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.

Robert Bosch GmbH (BOSCH)

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The Bosch Group is a leading global supplier of technology and services. In 2013, its roughly 281,000 associates generated sales of 46.1 billion euros. Its operations are divided into four business sectors: Automotive Technology, Industrial Technology, Consumer Goods, and Energy and Building Technology. The Bosch Group comprises Robert Bosch GmbH and its more than 360 subsidiaries and regional companies in some 50 countries. If its sales and service partners are included, then Bosch is represented in roughly 150 countries. This worldwide development, manufacturing, and sales network is the foundation for further growth. In 2013, the Bosch Group invested some 4.5 billion euros in research and development and applied for some 5,000 patents. This is an average of 20 patents per day. The Bosch Group’s products and services are designed to fascinate, and to improve the quality of life by providing solutions which are both innovative and beneficial. In this way, the company offers technology worldwide that is “Invented for life.” The company was set up in Stuttgart in 1886 by Robert Bosch (1861-1942) as “Workshop for Precision Mechanics and Electrical Engineering.” The special ownership structure of Robert Bosch GmbH guarantees the entrepreneurial freedom of the Bosch Group, making it possible for the company to plan over the long term and to undertake significant up-front investments in the safeguarding of its future. Ninety-two percent of the share capital of Robert Bosch GmbH is held by Robert Bosch Stiftung GmbH, a charitable foundation. The majority of voting rights are held by Robert Bosch Industrietreuhand KG, an industrial trust. The entrepreneurial ownership functions are carried out by the trust. The remaining shares are held by the Bosch family and by Robert Bosch GmbH. Functions like fleet management, condition monitoring and position fixing for commercial vehicles are based on the interconnection of vehicle and external IT systems. For commercial vehicles, Bosch offers technical system solutions that enhance the efficiency, safety and ergonomics of the driver’s workplace. To connect the vehicle’s systems to external IT systems, an additional communication unit – the connectivity hardware – reads out the vehicle data from the control units and transmits it to the external systems. Bosch provides various hardware solutions for this data transmission that have been specially designed for commercial vehicles. The access to vehicle data by external IT systems can, for instance, be utilized for continuous vehicle condition monitoring and uptime management. This allows maintenance schedules to be organized better, potential malfunction to be detected sooner and uptime to be enhanced.

Relevant Expertise for the project:

Bosch works on the development of preventive diagnosis modules for enhancing uptime. To do this Bosch combines relevant powertrain system knowledge with a holistic system approach. For commercial vehicles external surveys and customer consultations show that for fleet operators uptime is a business critical topic. Therefore the key activities focus on answers for the questions: Which detection methods for the state based prediction of failures are necessary? How to enhance uptime and retain flexibility and maintainability in use of predictive maintenance algorithms after start of vehicle production? How to integrate those predictive maintenance modules in fleet management? How to keep predictive modules and transfer technologies standardized? Bosch performs research to reach a deep inspection depth and to achieve a new detailed prediction granularity with a combination of several state detection technologies. In addition to that Bosch works on software algorithms which enable the over the air execution and post SOP adaption of preventive diagnosis modules on connectivity hardware.

Role in the project:

Establishment of a foundation for the preventive diagnosis of powertrain products (commercial vehicles) for the web based optimisation of uptime. Development of methods and proceedings to: a) detect the load and wear based failure based on the actual state of systems and components and b) do prognosis of the product lifetime by reconfigurable analysis systems based on online data of vehicle individual data in order to enhance vehicle availability. From development point of view Bosch has long term extensive knowledge in component and system design of powertrainIn MANTIS Bosch will contribute with knowledge for the development of algorithms to enhance uptime with preventive diagnosis modules with a detection granularity down to component level. The competencies will be used in WP7 (Validation of MANTIS solutions in relevant scenarios) and WP4 (analysis and decision making). Furthermore these preventive diagnosis modules can be included in a commercial service platform solution relevant for WP2 (service platform architecture development). With an additional Bosch communication unit – the connectivity hardware we contribute to WP3 (smart sensing and data acquisition technologies) as Bosch uptime modules partly run on connectivity modules and are reconfigurable after vehicle start of production.


