September 2016

Closure event for T-Rex European project: WorkShop “Industry 4.0: Extension of machinery life-cycle, component re-use and servitization”

T-Rex project – Lifecycle Extension Through Product Redesign And Repair, Renovation, Reuse, Recycle Strategies For Usage & Reusage-Oriented Business Models

In current global economy, manufacturers are under pressure to adapt to an ever-changing business environment. As a consequence, as part of Industry 4.0, new trends are gaining momentum, such as the servitization of manufacturing. The servitization can also be seen as a business model innovation of organization process and capabilities, where service-oriented activities increase. This leads in turn to revise the importance of certain strategies and technologies, such as reliability and life-cycle assessment, service engineering or advanced maintenance.

Previous to the MANTIS project, during last 3 years, T-REX project, funded under 7th framework factories of the future programme, has developed technologies oriented to the extension of machinery life-cycle, component re-use and servitization. Moreover, it has developed a framework and other support tools to facilitate new business opportunities to companies, in particular SMEs.

These activities are all contributing towards the development of Industry 4.0, in particular with respect to the extension of the manufacturing activities beyond the factory.

Ulma truck and screenshot of the trucks fleet Control panel at the BIEMH fair in Bilbao (June 2016)
Ulma truck and screenshot of the trucks fleet Control panel at the BIEMH fair in Bilbao (June 2016)

Workshop “Industry 4.0: Extension of machinery life-cycle, component re-use and servitization”

As closure event for the T-Rex project in September 2016 IK4-TEKNIKER and ULMA are organizing a workshop which aims to demonstrate the feasibility of service-oriented business models, in particular for SMEs, and will include direct feedback from manufacturing companies interested in extending servitization and re-use activities. Part of these activities will take advantage of the results obtained in T-REX project.

WorkShop programme and registration

S[&]T corporation: Your partner in smart manufacturing

Science and Technology BV (S[&]T) is a SME developing cutting edge technology for complex systems. The company has built track record in space industry and since several years it is applying its innovation knowledge in smart manufacturing. Examples are central use of predictive analytics for real-time optimization and automated event handling with intelligent database and self-learning algorithm enabling impact analysis and decision support.

Below are some examples of previous projects that helped build the knowledge base:

Decision Support Systems

Time is a scarce and expensive resource aboard challenging scientific environments such as the International Space Station (ISS). The training and preparation of astronauts for onboard missions can take up a large amount of this resource, as do the actual maintenance, operation and troubleshooting involved with such missions. ESA has been researching more efficient, effective, and easy ways to realize human operations. S[&]T works on the following projects: ETECA (Expert Tool to Enhance Crew Autonomy), MECA (Mission Execution Crew Assistant) and TIDE (Technology for Information, Decision and Execution superiority). These technologies form the basis of decision support development in MANTIS.

GUI of Mission Execution Crew Assistant
GUI of Mission Execution Crew Assistant

System Health Management

SHM optimizes operation of complex systems by analyzing their health using either model-based methods i.e., using online sensor data and knowledge of normative system behaviour, or data-driven techniques, i.e., system behaviour is learned and extracted from large data volumes. Typical functionality includes: fault detection, diagnosis of system failures, and prediction of system failures. S[&]T has been involved in: ESA’s Future Launchers Preparatory Programme (FLPP), the real-time multiple sensor array LOFAR, and the development of a health management system for a Reusable Space Transportation System.

Rocket propellant with graphical analysis of the system health management
Rocket propellant with graphical analysis of the system health management
An example of system health management
Rocket propellant with graphical analysis of the system health management

Aim of S[&]T is to further develop its digital factory tools in a modular way. In this way specific analysis- and decision-support solutions can be created, dedicated per client.

Emerging Requirements for Future Manufacturing: the role of the new IoT/CPS based technologies

Internet of Things Applications in Future Manufacturing

The book chapter “Internet of things Applications in Future Manufacturing” is part of the 2016 IERC-European Research Cluster on the Internet of Things book (Digitising the Industry – Internet of Things Connecting the Physical, Digital and Virtual Worlds). This book is published by “River Publishers Series in Communications” that is a series of comprehensive academic and professional books which focus on communication and network systems. The book chapter is the result of a collaboration between John Soldados (Athens Information Technology), Sergio Gusmeroli (Politecnico di Milano) and MANTIS partner: Pedro Malo and Giovanni Di Orio (UNINOVA). You can download the book chapter in the Dissemination section of the web as well as the entire book by using the following link:


Introduction — Future manufacturing is driven by a number of emerging requirements including:

  • The need for a shift from capacity to capability, which aims at increasing manufacturing flexibility towards responding to variable market demand and achieving high-levels of customer fulfillment.
  • Support for new production models, beyond mass production. Factories of the future prescribe a transition from conventional make-to-stock (MTS) to emerging make-to-order (MTO), configure-to-order (CTO) and engineer-to-order (ETO) production models. The support of these models can render manufacturers more demand driven. For example, such production models are a key prerequisite for supporting mass customization, as a means of increasing variety with only minimal increase in production costs.
  • A trend towards profitable proximity sourcing and production, which enables the development of modular products based on common plat- forms and configurable options. This trend requires also the adoption of hybrid production and sourcing strategies towards producing modular platforms centrally, based on the participation of suppliers, distributors and retailers. As part of this trend, stakeholders are able to tailor final products locally in order to better serve local customer demand.
  • Improved workforce engagement, through enabling people to remain at the heart of the future factory, while empowering them to take efficient decisions despite the ever-increasing operational complexity of future factories. Workforce engagement in the factories of the future is typically associated with higher levels of collaboration between workers within the same plant, but also across different plants.

