Smart Sensor and Production Systems for Industrial IoT

Short Description:

The progression of digitalization in production is driving the Fourth Industrial Revolution (Industry 4.0) significantly. Thus, the gap between virtual and real world continues to decline and equipment involved in the production plants, machines, components, sensors or tools become identifiable and linked devices in an Industrial Internet of Things (IIoT).
The presented Roadshow Trail “Smart Sensor and Production Systems for Industrial IoT” aims to present innovative solutions for consistent and comprehensive digitization in production across the entire value chain. Here, the main focus of the various aspects of the IoT is on sensor-based delivery of device data, their analysis and evaluation, and finally the feedback of production-relevant information. With the visualization of devices in Virtual / Augmented Reality, this trail presents scenarios of end-to-end digitalization.

Coordinator:

Dr. Jan Reimann, Fraunhofer Institute for Machine Tools and Forming Technology IWU

Target Group(s):

    • Sensor and actuator users
    • Manufacturing companies
    • System integrators
    • Industry 4.0 users
    • Start-ups

Partner from Research, Industry:

Partner Expertise Contact Person
Fraunhofer IWU Production Systems, data & Information management , energy efficiency, Industry 4.0, Robotics, Industrial IoT Dr. Tino Langer,
Dr. Jan Reimann,
Ken Wenzel
Fraunhofer ENAS Sensor, actuator and system development, Industrial IoT Dr. Martina Vogel
N+P Informationssysteme GmbH Industry 4.0, augmented reality, Industrial IoT Björn Schuster
Agilion GmbH Industrial Supply Chain Tracking, Radio localization, Industry 4.0 Andreas Werner
AMAC ASIC- und Mikrosensoranwendung Chemnitz GmbH System & ASIC design, microtechnology, microelectromechanical Systems (MEMS) Dr. Claus Dittrich
Chemmedia AG Knowledge Transfer, KnowledgeCloud, E-Learning, training Lars Fassmann
Chemnitzer Wirtschaftsförderungs- u. Entwicklungsgesellschaft mbH Business promotion, location development Sören Uhle
EDC Electronic Design Chemnitz GmbH Development, production & test of discrete, integrated circuits, control, Sensor and evaluation electronics Dr. Steffen Heinz
Fraunhofer IIS/EAS Integrated sensor interfaces for MEMS, complex signal processing, smart evaluation algorithms Andreas Brüning
Institut für Werkzeugmaschinen und Produktionsprozesse (IWP), Technische Universität Chemnitz Machine tools, production processes, Virtual / Augmented Reality, Industry 4.0, Industrial IoT Dr. Philipp Klimant
Technologie Centrum Chemnitz Promotion of young enterprises, start-up support, business development Jens Weber
Zentrum für Mikrotechnologien ZfM Micro and nano systems (sensors, Actuators, arrays), design of components and systems Prof. Dr. Karla Hiller

Value Proposition:

Smart production systems do not only aim for a high level of communication or a self-sufficient energy supply by connecting electronic components, micro and nano sensors and actuators with interfaces. But those systems are increasingly equipped with the ability to communicate and cooperate. Their connectedness thus forms an industrial IoT and the machines, components and sensors etc. involved in the production processes and production systems are regarded as networked devices. These form the basis for IoT in the Industry 4.0 application area. In addition, parts of it can also be integrated into other IoT applications (mobility, society, energy or healthcare).
In this trail, we focus on digitization in production and present demonstrators covering the entire value chain:

    • Identification of the customer requirement,
    • Proposal of possible concepts,
    • Feasibility to capture customer-specific parameters via sensors,
    • Development of customized sensors,
    • Integration into production processes,
    • Collection and analysis of data,
    • Intelligent information acquisition from the data (Smart Data),
    • Preparation and visualization of data,
    • IoT -based control and monitoring of the customer’s production process

Character:

This trail is divided into two phases. Phase 1 implements a pure teaser trail. For this, demonstrators of the Fraunhofer Institute IWU and ENAS, as well as the N+P Informationssysteme GmbH (N+P) are presented, which will take no more than half a day. The other partners (see section 3) are involved in the construction and development of the demonstrators, are technology suppliers or contribute to the integration of the demonstrators into real production processes. The main foci of this phase are on the presentation of individual aspects of the value chain and the networking of the industrial devices. In addition to the demonstrator inspection, guests also have the opportunity to take action. The focus is on discussion and the bilateral exchange of knowledge in workshops, Design Thinking Sessions are planned to creatively find innovative solutions for current issues of Roadshow participants. Based on the results of already carried out workshops, events, current research and projects, this trail will constantly be evolved.

Thus, in Phase 2 the trail will be expanded from a pure teaser trail to a teaser and intensive trail. The demonstrators from Phase 1 will exemplarily be taken in a larger context and combined in such a way that all parts of the value chain can investigated intensively over several days regarding one specific production scenario. Thus, the specific needs of the visitors are attended to and the trail program can be extended demand-driven and based on the target group.

Demonstrators:

Fraunhofer IWU

E3-Forschungsfabrik
In the E³-Forschungsfabrik, human-robot interaction, various forming machines and a fully networked production hall are presented, which illustrates the Industrie 4.0 stack of the Fraunhofer IWU:

    • Smart Devices (e.g. sensors) that serve as data providers,
    • Linked Factory as a central component and “data hub” for the management of all data,
    • Smart Analytics for analyzing data and transforming big data into smart data
    • Smart Wearables for the presentation of information,
    • Tracking & Tracing for object identification and localization,
    • Integration in the IT infrastructure, which is constantly growing.