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STILL supplies customised internal logistics solutions and implements the intelligent management of material handling equipment, software and services worldwide. With over 7000 employees, four production facilities, 14 branches in Germany and 20 international subsidiaries as well as a global dealer network, STILL is a successful international player. Today and in the future, STILL fulfils the requirements of small, medium-sized and large companies with highest quality, reliability and innovative technology.

Relevant Expertise for the project:

Within STILL focuses on a comprehensive concept for intralogistics managing the exchange of information between trucks and all related systems. Our holistic approach aims at an efficient interplay of all components involved in intralogistics including manpower. Quality and fast service at STILL guarantee high availability. Our products are user-friendly and therefore time saving to operate. By analysing the flow of material and information of our customers, we want be able to offer solutions perfectly tailored to any individual demand. Innovative and intelligent ideas help us to meet the responsibility we have toward the environment.

Role in the project:

STILL will contribute significantly to the software development and modification. Working with the support of the other partners, STILL will act as an OEM in exploitation and integration activities within the use-case test. Still is responsible for the implementation of requirements regarding the information management systems from our fleet and our services.

m2Xpert GmbH & Co KG (M2X)

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m2Xpert is a German startup company located in Bielefeld. m2Xpert develops software, system components and provides intelligent networking services. m2Xpert aims on providing safe solutions for networking machines between themselves and with different management infrastructures. For this purpose machines communicate with each other via communication modules. m2Xpert delivers safe multichannel communication systems (radio modems) together with specialized hardware suppliers. Intelligent embedded systems for controlling machine to machine communication and machine to infrastructure communication belong to the range of services. Software applications developed by m2Xpert are able to run distributed or locally. The applications aim on classic telemetry, service management, order management, control of intelligent sensor networks, fleet control and other content. A variety of sensor data from networked mobile and stationary machinery and equipment can be recorded, processed and analyzed by m2Xpert. One important goal is to avoid machine downtime to increase the efficiency of machinery use. Intelligent machine-, fleet-, and multi-vendor service solutions can be realized. One main task of m2Xpert is the development and implementation of user-centered, intuitive HMI design concepts. The client systems are applicable to different software architectures on various mobile devices, such as consumer devices (smartphones, tablets) or machine terminals. The aim of m2Xpert is to develop and establish open, cross-vendor networking standards. m2Xpert is currently working on cross-vendor standardisation of data exchange interfaces. The aim is to network different machines safely and consistently. Many machines form collective units. These machineunits are characterized by a comprehensive networking among themselves. In addition, the machines are networked with various distributed decentralized management systems. For this purpose m2xpert designs knowledge-based value-added services. These knowledge-based services lead to measurable performance improvements in machine collectives.

Relevant Expertise for the project:

m2Xpert is a startup company that started economic activity in 2014. Some employees of m2Xpert worked in the field of system-based services. They gained research experience in the following research projects: • INA – Integrated, multimedia-supported agricultural services in virtual structures, funded by the Federal Ministry of Economics and Technology, 2002-2006, grant number 01MD201. • marion – Mobile autonomous cooperative robots in complex value chains, funded by the Federal Ministry of Economics and Technology, 2010-2013, grant number 01MA10025A. • iGreen – the intelligent information technologies for the public-private knowledge management in the agricultural sector, funded by the Federal Ministry of Economics of Education and Research, 2009-2013, grant number 01IA08005Q. • M2M Teledesk, sponsored by Ziel2.NRW, 2012 until 2014 • itsOWL-RUMORS – modeling and run-time support for hybrid value creation in semi-autonomous and mobile agricultural machines, 2012-2014, grant number 02PQ2070.

Role in the project:

m2xpert plan to participate in the following work packages: due to our experience we like to contribute to work package 1 “Service platform architecture requirement definition. Scenarios and use cases descriptions”, 2 ”Service platform architecture development” 4 ”Analysis and decision making functionalities” and work package 5 “HMI design and development”. Since we are very experienced in business model design we also want to participate in work package 6 “Business impact and models”. As SME we are especially forced to validate and demonstrate our results. Therefore our main work package will be work package 7 ”Validation of MANTIS solutions in relevant scenarios”. Our main work package lies in use-case 2.2 ”Offroad and special purpose vehicles. We also want to contribute to work package 8 ”Dissemination of knowledge and exploitation” and work package 9 ”Project Management”.