{"id":40540,"date":"2026-06-17T19:20:33","date_gmt":"2026-06-17T17:20:33","guid":{"rendered":"https:\/\/hitech.at\/auf-dem-weg-zur-autonomen-software\/"},"modified":"2026-07-27T13:15:26","modified_gmt":"2026-07-27T11:15:26","slug":"toward-autonomous-software","status":"publish","type":"post","link":"https:\/\/hitech.at\/en\/toward-autonomous-software\/","title":{"rendered":"Toward Autonomous Software"},"content":{"rendered":"\n

When Manufacturing Execution Systems (MES) are used in large production lines, they must be customized to meet the specific needs of the customer and the manufacturing process. “Typically, configuration takes several months due to the enormous complexity of such systems,” says Vladimir Zahorcak of the Siemens Research Department. Configuration is either handled by the customers themselves using their own staff, or the task is outsourced to an external integrator. Both approaches have drawbacks, primarily because the configuration process typically also requires software programming to adapt the system to specific needs, which demands a high level of expertise. This entails a significant time commitment and places high demands on employees, or represents a financial burden for system integrators that should not be underestimated.<\/p>\n\n\n\n

Self-evolving software is the technology that is expected to drive progress in this area. Thanks to its implementation, the time required for configuration could soon be cut in half and the process could become significantly more efficient. “The plant operator specifies how it should operate,” says Zahorcak, “for example, you can set the production line to be optimized for maximum energy efficiency.” The entire complex MES configuration process must now be adapted to this requirement, which currently still has to be done manually.<\/p>\n\n\n\n

Self-evolving Software: Autonomous Adaptation to Individual Requirements<\/h2>\n\n\n\n

The Vienna-based, nine-member research group Scalable & Resilient Architectures, led by Vladimir Zahorcak, is ensuring that this concept becomes a reality. It is part of Siemens’ global Software Systems & Processes technology area. “We’re conducting research on the future trends in software architecture,” says the expert, “and right now, we’re focusing in particular on what’s known as ‘self-evolving software.’” What does that mean? “Our goal is for software to adapt autonomously to users’ individual needs in the future,” explains Zahorcak. The Vienna-based research team is part of a global research and predevelopment unit with a staff of just over 200. Saurabh Narayan Singh coordinates the research groups on an international level and highlights their importance: “We see this as a truly major topic for the future, one that we are driving forward in a decisive way — not least thanks to our collaboration with renowned universities.”<\/p>\n\n\n\n

Back to self-evolving software and the added value it will deliver to customers. In the future, innovative software will handle the task of customizing MES systems — such as Siemens’ Opcenter X — to meet the needs of customers and manufacturing operations. Using AI agents, it will adjust parameters throughout the entire plant in such a way that efficiency targets, for example, are met — and it will do so completely autonomously. “SCADA systems and PLCs — that is, programmable logic controllers that run directly on production machines as control systems — are included,” says the research group leader.<\/p>\n\n\n\n

Self-evolving software will therefore solve two problems: first, configuration, and second, the integration of various Siemens products — and soon, external products as well. Optimizing large production lines for energy efficiency is just one example; other KPIs include maximum productivity, speed, or service life — and combinations of these are also possible. “One challenge and a central focus of our research activities is AI self-awareness — that is, teaching the agents what they must do, what they must not do, and where the boundaries lie,” adds Singh, who heads the global division. The benefits of AI are not limited to large facilities: Medium- and small-sized manufacturing companies can also benefit from self-evolving software solutions, as these solutions are particularly well-suited to achieving sustainable cost reductions and accelerating the configuration and commissioning processes.<\/p>\n\n\n\n

\"\"© Siemens<\/span><\/span><\/figure>\n\n\n\n

Using AI agents, this innovative software autonomously configures and optimizes systems
to meet target production KPIs.<\/p>\n\n\n\n

The software systems are currently being tested step by step on virtual plants — a process that requires a great deal of effort — so that customers can benefit significantly from their use in their production lines in the future. And there are other research approaches as well. Vladimir Zahorcak: “One example of this, in addition to self-configuration, is the concept of self-healing — that is, how does the machine react when the AI agents make a mistake?” And ultimately, it leads to the highest level: complete autonomy. “Today, everything goes right in nine out of ten attempts. “But this one experiment, which is encountering problems, is representative of the research topics that still lie ahead of us.”<\/p>\n<\/body><\/html>\n","protected":false},"excerpt":{"rendered":"

Configuring large production facilities is a challenging task. 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