals with application of Condition-Based Maintenance approach to an electrical circuit breaker. The goal is to develop a diagnostic tool for Fault Detection, using 3-Sigma rule and Control Charts.

A magnetic field mapper based on (i) a rotating coil transducer of 40 × 10 mm² with a total coil surface of 0.1237 m², and (ii) a train-like system for longitudinal motion and positioning inside magnet bore, is proposed. The mapper allows a localised measurement of magnetic fields and the variation of the harmonic multipole content in the magnet ends. After an introduction to the measurement needs and problems, the magnetic measurement system is presented, focusing on the requirements, the architecture and conceptual design, and the prototype for straight magnets. Functional tests of the longitudinal position measurements of the system are reported and results of the experimental characterization are presented in terms of repeatability and resolution.

New emerging ICT solutions are providing powerful capabilities for distributed control and monitoring of production plants and machineries. In particular, Smart Sensors and Embedded mechatronics systems are promising intelligence at shop floor level, allowing many decisions taken in real time by decentralizing data analysis. Moreover, such new devices can be exploited by the use of Service Oriented Architecture (SOA), that can allow their interconnection in a kind of flat architecture. Maintenance activities can especially benefit from these technological developments, leading to distributed monitoring activities, faster data analysis, also guaranteeing low cost solution development. The paper presents the potential of a combined use of modularization and standardization to better exploit technology-enhanced solutions for improving maintenance management.

The purpose of this work is to model and simulate a harvester device whose purpose is to recover energy from the vibrations due to the irregularity of the railway and store it in order to subsequently feed a wireless sensor node.
The use of a piezoelectric harvester, instead of traditional batteries, allows the achievement of an energetically autonomous system, which does not need periodic maintenance to replace the batteries themselves. Studies about dynamics of trains showed that the axle box represents one of the most stressed components of the wheelset due to the irregularities of the railway line. For this reason it has been chosen as the optimal place to install the piezoelectric harvester. The system designed allows a real-time monitoring for diagnostic and prevention.

This work describes the development of a laser instrument for measuring the flow speed of oil, for minimum-quantity lubrication. The sensor is the laser diode itself, placed on the oil tube without any lens, acting as a self-mixing interferometer. The dyes inside the oil induce a back scattering of the emitted light, and generate a Doppler signal, measured by the laser monitor photodiode. Through a suitable elaboration of the signal spectrum, it is possible to estimate the oil flow; this measurement is essential for the correct maintainability of machine tools.