Factory-X

As industrial manufacturing becomes increasingly digitalised, companies are facing a wide range of challenges: fragmented data landscapes, heterogeneous IT/OT systems and a lack of standardisation are hindering the consistent flow of information along value and supply chains. At the same time, increasing demands for sustainability, CO₂ transparency, energy and resource efficiency, and growing uncertainties in global supply chains are leading to increased complexity in the planning, operation and maintenance of plants. Pilot projects often remain isolated due to a lack of cross-company and cross-system scaling. Against this backdrop, the mechanical and plant engineering industry needs an integrated infrastructure that addresses interoperability, data sovereignty, horizontal and vertical networking, and standardised data models in equal measure. This is the only way to ensure efficiency, transparency and competitiveness in the long term.

Objectives

The objective of Factory-X is to establish an open, collaborative data ecosystem for machine and plant manufacturers as well as operators of industrial manufacturing environments. To this end, a technical platform is being developed that enables scalable, cross-company data exchange and features a central kernel that provides basic services, common standards and end-to-end interoperability. The focus is on the ability to share data securely and confidently across system and organisational boundaries. At the same time, the project aims to ensure both horizontal integration along the entire value and supply chain and vertical consistency right down to the shop floor. The aim is to link engineering, operational and production data throughout and make it possible to map it in a uniform digital infrastructure. The IFW considers order processing and energy and load management to be use cases here.

Benefits

• Increased flexibility and efficiency through digital marketplaces
• Reduced maintenance and operating costs and higher plant availability
• Development of data-based solutions to reduce energy consumption and optimise load management in production

Approach

TP 2.6 - Manufacturing as a Service (MaaS)

As part of the Factory-X project, IFW is developing a method for automating order processing. This process is known as CAM automation. IFW is developing a programming interface that will allow an application to be connected to the design program.  Firstly, relevant features are extracted from the 3D model of the order. Features are defined as product characteristics that describe, for example, the workpiece geometry and manufacturing characteristics such as tolerances. Using this information, it is possible to automatically derive the necessary process steps, machines and tools. The data is stored in an administration shell of the product. The administration shell (Asset Administration Shell, or AAS) is a standardised format developed by the IFW as part of Factory-X. This information can then be used to calculate the costs of the order. This approach enables the economic viability of the order to be assessed prior to the commencement of production. The knowledge gained from CAM automation can also be used to optimise capacity planning. The IFW is developing an algorithm that can be used to evaluate orders before they are accepted and determine whether sufficient capacity is available for the rush order. Should the costs of retooling exceed the profit generated by the rush order, a rejection of the order is to be recommended.

TP 2.7 - Autonomous Operation as a Service (AOaaS)

Certain operations, such as the production of gear teeth or polygons, require a significant amount of programming effort to create the NC code. Technology cycles have the potential to reduce the effort required. Technology cycles already contain sub-steps and requirements for specific operations, such as gear shaving. As part of the project, IFW is developing an AI assistant that performs an economic analysis of the technology cycles. The AI assistant assesses whether utilising a technology cycle during manufacturing results in enhanced machining efficiency and productivity compared to scenarios without such cycles. The potential cost reduction is then calculated.

TP 2.9 – Energy Consumption and Load Management

As part of the project, an analysis of existing energy and load data at machine, plant and factory level will be carried out first to identify any gaps in measurements and data. Building on this, digital twins of key energy consumers will be modelled, and soft sensors will be established to record previously unrecorded variables. Next, forecast models will be developed to predict future energy requirements and peak loads. Active load management will then be implemented to enable control concepts for shifting loads, utilising flexible production capacities, and increasing energy flexibility for grid and balancing group participants. Meanwhile, an infrastructure based on open standards such as Asset Administration Shell and OPC UA will be developed for the data room, ensuring data sovereignty and enabling the cross-company and cross-system exchange of energy data.

Are you also interested in a cooperation project?

Contact Jana Pralle via email at Pralle@ifw.uni-hannover.de or by phone at +49 511 762 5997.