Reference Architecture of the Portuguese Mantis Pilot


The MANTIS Steel Bending Machine pilot aims at providing the use case owner – ADIRA – a worldwide remote maintenance service to its customers. The main goal is to improve its services by making available new maintenance capabilities with reduced costs, reduce response time, avoiding rework and allowing for better maintenance activities planning.

To this purpose existing ADIRA’s machines (starting with their high end machine model – the Greenbender) will be augmented with extra sensors, which together with information collected from existing sensors will be sent to the cloud to be analyzed. Results made available by the analysis process will be presented to machine operators or maintainers through a HMI interface.

adira greenbender gb-22040 MANTIS
Adira –  Greenbender GB-22040

A number of partners are involved into the development and testing of the modules, which regard the communication middleware (ISEP, UNINOVA), data  processing  and  analytics activities (INESCISEP), the HMI applications (ISEP), and a stakeholder providing a machine to be enhanced with the MANTIS innovations (ADIRA).

System Architecture

The distributed system being built responds to a reference architecture that is composed by a number of modules, the latter grouped into 4 logical blocks: the Machine under analysis, Data Analysis module, Visualization module, and the Middleware supporting inter-module communications.

architechture of the maintenance system for MANTIS
architecture of the maintenance system for MANTIS


Data regarding the machine under analysis are collected by means of sensors, which integrate with the machine itself. This logical block consists thus of data sources that will be used for failure detection, prognosis and diagnosis. This set of data sources comprises an ERP (Enterprise Resource Planning) system, data generated by the machine’s Computer Numerical Controller (CNC) and the safety programmable logical controller (PLC).


This logical block operates through two basic modules. The first is the MANTIS Embedded PC, which is basically an application that can run on a low cost computer (like a Raspeberry Pi) or directly on the CNC (if powerful enough). This module is responsible for collecting the data from the CNC I/O and transmitting it to the Data Analysis engine for processing and is implemented as a communication API. When based on an external computer, this module also connects to the new wireless MANTIS sensors placed on the machine using Bluetooth Low Energy protocol (BLE). Communications are then supported by the RabbitMQ message oriented middleware, which takes care of proper routing of messages between peers. This middleware handles both AMQP and MQTT protocols to communicate between nodes.

The I/O module is used in order to extract raw information from the machine sensors which is collected by the existing PLC, made available on the Windows-based numerical controller through shared memory and then written to files. Our software collects sensor data from these files, thus completely isolating the MANTIS applications from the numerical controller’s application and from the PLC.

Data Analysis

This logical block takes care of Data Analysis and Prediction, and it exploits three main modules. The first is a set of prediction models used for the detection, prognosis and diagnosis of the machine failures. The second is an API that allows clients to request predictions from the models, and that can respond to different paradigms such as REST or message-queue based. Finally, the third module is a basic ETL subsystem (Extraction, Transformation and Loading) that is responsible for acquiring, preparing and recording the data that will be used for model generation, selection and testing. This last module is also used to process the analytics request data as the same model generation transformations are also required for prediction.


This logical block consists of two modules, the human machine interface (HMI) and the Intelligent Maintenance DSS. The HMI is designed to be a web-based mobile application, and to be accessed via the network from any computer or tablet. The HMI is developed to work in two different modes, depending on which kind of user is accessing it. In fact, the HMI is developed to support two user types, the data analyst and the maintenance manager, allowing both of them to analyze the machine’s status, record failure and diagnostics related data. Moreover, the data analysis HMI provides an interface with the data analyst, allowing the consultation and analysis of data and results. On the other hand, the maintenance management HMI allows for consulting predicted events and suggested maintenance actions.

The second module is an Intelligent Maintenance DSS, which uses a Knowledge Base that uses diagnosis, prediction models and the data sent by sensors. On top of this Knowledge Base there is a Rule based Reasoning Engine that includes all the rules that are necessary to deduce new knowledge that helps the maintenance crew to diagnose failures.

Ongoing work

The work performed so far is well advanced and an integration event will occur in the near future where the interconnection between all systems will be tested and validated.

The demonstrator being built, will be evaluated according to the following criteria: prediction model performance (live data sets will be compared to model generation test   sets) and the applications usability (the user should access the required information easily, in order to facilitate failure detection and diagnosis).

1st CREMA/C2NET Industrial Workshop

The 1st CREMA/C2NET Industrial workshop will take place the 24th November at Orona Fundazioa facilities located in Hernani (Basque Country – Spain). The event, organised by CREMA and C2NET H2020 EU projects, is intended to present future trends of European Industry especially those related to digitalization technologies applied to manufacturing. High levels speakers from the Basque Government, the European Commission, and the Industry sector (ill give their expert vision.

Moreover, CREMA and C2NET will present findings generated in both projects highlighting their approaches to meet above challenges. Presentations and practical demonstrations will be made by partners of both projects to present innovative solutions based on digital platforms in the Cloud to boost collaboration among manufacturing companies. Advanced Cloud technologies and applications will be shown to allow manufacturing companies faster and more efficient decision making for a better use of their manufacturing assets. Different business models and exploitation strategies followed by both projects to bring their outcomes to the market will also be presented.

Some MANTIS partners such as MGEP, IKERLAN, TEKNIKER, MCC, FAGOR ARRASATE and GOIZPER will attend this event to know other EU projects approaches to deal with common research areas and to make new contacts for potential collaboration actions in the future.

There is still time for registration accessing the website of the event: http://www.crema-c2networkshop.com/. We encourage you to do so.


