Sensor System for SMEs
A state-of-the-art mobile sensor system makes it possible to capture data from existing processes as well as from additional sensors and transmit it via mobile communication to a database. Analysis techniques can reveal causes of quality deficiencies or identify signs of imminent maintenance.
What do customers in the SME (small and medium enterprises) sector expect from Industry 4.0? Where do users hope to see advantages? What are the tangible, concrete benefits? It is difficult to answer these questions without first investing large amounts in resources and personnel. The Lemgo-based Fraunhofer Institute of Optronics, System Technologies and Image Exploitation (IOSB) offers a practical and cost-effective solution: the developers hope to use the new INAsense sensor system to allow medium-sized businesses to achieve simplicity, transparency, control, predictability, security and flexibility in their production. Dr. Holger Flatt, leader of the Smart Sensor Systems research project at Fraunhofer, summarizes the incentive for this development: "For many medium-sized businesses, Industry 4.0 is still an abstract concept that has nothing to do with their commissions or products. Using the mobile sensor system, we hope to obtain local data, achieve transparency and identify potential or assist with locating issues. A major advantage of this is that neither in-house sensor hardware nor relevant Industry 4.0 competence must be available in the company."
The compact and mobile sensor system offers a large spectrum of technical data: infrared, vibration, pressure, distance, temperature, humidity and system performance as well as the measurement of various other physical properties. In addition, a programmable logic controller (PLC) is installed, as well as an internal computer and a gateway and an LTE router to transmit the sensor data to a secure cloud. In contrast to other similar systems, this measurement system is not just optimised for one sector and can be introduced and used directly in the current production processes. For example, in the future the system could be used to create transparency in the quality assurance process or to predict upcoming maintenance. Additionally, the knowledge acquired from the production data could be used to make machines more efficient and productive.