Industrial mass customisation & the role of AI


Why is the traditional one-size-fits-all approach in manufacturing giving way to a more nuanced strategy? Today, the old saying ‘customer is king’ is more alive than ever. Mass customisation reflects changing customer demands, but it is also a strategic response to the dynamic market forces at play.

With that in mind, manufacturing companies and machine builders need to think about the best way to tackle this challenge. How can they achieve mass customisation without ramping up costs or slowing down production?

The growing significance of flexibility

The ability to swiftly adapt to changing demands and seamlessly customise production lines has become a huge business advantage. No wonder manufacturers seeking automation solutions are increasingly prioritising flexibility in their production processes. 

Technological hurdles

Mass customisation isn’t a dream anymore – it’s the competitive edge of many manufacturers today. At the same time, it presents machine builders with a clear challenge. They are the ones that have to make it happen. Ensuring continuous innovation for their customers while minimising disruptions requires a new approach. 

That’s how mass customisation is reshaping the way machine builders envision and engineer their solutions. If the automation set-up has to be adapted for every small batch, manufacturers – and their customers – will not get the swift and affordable result they are expecting.

Ready for continuous change

AI is the answer to be successful in this dynamic reality. Imagine offering machines that manufacturers can tailor to their own continuously changing needs without breaking a sweat. By integrating AI into their machines, machine builders can make mass customisation a breeze for manufacturers. It enables machines to learn and evolve, paving the way for highly flexible and responsive production environments. From fine-tuning parameters to introducing new product variants, the possibilities are endless.

Real-time decision making

AI algorithms empower machines to make real-time decisions, optimising production processes on the fly. This agility ensures that customisation doesn’t come at the cost of efficiency. Pricing and efficiency are obviously crucial, but it is definitely also about fostering loyalty, awareness, and a distinctive market presence for machine builders and their customers.

From products to solutions

By integrating AI capabilities, you’re not just creating machines; you’re crafting solutions with state-of-the-art performance that are fully self-serve. The end-users, whether they are operators on the factory floor or workers in a greenhouse, can adapt the solutions for the task at hand and troubleshoot to avoid downtime. Embracing this transformation is critical to enjoy first-mover advantage in a world of new possibilities. The winners will not just be those that hit the market first, but the ones that manage to scale out and achieve critical mass.

Operationalise and scale AI in automation

Nobody disputes the potential of AI in automation. The sad truth is that machine builders often lack confidence in operationalising and scaling it. It is understandable, as more than half of AI projects never become more than a proof-of-concept. This is mainly due to a great misunderstanding of AI.

 If you’ve trained a model, and it’s getting good results, the work isn’t finished. You’re just getting started. The hard part is actually maintaining the AI, in a continuous cycle of developing, deploying, and retraining AI models. Simply put: if you can’t repeat the initial success of your POC over and over, you don’t have a solution. You have a demo.

Fast-forward to Vision AI-powered machines

As a machine builder, you build machines that need to perform 24/7 with perfect reliability: that’s an impressive feat. But what if we told you these machines can do even more. They hold the potential to change entire industries. By adding Vision AI to them, you upgrade your machines to smart solutions that take automation to an entire new level. This will drastically reduce your time-to-revenue for AI-powered solutions. 

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