The advent of future internet technologies, including cloud computing and the Internet of Things (IoT), provides essential support to fulfilling these requirements and enhancing the efficiency and performance of factory processes. Indeed, nowadays manufacturers are increasingly deploying Future Internet (FI) technologies (such as cloud computing, IoT and Cyber-Physical Systems (CPS) in the shop floor. These technologies are at the heart of the fourth industrial revolution (Industrie 4.0) and enable a deeper meshing of virtual and physical machines, which could drive the transformation and the optimisation of the manufacturing value chain, including all touch-points from suppliers to customers. Furthermore, they enable the inter-connection of products, people, processes and infrastructures, towards more automated, intelligent and streamlined manufacturing processes. Future internet technologies are also gradually deployed in the shopfloor, as a means of transforming conventional centralized automation models (e.g., SCADA (Supervisory Control and Data Acquisition), MES (Manufacturing Execution Systems), ERP (Enterprise Resource Planning)) on powerful central servers) towards more decentralized models that provide flexibility in the deployment of advanced manufacturing technology.

The application of future internet technologies in general and of the IoT in particular, in the scope of future manufacturing, can be classified in two broad categories:

  • IoT-based virtual manufacturing applications, which exploit IoT and cloud technologies in order to connect stakeholders, products and plants in a virtual manufacturing chain. Virtual manufacturing applications enable connected supply chains, informed manufacturing plants comprising informed people, informed products, informed processes, and informed infrastructures, thus enabling the streamlining of manufacturing processes.
  • IoT-based factory automation, focusing on the decentralization of the factory automation pyramid towards facilitating the integration of new systems, including production stations and new technologies such as sensors, Radio Frequency Identification (RFID) and 3D printing. Such integration could greatly boost manufacturing quality and performance, while at the same time enabling increased responsiveness to external triggers and customer demands.

Within the above-mentioned categories of IoT deployments (i.e. IoT in the virtual manufacturing chains and IoT for factory automation), several IoT added-value applications can been supported. Prominent examples of such applications include connected supply chains that are responsive to customer demands, proactive maintenance of infrastructure based on preventive and condition-based monitoring, recycling, integration of bartering processes in virtual manufacturing chains, increased automation through interconnection of the shopfloor with the topfloor, as well as management and monitoring of critical assets. These applications can have tangible benefits on the competitiveness of manufacturers, through impacting production quality, time and cost. Nevertheless, deployments are still in their infancy for a number of reasons including:

  • Lack of track record and large scale pilots: Despite the proclaimed benefits of IoT deployments in manufacturing, there are still only a limited number of deployments. Hence manufacturers seek for tangible showcases, while solutions providers are trying to build track record and reputation.
  • Manufacturers’ reluctance: Manufacturers are rather conservative when it comes to adopting digital technology. This reluctance is intensified given that several past deployments of digital technologies (e.g. Service Oriented Architectures (SOA), Intelligent Agents) have failed to demonstrate tangible improvements in quality, time and cost at the same time.
  • Absence of a smooth migration path: Factories and production processes cannot change overnight. Manufacturers are therefore seeking for a smooth migration path from existing deployments to emerging future internet technologies based ones.
  • Technical and Technological challenges: A range of technical challenges still exist, including the lack of standards, the fact that security and privacy solutions are in their infancy, as well as the poor use of data analytics technologies. Emerging deployments and pilots are expected to demonstrate tangible improvements in these technological areas as a prerequisite step for moving them into production deployment.

In order to confront the above-listed challenges, IoT experts and manufacturers are still undertaking intensive R&D and standardization activities. Such research is undertaken within the IERC cluster, given that several topics dealt within the cluster are applicable to future factories. Moreover, the Alliance for IoT Innovation (AIOTI) has established a working group (WG) (namely WG11), which is dedicated to smart manufacturing based on IoT technologies. Likewise, a significant number of projects of the FP7 and H2020 programme have been dealing with the application and deployment of advanced IoT technologies for factory automation and virtual manufacturing chains. The rest of this chapter presents several of these initiatives in the form of IoT technologies and related applications. In particular, the chapter illustrates IoT technologies that can support virtual manufacturing chains and decentralized factory automation, including related future internet technologies such as edge/cloud computing and BigData analytics. Furthermore, characteristic IoT applications are presented. The various technologies and applications include work undertaken in recent FP7 and H2020 projects, including FP7 FITMAN, FP7 ProaSense, ECSEL MANTIS, H2020 BeInCPPS, as well as the H2020 FAR-EDGE initiative. The chapter is structured as follows: The second section of the chapter following this introduction illustrates the role of IoT technologies in the scope of EU’s digital industry agenda with particular emphasis on the use of IoT platforms (includ- ing FITMAN and FIWARE) for virtual manufacturing. The third section is devoted to decentralized factory automation based on IoT technologies. A set of representative applications, including applications deployed in FP7 and H2020 projects are presented in the fourth section. Finally, the fifth section is the concluding one, which provides also directions for further research and experimentation, including ideas for large-scale pilots.

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.

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.