Early detection of fissures in industrial structures

Industrial sectors such as automation, energy and mechanical manufacturing are more increasingly in the need of including predictive maintenance techniques and processes, in order to improve their product quality and reduce their maintenance costs.

In such scenarios, fatigue is a cumulative phenomenon that appears when material is subjected to repeated loading and unloading. When this happens and the target is stressed beyond its critical threshold, microscopic cracks begin to form, which will eventually end fracturing the structure. Thus, smart sensors must be placed in the critical zones, in order to early monitor the growth and evolution of the cracks.

Solution approaches

As it is described within WP3’s use case 1.3 in MANTIS project, which focuses on developing a framework for smart sensing and data acquisition technologies, there are several detection techniques for direct crack measurements, such us regular strain gauges and crack gauges. These last elements are made of aligned grids which are disconnected one by one with the propagation of the crack. The drawback comes in terms of placement, as the location of the failure is not always predictable and therefore it would require a complex multi-gauge installation, in order to cover a large area of sensorization and anticipate the formation of cracks.

Another approach which is being analyzed and tested within use case 1.3, is the utilization of conductive inks, which could give more flexibility in terms of placement and the design of the sensorization area to be monitored.

Installation requirements

If the fissure detection is performed with conductive inks a necessary requirement must be taken into account. As the structures that are monitored are electrically conductive, an insulation layer must be deposited between the structure and the conductive ink. For the efficient detection of fissures, this insulation layer should break with the structure, but it must not brittle with time, temperature, humidity, etc. Even more, it should be easily deposited, as the structure may be located in a difficult to access place.

According to the conductive ink, it should also be of easy deposition, with low resistivity and withstand high temperatures without breaking.

Current tests

In the preliminary tests, a Magnesia paste based insulation layer has been used and on top of it, a vinyl mask layer has been stuck for the definition of the conductive layer structure. As conductive ink, a low resistivity silver ink has been used, defining two structures: a gage structure, Figure 1, and continuous conductive line.

Conductive ink structures
Conductive ink structures

During the fissure measurements, the gage structure has been supplied and measured, recording both current and voltage. As it is shown in Figure 2, as the lines of the gage structure break, an increase in the measured voltage and resistance is recorded.

Fissure detection measurements
Fissure detection measurements

Thus, properly deposited and structure adapted conductive inks could stand as a solution for the early detection of fissures in industrial structures.

Nowcasting and Forecasting tecniques for railway switches maintenance

A large proportion of the costs of the European railway Infrastructure is related to maintenance and the current situation of railway maintenance .

The increasing usage of the railway infrastructure, due to a growing frequency of passenger and freight trains on it, and environmental and safety regulations, the increasing of maintenance requirements cannot be met without a substantial shift in maintenance strategies.

In this prospective, the new “Proactive/Predictive Maintenance”  approach will involve/have an impact all the main railway stakeholder on long-term preservation of assets (expressed in RAMS requirements) minimizing life cycle costs, while for the railway operators, the proactive maintenance will improve the railway infrastructure availability and reliability.

Switches and Crossings (S&C) are fundamental infrastructure assets that allow efficient routing of trains on the network. Assessing their current status and ensuring their proper functionality is obviously a key requirement to guarantee the railway infrastructure availability for the railway operators. For these reasons, Ansaldo STS tries to discover in the Mantis project, references concerning railway S&C condition monitoring based on a wide range of methodologies from the world of statistics, data mining, time series analysis, machine learning, and filtering.

Given the examined literature, it seems clear that the use of the word “nowcasting” can be associated with: a shorter timeframe respect to “forecasting”, a different approach or algorithm for performing the estimation of the value of interest, the fact that the data used for the estimation is imprecise, uncertain, incomplete or is only indirectly related to the phenomenon of interest, and, finally, with the purpose of providing an alert for a sudden event or a possible anomaly.

A reasonable simple definition could be adopted in the framework of the Mantis project for differentiating “forecasting” and “nowcasting” processes:


The process of exploiting past and present data to make deductions about the future.


The process of exploiting past and present uncertain or incomplete data to make deductions about the present.

Many of the failures are not detected until the asset is being operated by the interlocking system when trying to lock the train route. This means that for some failures, nowcasting cannot be done before operating the unit. Frequent test procedures could solve this issue but it has other disadvantages like the introduction of increased wear, cost and reduced inherit capacity. Another solution for this problem is to introduce additional condition monitoring systems for detection of different states of critical components in the S&Cs.

