With the UK targeting a new frontier in circular manufacturing, a powerful combination of AM and AI will be vital in linking everything together on our journey to Net Zero, writes Julien Vaissieres of Batch.Works
It feels as if we’ve reached a critical juncture for manufacturing, one where traditional moulds and traditional mindsets no longer fit. As CEO of Batch.Works, I’ve seen first-hand how the drive for local, circular production collides with realworld manufacturing challenges.
We’re producing thousands of end-use parts every day at our London hub, working with small studios right through to large UK retailers, all looking to push beyond prototyping into on-demand, consumerready products.
But with AI rapidly transforming additive manufacturing (AM), and with government initiatives such as the UK’s new Circular Taskforce, ongoing reshoring efforts, and initiatives for AI adoption and supply chain resilience, there’s now a genuine opportunity to overcome those barriers and unlock unprecedented potential for designers and end users alike.
Manufacturing challenges
Many of traditional manufacturing’s entrenched production models are increasingly misaligned with net-zero targets and local, sustainable supply chains.
Designers and engineers crave agile, small-batch production with minimal waste, but often face cost constraints, long lead times and a shortage of domestic suppliers. That’s precisely what Batch.Works has set out to tackle with a technology platform that merges AI-driven additive processes with circular material flows, printing every part locally using recycled or renewable feedstock, and then recovering it for reprinting at end of life.
This resonates with a wave of new UK government measures, from Extended Producer Responsibility rules holding producers accountable for packaging waste, to the forthcoming Deposit Return Scheme arriving in 2027, aimed at boosting plastic recycling rates.
Put simply, there’s mounting institutional support for practical, low-carbon production solutions that don’t rely on shipping vast volumes of products across oceans.
But to ensure such visions truly scale, we need AI to boost efficiency, reliability and speed, empowering designs that are as green as they are feasible.
Breaking down siloes
Part of the solution lies in addressing the siloed nature of how we design, develop and manufacture products. Typically, there’s a cycle between a designer and an AM engineer, who painstakingly tinkers with slicing parameters and toolpaths. If something goes wrong, the cycle repeats. This is neither time-efficient nor scalable.
As 3D printing rapidly expands into high-volume, end-use territory, the question is how to ensure consistency, reliability and cost-effectiveness at scale. That’s where AI and data analytics come into play
AI can streamline the process, by spotting potential structural weaknesses, predicting print failure rates and automating slicer settings. In practice, such tools drastically reduce the trial-and-error loop. Designers can be confident that their concept will print flawlessly and efficiently, while also tracking its carbon footprint from day one.
As 3D printing rapidly expands into highvolume, end-use territory, the question is how to ensure consistency, reliability and cost-effectiveness at scale. That’s where AI and data analytics come into play.
Imagine an AI engine that has learnt from tens of thousands of print jobs how to continually finetune parameters such as extrusion temperature, infill density and print orientation. It slashes the time from concept to production-ready part, while driving down scrap rates. It can also optimise material flows, ensuring that reprocessed polymers or bioplastics remain consistent in quality after multiple cycles, crucial for functional end-use parts where safety and regulatory compliance matter.
An ever-growing dataset on real-world mechanical performance will let designers and engineers confidently specify 3D-printed components for everything from consumer electronics to retail fixtures, knowing they can be repaired on-site or recycled entirely.
From my perspective at Batch.Works, bridging design and manufacturing to meet net-zero and circular targets is impossible without AI. We cannot rely on guesswork or on the old approach of sending containerloads of identical items across the globe.
The UK has Europe’s largest design economy, worth over £100 billion, and we’re seeing that talent channelled into more sustainable, digitally powered processes.
With AI-driven AM, the results can be profound: localised, on-demand microfactories, near-zero-waste production, and products designed from the ground up for repair and re-use.
At Batch.Works, we’re already demonstrating this in our London facility, backed by over £3 million in government grants and a major partnership with E3D to scale our technology globally. We aim to make our platform accessible by the end of the year, enabling more designers to embed net-zero principles into their work.
In many ways, this feels like a new industrial revolution, merging local resilience with global collaboration and powered by the belief that we can both dream and deliver.
About the author:
Julien Vaissieres is CEO of Batch. Works, a London-based tech company pioneering scalable, circular and sustainable 3D printing innovation and actively contributing to the achievement of the UK’s Net Zero ambitions.
This article first appeared in DEVELOP3D Magazine
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