Using the asset administration shell to integrate machine data uniformly for integrated maintenance and production planning – researchers at the Institute of Production Engineering and Machine Tools (IFW) are working on this goal in cooperation with Lauscher Präzisionstechnik GmbH, the MES provider Fauser GmbH, the digitization experts at Seitec GmbH and the Chair of Integrated Automation (LIA) at Otto-von-Guericke-University Magdeburg.
Planning machine tool maintenance with foresight
Many SMEs carry out purely preventive maintenance planning. Machine tool failures between defined maintenance intervals repeatedly lead to short-term and unplanned production downtimes. This is also due to the fact that usually only selected machine components are part of the maintenance plan. This results in coordination efforts due to the rescheduling of orders and, under certain circumstances, delays in delivery dates.
At the same time, predictive maintenance is the central element of efficient production planning and control (PPC). The objective of predictive maintenance is to forecast maintenance requirements as correctly as possible and to avoid unplanned machine tool downtime. Due to the increased plant availability, the long-term competitiveness of SMEs is enabled by efficient maintenance and production planning.
Lack of data for machine-specific maintenance forecasts
However, for the correct prognosis of failures, an end-to-end, digital networking between machine tools and higher-level control systems is essential, so that a sufficient database of condition-related data is available. Due to limited resources and the often uneconomical retrofitting of older inventory machine tools, SMEs can only carry out efficient maintenance and consequently production planning to a limited extent.
Due to maintenance at fixed intervals, there is a risk of machine failures outside these intervals. As a result, machine repairs are only carried out after a machine component has failed, resulting in short-term and unplanned production downtime.
Asset administration shell enables standardized integration of machine data
Asset administration shells (AAS) enable the management of so-called assets. In industrial production, assets can be manufactured products, for example. Assets include also machines and systems or machine components such as motors or drives. AAS consider assets over their entire lifecycle and create cross-manufacturer interoperability. When considering an engine, this includes related assets such as CAD files or bills of materials. AAS also enable communication between assets through a standardized interface and specification or language. Due to the combination of data and information on an asset (machine, workpiece, machine element), AAS are a kind of implementation of the digital twin or provide the basis for deriving digital twins.
Joint project BaSys4iPPS: Maintenance and production planning
The objective of the BaSys4iPPS joint project is to develop a method for integrated maintenance and production planning for inventory machines. Optimized maintenance and production planning should enable a significant reduction in unexpected production downtimes and a significant increase in planning reliability.
With the help of the implementation of AAS and an extension, a standardized machine data acquisition (MDE) of Lauscher’s machine tools will be realized. The AAS is used to uniformly describe the properties and capabilities of machine tools. It also provides, for example, information about available machine components and associated interfaces for data acquisition. The information provided is used to implement a counter for machine component operating hours, such as the spindle. With the help of the counter, maintenance orders can be scheduled in a focused manner.
Objective: Condition-based maintenance of machine tools
In the future, machine components that are not currently part of the maintenance plan will also be considered. In addition, further machine data is to be used to enable condition-based maintenance. The AAS enables communication between digital twins of the machine tools and the Manufacturing Execution System (MES).
The acquired machine data will be used by IFW to improve maintenance planning at Lauscher Präzisionstechnik GmbH. In a first step, the operating hours counter for numerous machine components will be implemented. Currently, IFW is developing a method for determining the failure probabilities of machine components, which will be taken into account in production planning.
