Achieving manufacturing simplicity through AI
In the complex world of manufacturing and production, achieving simplicity in any process is often easier said than done. This is especially true for cutting-edge technologies that require extensive expertise in both the new technology and the application domain. Bringing artificial intelligence into industry is no different, traditionally requiring experience in data science as well as knowledge of fields like simulation, design or factory operations. However, as with all technologies, as AI continues to develop the barrier to entry will lower and, in the future, AI itself will become a powerful tool for making technology more accessible.
In a recent podcast, Ralf Wagner, Senior Vice President of Data Driven Manufacturing at Siemens, broke down the ways AI is being seamlessly integrated on the shop floor, offering AI functionality in areas that have traditionally lacked data scientists to implement it. Beyond that, he also explores the applications of the Industrial Copilot and its unique ability to simplify access to complex tools
Check out the full podcast here or keep reading for some of the highlights of that conversation.
Balancing pretrained and finetuned models
One of the key challenges of applying AI in the past has been training. AI models require training to understand their tasks which has traditionally required extensive, curated datasets and data scientists to perform the training. Ralf highlights how, to bring AI into the industrial mainstream, the goal must be to make the benefits clear while the AI and setup process are as seamless as possible.
By making sure AI models are ready to use either from the moment they are deployed or by simply selecting a few weeks of data in an intuitive interface, the barrier to bringing this type of advanced technology into industry is significantly lowered. This is especially true for manufacturing, which tends to be slower in adopting new technologies and lacks the strong data science backbone to deploy AI from scratch.
While pretrained models are important in driving adoption, allowing customers solutions is important as well. Ralf explains how striking this balance is important within Insights Hub’s AI strategy, ensuring that while their AI solutions are quick and easy to deploy, they also support further training when it makes sense to take their capabilities to the next level.
Applying the Industrial Copilot
Deploying advanced technology, including AI, is getting easier every year and AI itself may be one of the tools that assists that. AI systems like the Industrial Copilot make accessing critical information and interacting with complex tools easy and accessible to experts and non-experts alike, speeding up tasks and offering solutions.
Artificial intelligence can not only help with data analysis, reaching the right decision faster, but also in automating planning and tasks with powerful AI agents. Ralf explains how Copilot systems can employ all these techniques, combined with the data and connections of Siemens Insights Hub to improve the lives of users on the manufacturing floor, increasing efficiency while also remaining transparent.
Transparency is important when it comes to AI on the shop floor, where decisions often have expensive consequences. By making sure AI systems are grounded in real information and explicit about where their suggestions come from, not only do they help highlight key information to users but also build trust in the AI at the same time as users are able to see AI suggestions lining up with their own assessments.
As a whole, an Industrial Copilot can help ease the adoption of new technologies into any setting, be that manufacturing or design, by shortening learning times and making data and decisions more accessible. In the future, AI-powered wizards may even help configure advanced AI solutions that connect machines, people and the Digital Twin to enable a greater degree of efficiency and autonomy in the production process.
Artificial intelligence is here to stay but the key to widespread adoption is, as always, simplicity. In a critical setting like a shop floor, the value of an AI solutions must be as clear as the system itself is easy to setup and transparent to the end user. By developing AI solutions with these constraints in mind first and foremost, it will help smooth the adoption process and bring AI to where it can have the greatest impact.
To find out more, check out the full podcast here.
Siemens Digital Industries Software helps organizations of all sizes digitally transform using software, hardware and services from the Siemens Xcelerator business platform. Siemens’ software and the comprehensive digital twin enable companies to optimize their design, engineering and manufacturing processes to turn today’s ideas into the sustainable products of the future. From chips to entire systems, from product to process, across all industries. Siemens Digital Industries Software – Accelerating transformation.