Estimating the remaining component lifetime – a key activity of of MANTIS

A key activity of the MANTIS WP4 work on analysis and decision making functionalities has focus on identification and development of methods for forecasting the remaining useful life of an asset by modelling it’s deterioration and by extrapolating this into the future. When the extrapolated deterioration reaches a certain threshold that marks the end-of-life of the asset, and that point in time can be used as the forecasted remaining useful life (RUL). Simultaneously, the extrapolated deterioration gives an indication of the expected wear and tear, which can be compared with the observed wearing out to monitor the behavior of an asset.

Based on the predicted remaining lifetime, suitable maintenance tasks can be planned, in order to prevent unscheduled system down time.


Overall working strategy

The approach followed by MANTIS to address the estimation challenge is as follows:

  • Develop algorithms and train models to estimate the RUL or predict the wear and tear of an asset.
  • Monitored data (from embedded sensors or from quality assurance checks) is streamed to the cloud based storage system, where it will be investigated using time-series analysis or temporal data mining approaches.
  • These methods will be used to discover revealing relationships between parameters to identify significant patterns, trends and anomalies.
  • Based on this analysis of the historical data, a diagnostic model will be made self-learning, comparing predicted and actual data.
  • Flexible modelling techniques will be used on diverse information, such as condition parameters, data patterns, sparse data and/or existing expertise to learn more complex relationships between the different parameters or train models which allow prediction of future performance in terms of expected failures.


Current status of work

An overview of relevant deterioration models and methods to estimate the remaining useful life (RUL) has been made. Also, for each use case, the present status with respect to available data, deterioration models and methods for estimation of RUL has been collected. In particular, for each of the use cases, the following information is relevant:

  • Description of data typically available
  • Description of relevant deterioration processes
  • Description of models used for estimation of RUL


Next steps

During the next 6 months, the general models and methods will be analysed and compared with the present status for the individual use case (available data, deterioration process, RUL estimation models). Following this analysis, specific models and methods will be selected and unified as much as possible, and thereafter applied and validated on the use cases during the second half of the MANTIS project.

This will be achieved by using a bottom-top-bottom approach:

  • Collecting input for individual use cases
  • Seeking for commonalities and unification into a generic approach
  • Applying the generic approach on the individual use cases

Maintenance data analytics; How to deal with free text

Problem description

For analyzing maintenance problems, such as determining the root cause, in general three sources of information are available:

  • sensor data
  • machine generated logging messages
  • service and/or maintenance engineer reports

In contrast to sensor data and machine generated logging messages, of which the format is determined at design time, the service and maintenance reports have a free format, making it hard to analyze automatically.

Problem reporting
Problem reporting

Possible solutions

Before going into possible solutions, a better description of the problem is needed. Free format is this case means that a report can contain

  • unstructured text
  • ambiguous descriptions e.g. mixing commercial and technical identification
  • multiple languages e.g. using local language
  • spelling errors, ad hoc abbreviations, missing data etc.

For easy analysis it would be good if it is possible to bring free text back into the predefined format realm. Ways to solve this are

  • using predefined forms with e.g. dropdown lists for selecting options
  • using intelligent text editors that can recognize the vocabulary needed for describing the specific problems
  • combinations of the above
  • less stringent is specifying rules people have to abide by when entering maintenance logs (typo’s are still possible then)

As it is impossible to predict all problems that will be encountered during the lifetime of a machine, there still needs to be the option to enter free text, but it should be clear that this is only to be used when other options do not cover the problem at hand.


It is clear that free text will always be used in reporting, but in order to facilitate data analysis of service and/or maintenance reports computer aid or rules can make life a lot easier.

Research in WP5: HMI design and development

WP5 in MANTIS-project focuses to study on implementing an efficient intelligent human machine interaction to deal with the intelligent optimization of the production processes through the monitoring and management of its components. The overall objectives of WP5 is to develop HMI capable to contribute to:

  • Enhanced monitoring of shop-floor conditions
  • Automatic self-adaptation of control strategies
  • User-friendly, ergonomic and intuitive interaction between workers and machines

Work in WP5 started with the identification of human machine interaction scenarios from each eleven use-cases. When defining requirements for HMI from different use-case point of views, collaborative and proactive aspects were highlighted. Even though the use-cases are very different, common elements and functionalities from the requirements for HMI were identified. Figure 1 presents the overall approach towards WP5 when designing and developing HMI prototype.