09:00 – 09:30


09:30 – 09:40

Opening session

Welcome and event presentation

·       Eduardo Saiz, IK4-IKERLAN –  CREMA Project Researcher & C2NET Project Manager

Basque Government short talk

·       Alexander Arriola, General Director of SPRI/Basque Government

9:40 – 10:00

First Keynote: Industry 4.0 Implementation Strategy

·       Eduardo Beltrán, Innovation & Technology Director of MONDRAGON Corporation

10:00 – 10:15

Digitising European Industry

·       Max Lemke, Head of Unit Components and Systems, European Commission, DG CONNECT

10:15 – 11:00

The CREMA / C2NET viewpoint on future Industrial trends and a taste of the services that can be deployed in the Industrial Arena

·       Tim Dellas, ASCORA – CREMA Project Coordinator

·       Jorge Rodriguez, ATOS – C2NET Project Coordinator

11:00 – 11:30

Coffee Break

11:30 – 12:15

CREMA – Cloud Services for the Manufacturing Sector

·       Jon Rodriguez, FAGOR ARRASATE – CREMA Use Case I: Machinery Maintenance WP Leader

·       Mikel Anasagasti, GOIZPER – CREMA Use Case I: Machinery Maintenance Partner

·       Aizea Lojo, IK4-IKERLAN – CREMA Project Manager

·       Jessica Gil, TENNECO – CREMA Use Case II: Automotive WP Leader

12:15 – 13:00

C2NET – The complete Networked solution for Industry

·       Raúl Poler, UPV – C2NET Processes Optimization of Manufacturing Assets WP Leader

·       Carlos Agostinho, UNINOVA – C2NET Continuous Data Collection Framework WP Leader

·       Jacques Lamothe, ARMINES – C2NET Tools for Agile Collaboration WP Leader

13:00 – 14:00

Lunch break

14:00 – 14:45

Second Keynote: Industry 4.0 – How to master challenges to exploit new business opportunities

·       Stefan Zimmermann, Head of Global Vertical Manufacturing, Retail and Transportation market at ATOS

14:45 – 15:15

Interactive Session: Feedback from audience to capture the Pros and Cons if Industry 4.0. What hurdles need to be overcome  from an Industrial viewpoint

·       Moderator: Gash Bhullar, TANet – CREMA Impact WP Leader

15:15 – 15:45

CREMA / C2NET Response to the Interactive Session and potential solutions to the Industry 4.0 Implementation and Deployment Strategies

·       Moderator: Gash Bhullar, TANet – CREMA Impact WP Leader

15:45 – 16:00

Coffee Break

16:30 – 17:00

Panel discussion

·       Moderator: Gash Bhullar, CREMA TANet – Impact WP Leader


Closing remarks

·       Eduardo Saiz, IK4-IKERLAN –  CREMA Project Researcher & C2NET Project Manager

User-friendly interfaces: Treating data sets like recommendations from a friend

Data from smart, connected devices and related external data may come in an array of formats, such as sensor readings, locations, temperatures and history. In order to understand the patterns, the spreadsheets and database tables need to be suited to user’s needs.

Ideally, the interface would not require the user to undergo training in order to be able to use it. As far as text is concerned, it is crucial that the messages avoid ambiguity, inaccuracy, inconsistency and inadequacy in order to ensure more safety, fewer errors and higher productivity.

To capture and display maintenance-relevant information, MANTIS is designing user-friendly industry dashboards for control rooms combined with mobile extensions on the go. As MANTIS use cases vary from railway maintenance to healthcare equipment maintenance, strongly dependent on individual technical constraints, there is no common, specific MANTIS Human Machine Interface (HMI) design.

However, as central feature of most design use cases is displaying data of monitoring process and responding to alarms, parallels can be drawn and best use practices can be used in MANTIS.

E.g. presenting information such as asset maintenance history, the overall condition, sensor data and analysis was a task assigned to XLAB in several other past and current projects. We describe how feedback gained from two successful past projects – the spin off company Sentinel Marine Solutions and FINESCE smart buildings – helped draw up guidelines. Special emphasis was placed on user experience (UX), creating a relationship with the user over time and on how he feels during the whole lifecycle of the product.

The IMPACT-accelerated startup and FIWARE technology implementer Sentinel Marine Solutions follows the overall state of the boat and allows real time access to sensor data to avoid e.g. batteries losing charge. Crucial boat parameters, water level, temperature readings, battery voltage, bilge pump, are presented on a user-friendly interface – tablet, smartphone or dashboard in the control room or cabin (Image below).

Monitoring is done continuously, providing rich information about one or several vessels’ position, voltage, temperature – where ever the user may be, on land or off shore. That is why Sentinel keeps it simple, to avoid cluttering and confusion, and complements it with a visually pleasing design for sustained usage of application.

HMI battery status maintenance
HMI battery status maintenance
hmi sensors maintenance
hmi sensors maintenance

Work on previous research projects confirms that it is worth investing a significant part of the application development into how the system presents data to the end users. Within the FINESCE project, the top part of the presentation layer was designed by XLAB. The interface connects data on energy generation and consumption in smart factories and smart buildings. It had to be optimized for quick retrieval and display in order to identify deviations and enable fast responses.

The application has many views showing specific aspects of the data, but each in a context that is relevant to the workflows of end users – below an example of the Smart building consumption Overview tab.

Last but not least, the aim of the design of these applications was to present the data to the users with a pleasing appearance, while at the same time offer crucial visual information on the current and past energy consumption.