Sheet metal forming
The intelligent model production line for hot forming is a demonstrator for “Machine Learning for Production”. It consists of a novel contact heating system, one Servo spindle press with freely programmable path-time behavior, various (tempered) forming tools, an automated workpiece handling system and an innovative system for trimming the manufactured part. As an alternative to the contact heating system, the tempering of the semi-finished sheet products can also take place in a chamber furnace integrated in the line (statements on efficiency / production line design). The plant is automated and equipped with extensive measuring technology to ensure reproducible process conditions based on measured process variables.

Monitoring and control of manufacturing processes
A key topic at the IWU is the monitoring and control of manufacturing processes. For example, the measurement of the thermal influence of the peripheral zone can be measured during grinding. These measurements make process control during grinding possible. Within a research project the integration of newly developed measuring method in the laboratory was realized. Thus, the following potentials can be achieved for the user:

    • Reduction of grinding time, increase in productivity
    • Increase of the dressing interval, reduction of non-productive time and tool costs
    • Improvement of process reliability and Quality

Applications of process-integrated sensors
The knowledge of the current process status is an essential prerequisite for the control of manufacturing processes. Established approaches usually rely on signals from the machine control or on sensor information from the machine periphery. However, this often does not provide adequate information quality.

Therefore, the Fraunhofer IWU develops sensor solutions that capture information from manufacturing processes very close to the process which are then passed on to the process control unit in real time . Novel physical principles such as dielectric elastomers or piezoelectric thin films are used for the comprehensive integration of the sensor technology. Complemented by wireless communication and intelligent data processing or evaluation, the sensors function as cyber-physical components and form the basis for the automatization of complex manufacturing processes. Examples are a sensor system for capturing the printed image during forming as well as a sensor for cutting force measurement during machining.

Fraunhofer ENAS

Sensors for motion, navigation, position and vibration
In digital production, but also in robotics, sensors are increasingly needed for the condition monitoring of systems, for the detection and monitoring of movements, for vibration detection with high bandwidth, for low-energy motion detection and for navigation tasks.
In the laboratory “Precision Metrology” inertial sensors and magnetic field sensors are demonstrated.

    • For inertial sensor technology, the focus is on high-precision silicon-based sensors for measuring acceleration, vibration, inclination and rotation rates. The entire value chain is mapped together with the associated partners.
    • Magnetic field sensors are used to uniquely determine the position, position or rotation of components, workpieces and materials.

Sensor system for monitoring infrastructure
Sensor systems not only acquire measured data, but also evaluate this data and send it to the base station or control center in order to control processes from there.

    • The condition monitoring of sealing rings or greases helps operators to reduce plant and machine failures and to adapt service intervals corresponding to wear behavior. Exemplary systems for the monitoring of lubricating greases are demonstrated.
    • High-precision inclination sensors are demonstrated as a monitoring structure of high-voltage. The autonomous sensor nodes are installed along the overhead line and contain inclination sensors and current and temperature sensors. Acquired data are recorded by an ultra-low power microcontroller and sent wirelessly along the overhead line to a base station.
Figure 1: Two sensor nodes of the autonomous sensor network for condition monitoring of the high voltage line AASTROSE collect during a field test data on 110-kV-high voltage lines. The system consists of several sensor nodes, which measure the slope, temperature and electricity flows of the lines and pass the data to the base station. ©Sven Voigt/Fraunhofer ENAS
Figure 2: Integration of sensors with a self-sufficient energy supply in a Simmering. ©Fraunhofer ENAS

Material and structure sensors for stress, strain, overload, humidity
The material and structure sensor technology comprises various adapted systems. The sensors for stress, strain, and overload (crack and fracture detection) are based, among other things, on silicon technologies. The nanocomposite-based overload sensors and humidity sensors use thin layers of organic materials with embedded nanoparticles. An integration in fiber composite materials is possible.

Example: Microscopic damage can form in a fiber-reinforced plastic and remain undetected over a period of time. Rigidity and strength losses are the result and lead to failure in extreme cases. One remedy is for example a multi-layered sensor film which is coated with fluorescent nanoparticles. The film changes its brightness under load and stores this state for a certain time. Thus, defects can be detected early on.

Figure 3: Martin Möbius (l.) and Jörn Langenickel (r.) from the Center for Microtechnologies of the Chemnitz University of Technology demonstrate the fluorescent effect of a sensor layer based on Quantum Dots (nanoparticles) which have been integrated into a fibre composite. Through mechanical exposure on the piezoelectric layer carriers are generated which influence the fluorescent effect of the Quantum Dots. Such sensor layers could be integrated into rotor blades of wind turbines to indicate mechanical exposure and associated damages. ©Conny Schubert/Fraunhofer ENAS
N+P Informationssysteme GmbH

Augmented reality-based services in cyber-physical production systems
This demonstrator will show how intelligent sensors independently detect errors or disturbances. Intelligently linked information via ERP, MES; maintenance, plant and building management software allows the automated planning of upcoming service tasks or maintenance without production downtime. Using state-of-the-art technologies, a cross-device workflow (PC, mobile end devices, SmartWatch, Augmented Reality Microsoft HoloLens glasses) can be started to ensure the fast processing of upcoming tasks.

Figure 4: Presentation of the Pareto-Analysis of a machine via AR-glasses Microsoft HoloLens, ©N+P Informationssysteme GmbH
Figure 5: Presentation of machine information in preparation for a checklist-led maintenance via AR-glasses Micorsoft HoloLens, © N+P Informationssysteme GmbH

Current Projects:

Opportunities for Projects and Funding Instruments:

Public funding instruments, such as:

    • SAB InnoTeams
    • BMBF KMU Innovative
    • ZIM

Services in industrial projects:

    • individual Research and development projects
    • direct orders
    • studies
    • consulting

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