Partners

MANTIS: Conventional Energy Production Use-Case

The Finnish use-case under the MANTIS project concentrates on proactive maintenance solutions in the field of conventional energy production. The industry is moving towards smaller distributed plants with less on-site staff and thus, the ability to deploy conventional CBM strategies has declined. However, availability is still a major factor in power generation efficiency and plant feasibility. Therefore, new kind of energy production asset maintenance solutions applicable also for less critical components are required.

Five industrial and academic partners, namely Fortum, Lapland University of Applied Sciences (LUAS), Nome, VTT and Wapice, form the Finnish consortium in the MANTIS project. The Finnish use-case of conventional energy production is centered on a flue gas blower in Fortum’s Järvenpää power plant. Power plants have a large array of rotating machinery, whose reliability greatly affect on the overall reliability of the plant. As such, the blower offers a valid testing environment for collaborative maintenance solutions developed by the Finnish partners. The blower has been instrumented with vibration sensors, virtual sensors and local data collectors provided by Nome, Wapice and VTT. The measurement data is stored in the MIMOSA data model based MANTIS database via REST interface developed by LUAS. The collected data can be distributed to individual systems across organizational boundaries for analysis purposes. The partners of the conventional energy production use-case have integrated their own analytic tools, such as Fortum’s TOPi, Nome’s NMAS and Wapice’s IoT-Ticket, to the MANTIS database, as illustrated in figure 1, and tested the system architecture successfully in practice.

Pilot structure of the conventional energy production use-case
Pilot structure of the conventional energy production use-case

The MANTIS project has offered a great opportunity for the conventional energy production use-case partners to develop their own HMIs that can be integrated to different fields of proactive maintenance. The development work continues in the third and last phase of the MANTIS project, as some advanced visualization approaches, including virtual reality and augmented reality applications, are piloted and integrated to the HMIs. The piloted cloud architecture from Fortum’s Järvenpää power plant will also be tested in larger scale in another entire power plant. The data collection will be extended to cover a wider range of equipment and process variables to enable plant-wide monitoring of assets and proactive maintenance strategies. In addition, the partners are developing their analytic tools further to  provide solutions capable of diagnostics and prognostics required in advanced maintenance.

 

Clustering machines based on event logs within the MANTIS project

Introduction

Liebherr participates in the MANTIS project as an industrial partner with the division Liebherr hydraulic excavators. As expected, the main expertise of Liebherr consists in developing and optimizing excavators under consideration of different information sources. However, after the delivery of the excavator to the customer, every excavator generates event respectively message data automatically, which are actually mainly used for fault diagnostics but not extensively for further investigations.

This event data logger records among other things basically:

  • timestamp, when an event occurs
  • type of event, e.g. info, warning or error
  • unique message identifier of this event class

In combination with anonymized data concerning service partner and customer the following questions are relevant:

  • Is there a relation between the message patterns and the corresponding anonymized service partner?
  • Is there a relation between the message patterns and the anonymized customer?

Analysis approach for clustering

The related analysis was performed by the University of Groningen (RUG) as a research partner within the MANTIS project by considering each excavator as a stochastic message generator. In the context of preprocessing, the different messages were first counted per excavator and afterwards normalized with the total amount of occurrence per unique message identifier.

Based on the computed message probabilities per machine a k-means clustering was performed. To overcome initialization influences the clustering was performed 100 times with random initialization. The relationship of the cluster assignment of each excavator with the corresponding service partner or customer for each ‘k’ was subsequently examined with the chi-square test. The average estimate of the significance of the 100 model estimations of each ‘k’ then represented the quality function.

Results of cluster analysis

As can be seen in figure 1, there is no tendency for a relationship between the service partner and the messages per excavator. The average significance level is obviously higher than 0.05 and all of the single levels have nearly the same magnitude.

Average p-significance levels as a function of k (number of groups), for the interaction clusters versus service partner
Average p-significance levels as a function of k (number of groups), for the interaction clusters versus service partner

In contrast to figure 1, figure 2 shows a clear minimum at k=7, indicating that for this number of groups, it is likely that the distribution of machines over customers is not likely to be random. Although the p_signif – value is with 0.0588 slightly above the significance level of 0.05, the magnitude at k=7 is obviously lower than at other k-values.

 

Average p-significance levels as a function of k (number of groups) for the interaction clusters versus customers.
Average p-significance levels as a function of k (number of groups) for the interaction clusters versus customers.

