AI is driving manufacturing software development.
It took some time for me to realize the intersection points to drive a successful software team, seeing the similarities between software development and engineering. Similarities are more pronounced than differences; I think manufacturers can be inspired by software development, while also seeing the similarities with leading a successful team on the manufacturing shop floor.
In software development, just as in manufacturing, you are managing complex projects and processes, and where the outcome isn’t clear in the beginning or even in the middle of it. People, infrastructure and organization structures play key roles, and it is not always predictable to understand customer value of products or services until you engage with customers. Thus, being agile and interacting with real world feedback is as important in software development as in manufacturing engineering.
Both are different fields and yet they have similarities. With the future of automation already evolving on our shop floors, both fields are continuously being transformed. Since some years, we use Development Operations (DevOps) continuous improvements and development in software. We see how AI infused tools increase productivity for software developers. It’s important for shop floors to stay updated on the latest AI developments.
There are manufacturing customers with a large amount of annual engineering changes, resulting in significant human hours spent on these processes—largely due to a lack of standardization and reliance data mapping and on file-based integrations. Leading manufacturers will in the future apply a software-first approach and hardware-second.
Shop floors using AI for data decision-making
For some time now, modern software development has embraced the cloud, a new generation of user-friendly tools, as well as rich analytics with real-time operational data enables data-informed decisions to enable a pipeline of continuous improvements.
This new generation of manufacturing tools frees up more time and space to tackle creative and challenging tasks.
With the introduction of Generative AI in software development, documenting code functionality for maintainability can be completed in half the time.
For example, writing new code in nearly half the time in some languages, and optimizing existing code (e.g., code refactoring) - and this is just the start.
Additionally, in my opinion it's about respecting both domains for their capabilities to deliver value to an organization.
For example, CNC machines have more dependencies such as tools, machines, fluids, and materials. Then, when we look at the successful strategies from a connected field like software development, we can apply them and make the manufacturing techniques and processes better.
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