Flexibility
Glossary page
Flexibility refers to the ability to respond promptly to various requirements. In modular production, flexibility can occur at different points. For example, there can be flexibility in production, within a module, or related to tasks. Quantity flexibility is the ability to quickly vary the output quantity. Production flexibility involves changing the type within an existing part mix, while product flexibility involves adding new parts to the part mix. Flexibility related to system design includes machine flexibility, material handling flexibility, process flexibility, and extension flexibility. Operational flexibility relates to the variety of possible production methods, while routing flexibility refers to the variety of possible routes through a production system for consistent results.
Catena-X Automotive Network e.V.
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Build & Operate: From Kubeapps to Devtron
When VMware deprecated and archived Kubeapps, the open-source Helm application manager embedded in T-Systems Build & Operate, we had a choice: stay on unsupported software or find something better. We chose Devtron, an open-source Kubernetes management platform that gives dataspace operators one control plane for application delivery, infrastructure, security and observability. This article explains why Kubeapps reached the end of its life, what Devtron brings to the Build & Operate operation toolkit, and how the transition runs in two phases without interrupting a single running service.
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Mohamed Radwan
Sep 29, 2026
Connect & Integrate: Simplifying certificate management with AI
Connect & Integrate brings the T-Systems AI power within the solution to support organizations scale up and become efficient in their business workflows within Catena-X. The cross-use-case AI layer sits at the intersection of data preparation and exchange as a business enabler directly within the workflows.
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Tushar Yadav
Aug 03, 2026
IDSA’s Dataspaces and AI: Our input from applied Physial AI in RoX with dataspaces
The IDSA position paper "Data Spaces and AI" argues that the coordination problems facing agentic AI — identity, trust, access control, governance and provenance across organizational boundaries — are the same ones dataspaces already solve for cross-company data sharing. Rather than reinventing them for autonomous agents, the peer-to-peer logic behind standards like ISO/IEC 20151 can transfer directly to agent-to-agent interaction. T-Systems contributes a concrete proof point: RoX, a German consortium where competing robotics players and institutes such as DFKI and DLR share a sovereign data foundation for AI-based robotics. Built on Tractus-X and aligned with IDSA and Gaia-X, it already powers live robotic cells and is now extending that governed data supply to an agentic layer — showing in practice what the paper argues in principle.
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Chris S. Langdon
Jul 21, 2026