In order to explain the minimum at k = 7, Liebherr decoded the anonymized customers and tried to find manually a description of the clusters. The cumbersome work did actually not yield to the expected result, namely the detection of short cluster descriptions, but rather to the recognition of customer data mismatching.

In summary the carried out analysis pointed out, that with the skillful usage of analysis algorithms superficial unmanageable data can disclose insights. But one of the basic requirements for later usage of the results is the proper preparation of data.

Providing reliability of components to customers with the MANTIS Maintenance Architecture

Goizper S. Coop., smart components’ manufacturer

Goizper S. Coop’s products are mechanical components (clutch brakes, gear boxes, indexing units…) installed within different kind of productive machines. These machines are designed to produce continuously and unplanned downtimes generate high costs. These components are the key part of some of the mentioned productive machines and the relevant component’s health influences directly within the machine status.

Clutch Brake Component located within a mechanical press machine

Breakdown of Components

Furthermore, if one of these components fails, it takes a long time while a new one is sent to the customer’s facilities, removed the old one and set up the new one. In these cases, the production asset maintenance means lot of expenses for customers and suppliers.

MANTIS for predictive maintenance

MANTIS platform provides an online and future view of these components’ health. Smart sensors installed at the mechanical component are connected to Monitoring and Alerting, which is performed automatically, within the smart-G box located next to the mechanical component. Then, this Big Data is processed in the Cloud and through different Maintenance data analytics the status and future trend of the component health is obtained as an output.

Smart-G box and rotary union with sensors

Obviously, the introduction of this Cyber Physical System will not eliminate all machine breakdowns, but it will help in order to reduce considerably machine unplanned downtimes, so that the customer and supplier will be able to plan their maintenance tasks and reduce these kind of stops.

MANTIS Collaboration

Within the MANTIS ECSEL project, Goizper has collaborated close to one of its customers, Fagor Arrasate, trying to improve the real inconveniences and reduce expenses that unplanned downtimes cause in both firms.

Xtel Wireless ApS

Xtel-MANTIS

Xtel Wireless is a Danish company specialized in ultra-low power solutions and technologies. With a specialized knowledge and competences in developing state-of-the-art IoT (Internet of Things) products and wireless core technologies, Xtel Wireless has an expertise in developing innovative products. Xtel Wireless employs 15 engineers with an average experience of 15 years in developing high-tech and embedded solutions, as well as having design and innovation competences in the team.

Relevant Expertise for the project:

Xtel Wireless has an expertise in developing innovative products. In the IoT business segment, Xtel Wireless has developed a platform for wireless sensor modules. This platform has unique features in matter of performance, price level and size.

Role in the project:

Xtel Wireless will be involved in developing sensors for typical domestic households to provide the project with data, monitoring humidity, CO2-levels, temperature and VTO in the residential buildings. The aim is to collect and distribute the data, as well as present the data motivationally to the residents hereby encouraging changed energy behavior.

Sataservice Oy

Sataservice MANTIS

Sataservice (Group) Oy provides industrial maintenance services and projects for customers to reach high level of performance. The Group includes following companies, Sataservice Oy and Rauman Sähkökonehuolto Oy.

Both companies have perfect service portfolio and co-operation. Sataservice was founded in 2003. The headquarter is in Rauma, Finland. The company has been growing every year and for the moment we have approximately 350 employees. The turnover 2016 is around 35 M€. We are ISO 9001:2008 certified by Bureau Veritas.

The company have expertise of demanding environments which means that mainly our customers are in businesses that have demanding regulations and laws that have to be followed, for instance the food industry where we are involved with living animals and in the end of the process we handle ready made food. We are also involved in the medical business with its own regulations. We mainly have customers that have outsourced their maintenance, either production or facility maintenance or both. We do also lot of projects such as modernizations of old equipment that ensures that the lifecycle can be extended and the productivity is high for the customer.

We have expertise in mechanical, electrical, automation, HVAC and cranes. Rauman Sähkökonehuolto is specialized in electrical motors, pumps and gears and helps us to keep up the customers productivity, while we can manage ourselves most of all maintenance areas and can minimize unnecessary waiting time. At the moment most of our customers are in Finland but we are aiming to expand abroad when we find the right partners and customers.

Relevant Expertise for the project:

We have a really broad expertise in maintenance of production equipment, especially machining, packing machines, electrical motors, automation and so on. We have divided our business in different technologies and all of those have a dedicated leader for instance for cranes, HVAC and automation.

Role in the project:

We have a good possibility to provide environments to test use-cases. We want to develop ourselves our IoT and CBM strategy and clarify what we can and should offer our customers. The aim is that everyone, meaning our customers, ourselves and possibly third parties, sees it as a win-win situation. We also want to find good long term partners to execute the strategy.

