Industrial tools, machine tools, and manufacturing machinery, as well as numerous workpieces generated in the production process, and production and service processes with a connection to relevant information systems are already continuously generating large volumes of data.
These data are collected and bundled in so-called ‘data clouds’ at the company. The problem is ensuring that an exchange of data between manufacturing companies, machine manufacturers, or logisticians for service development is carried out using a simple and secure procedure.
Project Basis
This is where the smart service factory joint project will provide assistance and ensure that all the gathered knowledge is made available in the cloud in a secure manner and according to customer requirements.
The aim of the project is to generate new innovations, product ideas, and in particular services that are closely related to production and to organise these together in a productive and professional manner. This means, for example, that a maintenance company could acquire the product knowledge about machine components in an encrypted form, and pay for this knowledge upon each use. This knowledge will then be offered in addition to further knowledge from other component manufactures for the preventive maintenance for an entire machine.
Generating Values
The company is a project partner alongside Friedrich-Alexander University Erlangen-Nürnberg (FAU), the Fraunhofer Institute for Integrated Circuits (IIS), with its Nuremberg-based Fraunhofer working group for Supply Chain Services SCS as partner, and Siemens.
The project is part of the research programme ‘Innovations for the production, service, and work of tomorrow’ that the German Federal Ministry for Education and Research (BMBF) is promoting the development of digital services and business models from data from industrial production.
According to Dr Dennis Arnhold from Digital Factory production processes: “Data have become ‘the new gold’. How we dig it up and use it in a sustainable manner remains unclear, in particular when the data are to be used across the company. With the new project we also want to develop standards and methods for this purpose. Furthermore, the value that can be generated from the obtained data must also to be determined. It must always be ensured that the valuable data are used in a safe and transparent manner.”
Real Load Data
How much are machines and their components actually utilised and how long will they hold up? With the measured load data and the actual load spectra determined from it, these questions can be determined for the first time with a machine tool in volume production.
The studies led to two new data-based services: The calculation of the remaining useful life of rolling bearings on the basis of real load spectra and automated rolling bearing diagnosis, which was realised with intelligent processing of oscillation data. The continuous calculation of the remaining useful life of rolling bearings opens up the following possibilities:
• Active control of machine utilisation with respect to predictive maintenance and repair
• Greater utilisation of individual axes and whole machines
• Needs-based maintenance intervals on the basis of real loads and
• The use of real field data and load spectra for design optimisation and re-engineering of machines by the manufacturer.
The engineers are also implementing the FAG ProCheck, a conventional condition monitoring system that also offers optional collision detection. This is about being able to evaluate the severity of a collision in the future and creating a connection between the collision and possible initial bearing damage.
The plan: This system is intended to make recommendations available to the operator in the future as to whether to continue operating the machine after a collision, whether to reduce the performance or even whether a maintenance team must be requested.
Additional Research Projects
These installed and integrated technologies and concepts have created a nucleus from which further developments can grow. Most important here are the unused potentials that result from the standardised access possibilities, transparency and the processing algorithms of the data. The possibilities of generating added value from the ‘field data’ for various interest groups have as such not been exhausted by any means. In the coming months and years the company will push additional research projects, including:
• The correlation of operating forces with quality characteristics and process parameters,
• A parts-related and machine-related energy performance certificate and
• Process simulation in advance as a supplement to process monitoring, key word: digital twin.
Dipl.-Ing. (DH) Roberto Henkel, director of high-precision bearings lead segment in Höchstadt, remarked: “Our overall goal is to digitalise the value flow of the machine from the horizontal, i.e. accelerate the upstream engineering process and reduce the time to the first cut, as well as include additional machines, systems and production cells in the digital cycles.”
APMEN Sept 2016, News