Overall approach towards WP5
Overall approach towards WP5

At the moment work in WP5 focuses on researching different platform solutions that would serve the HMI needs specified in use-cases. The objective is to develop a platform solution that will serve the common HMI needs identified from use-cases. Initial discussions among the WP5 participants relates to building a Web-based maintenance information portal that will act as a prototype HMI, which could be tested in selected use-cases. WP5 partners have discussed the potential approaches over the last period and the implementation plan have just been agreed on. Figure 2 is an example view what maintenance information portal could look like consisting of user specific content elements.

Example view of maintenance information portal
Example view of maintenance information portal

We need to have in mind that the information portal should behave as a support for the users not as their replacement. Maintenance information portal could be:

  • a single gateway to a company’s information and knowledge base
  • a framework for integrating information, people and processes across organizational boundaries
  • a secure unified access point
  • designed to aggregate and personalize information

Discussions about importance of three concepts in HMI-development has also been active. These concepts are collaborative, proactive and context-aware functionalities. Collaborative functions in HMI could be the possibility to communicate through the portal, share information and UI-views with different actors involved in certain maintenance tasks. These actors can be within the organization or external service providers. Proactive functions can be automated, model based calculations that predicts maintenance needs early enough that required maintenance actions can be carried out to prevent unplanned down time. Context-aware functions could for instance alter user defined UI-views in certain scenarios such as emergency situations or changes in the state of the production process. UI-view could also change depending on physical location of the portable mobile device connected to MANTIS-platform.

Strong presence of predictive maintenance technologies in Bilbao’s international machine-tool definition

Held in Bilbao from 28th May to 1st June, the 29th edition of the Machine-Tool Biennial (BIEMH) gathered a total of 40,000 people, representing a clear success and a gradual industrial recovery indicator. Predictive maintenance has constituted a trending topic (as Industry 4.0 pillar) within the fair, specifically threated by MIC (Maintenance Innovation Conference), playing several MANTIS partners (FAGOR Arrasate, IK4-Ikerlan, IK4-Tekniker) a key role during the BIEMH. Specifically related to maintenance, FAGOR Arrasate presented the wide range of applications and services derived from the advanced connectivity their products bring in (e.g. check of operating functions and potential machine utilization improvements).

FAGOR ARRASATE connected manufacturing lines
FAGOR ARRASATE connected manufacturing lines

Moreover, DANOBAT Group (belonging to MONDRAGON Corporation) presented Dynamics Active Stabilizer, a device capable of actively increasing the dynamic rigidity of the machine tool, reducing the risk of chatter during the machining process and thus increasing the cutting capacity by up to 300%. This represents a clear example of how process data real-time processing (and analysing) can have a significant impact on productivity and production costs. DAS (which received the Quality Innovation of the Year award, organized by the Finish Quality Association) improves 100% capacity through the complete workpiece volume, increases productivity up to 300%, improves workpiece surface quality, extends the tool life and operates in real-time.

It was eventually announced that next BIEMH will take place on May 28-June 1, 2018 (Monday to Friday), which means it will be one day shorter than this year’s event.


On the whole, ICT enabled predictive maintenance states one of the most promising revenue streams machine tool builders have (hence its strong presence within this international fair). However, there are still several technological and non-technological challenges to be faced, being most of them tackled by MANTIS.

Usage of the MANTIS Service Platform Architecture for Health equipment maintenance optimization.

Healthcare Imaging Systems of Royal Philips N.V. are essential for the diagnosis and treatment of patients in hospitals and private clinics. Due to the large costs involved it is not economically feasible to implement backup systems. Therefore system uptime has to be maximized, planned downtime has to be minimized and unplanned shutdown has to be prevented. To cope with the exploding cost of healthcare, the cost of ownership has to be reduced, which also implies that maintenance budgets are under pressure. In response Philips Healthcare has developed maintenance services for hospitals based on remote monitoring of their systems.

Unplanned system shutdown has a large impact on patients and hospital staff
Health equipment used during patient treatment

The main challenge is to retrieve, store and analyse large amounts of data from globally distributed systems such that predictive maintenance can be offered instead of maintenance at fixed time intervals. Furthermore an alerting system is necessary when the online big data analysis detects a threat of shutdown.

Due to the large purchase cost and the cost of housing unplanned shutdown has a large impact on patients who do not get the care and on the hospital. The Healthcare Imaging Systems of Royal Philips N.V. will use the MANTIS Architecture for equipment asset optimization, thereby aiming to move from a reactive to proactive and predictive maintenance.

Main challenge: getting from large amounts of data to accurate and precise failure detection and prediction.

The objective is to accurately predict upcoming failures by mining large amounts of data from heterogeneous systems distributed globally, such that maintenance can be timely scheduled or in urgent cases the responsible person can be alerted.