Neogrid Technologies ApS

Neogrid MANTIS

Neogrid Technologies ApS, is an entrepreneur company working with intelligent energy visualisation, monitoring and control, utilising knowhow within wireless communication technology to develop Smart Grid solutions.

Neogrid Technologies develop intelligent forecast based energy management systems for both consumers, energy companies and 3rd party actors, enabling home energy management capabilities for house owners and large scale monitoring – allowing optimised individual and aggregated controlling.

This consists of a data acquisition and IoT platform and online control-interface. It includes advanced analytics, which are able to forecast energy consumption and flexibility, based on individual house modelling and advanced model predictive control.

The aim is to enable the user to monitor, plan and even shift energy consumption based on knowledge of price, average consumption patterns and conditions, allowing for cost reduction and increased control and overview. The integration between hardware and software goes well with the background and experience of the people behind Neogrid Technologies.

Furthermore, Neogrid Technologies develop and deliver a cloud-based system for monitoring and optimized individual and aggregated control of heat pumps and district heating buildings based on requirements from the energy system actors and 3rd party actors.

Relevant Expertise for the project:

Neogrid Technologies have by participation in selected research project gained more than 6 years’ experience developing control strategies and cloud-applications for heat pumps and district heating focusing on the power and district heating system and end user requirements. Through this work, Neogrid Technologies have gained deep knowledge and experience regarding practical challenges arises when 80 live heat pump installations are centrally controlled.

Role in the project:

Neogrid will Participate in WP7, task 7.3, where an integrated energy system comprising of energy production, distribution and energy consumption of buildings (electricity and district heating) can be forecasted, optimized and moved according to various needs in the energy system.

Via aggregated control of a number of buildings (district heating and heat pumps), besides what is mentioned above, the predicted energy consumption can be taken into account when planning maintenance outage/interruptions so the influence or disadvantage of the heating service towards the consumers is minimized.

The above mentioned IoT platform Neogrid will develop and deliver services where the Product PreHeat and aggregator among other will be used to simulate and analyze the energy system with respect saving energy, monitoring and predicted maintenance.

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.

STILL GmbH (STILL)

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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”.

Fraunhofer Institute for Experimental Software Engineering IESE (FHG)

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Fraunhofer is Europe’s largest application-oriented research organisation. The Fraunhofer-Institute for Experimental Software Engineering (FhG IESE) in Kaiserslautern, Germany, founded in January 1996, is led by Prof. Dr. Dr. h.c. Dieter Rombach and Prof. Dr.-ing. Peter Liggesmeyer. Research efforts are entirely adjusted to societal and people’s needs: health, security, communication, energy and the environment. As a result, the work performed by our researchers and developers has a significant impact on people’s lives. We are creative. We shape technology. We design products. We improve methods and techniques. We open up new perspectives. FhG IESE focuses on applied research, development and technology transfer in the areas of innovative software and system development approaches, quality and process engineering, continuous improvement as well as organisational learning. In order to prepare industrial software developers and users for current and future information technology challenges, FhG develops new techniques, methods, processes, and tools that base software development on sound engineering principles. FhG thus provides competence as well as the training on methods and tools necessary to mature industrial software and systems development practices and give companies a competitive market advantage.

Relevant Expertise for the project:

FhG IESE has developed advanced engineering methods and tools in the field of requirements, architecture, safety, security, product lines/adaptable systems, and modelbased development in many national and international public projects (e.g., CESAR, CRYSTAL, EMC2 , MBAT, SPES 2020, SPES XT, FAMILIES, PESOA, HATS) and in cooperation with industry partners as Bosch, Continental, Daimler, EADS, and Siemens. Furthermore FhG IESE has many years of experience with numerous industry projects in the area of functional safety and is a strategic partner of many companies for innovative

Role in the project:

FhG will help to assure that the MANTIS platform architecture and solutions will meet the essential quality demands from the very beginning of the development, with a special focus on dependability including safety, security and openness. With this FhG is developing solutions within the MANTIS platform architecture in • Overall system requirements and architecture (WP 1 and 2) • System management approaches for open adaptive embedded systems that guarantee safety and security at runtime (WP 2). • Decision support, e.g. modelling and reasoning of adaptations and their interdependencies (WP 4) • Commercial vehicle and off-road vehicle use cases (WP 7). The platform will be validated, especially within the use case of off-road vehicles together with German OEMs and suppliers, thereby focusing on non-functional properties of the resulting CPS.