Graphic depiction of Health equipment maintenance use case
Graphic depiction of Health equipment maintenance use case

Every Healthcare Imaging Systems of Royal Philips N.V. contains many sensors and generates large log files daily. Since these systems are heterogeneous by nature the first challenge to address is to optimize logging such that data mining success can be optimized (anamnesis). The next challenge is to make all data available worldwide in the cloud. Once the data is centrally available it has to be translated to behavioral models and consolidated in a limited set of relevant parameters (translation). This translation requires significant computing power and storage space (infrastructure). Next, the obtained parameters have to be analysed with respect to the maintenance challenges (analytics) and the results have to be visualized for end-users (visualization).

General assembly of the MANTIS project in Ljubljana

A three-day MANTIS project general assembly took place in Ljubljana, Slovenia from 23rd to 25th of May 2016. The meeting was organized by Jožef Stefan Institute and hosted 73 participants.

During the event there were eight technical Workshops (one for each project work package), the main General Assembly meeting, the Executive Board meeting, and a Keynote talk by the member of External Advisory Board. Each workshop discussed its role to reach the project goals of proactive maintenance by establishing the overall Service platform architecture.

Working part

The first day started with the project overview by the Coordinator, followed by the WP4 and WP5 workshops in parallel. The second day consisted of WP1, WP2, WP3, WP6, and WP8 workshops. Special attention was given to the Keynote talk by Jerker Delsing, who presented his view on proactive maintenance. The second day ended with the General Assembly meeting. On the third day WP2, WP7 and WP8 took place, and the day ended with the Executive Board meeting.

Each workshop discussed some open issues and set future actions and deadlines in order to reach its goals as well as the overall goals of the project.

Keynote talk in the Main lecture room
Keynote talk in the Main lecture room

Social part

Social part of the event consisted of a short Ljubljana tour at the end of the second day, where we experienced the drive with the new Ljubljana’s Electric train Urban (we are grateful to the City of Ljubljana for giving us the opportunity to test the train), and a dinner at the Ljubljana Castle with the local culinary.

MANTIS project attendees in front of the electric train
MANTIS project attendees in front of the electric train

Optimising Maintenance: What are the expectations for Cyber Physical Systems

The paper “Optimising Maintenance: What are the expectations for Cyber Physical Systems” has been presented at the 3rd International Workshop on Emerging Ideas and Trends in Engineering of Cyber-Physical Systems, EITEC’16. This workshop was held at the CPS Week 2016 in Vienna, Austria. The paper is the result of a collaboration between four MANTIS partners: Erkki Jantunen (VTT), Urko Zurutuza (MGEP), Luis Lino Ferreira (ISEP) and Pal Varga (BME). You can download the paper in the Dissemination section of the web.

Abstract—The need for maintenance is based on the wear of components of machinery. If this need can be defined reliably beforehand so that no unpredicted failures take place then the maintenance actions can be carried out economically with minimum disturbance to production. There are two basic challenges in solving the above. First understanding the development of wear and failures, and second managing the measurement and diagnosis of such parameters that can reveal the development of wear. In principle the development of wear and failures can be predicted through monitoring time, load or wear as such. Monitoring time is not very efficient, as there are only limited numbers of components that suffer from aging which as such is result of chemical wear i.e. changes in the material. In most cases the loading of components influences their wear. In principle the loading can be stable or varying in nature. Of these two cases the varying load case is much more challenging than the stable one. The monitoring of wear can be done either directly e.g. optical methods or indirectly e.g. vibration. Monitoring actual wear is naturally the most reliable approach, but it often means that additional investments are needed. The paper discusses the above issues and what are the requirements that follow from these for optimising maintenance based of the use of Cyber Physical Systems.

Kick-off meeting of the MANTIS project

The first MANTIS project meeting tool place in San Sebastian the 3rd of June 2015. The meeting was organized by the coordinator partner, Mondragon University, and 64 participants took place.

MANTIS project Consortium
First picture of the MANTIS project kick-off meeting attendees

We discussed the organizational structures, shared information on project management, the tools that will be used for managing all aspects of the project, as well as constitution of the decision bodies (General Assembly, Executive Board and External Advisory Board).

MANTIS, ECSEL project, kick-off meeting
MANTIS kick-off meeting agenda

The second day the meeting was split in 4 different Working groups, which corresponded to Requirements gathering, Architecture development, Sensors and Intelligent systems to be used in the MANTIS proactive maintenance platform.