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Scaling is not synonymous with growth. The fundamental difference is that scaling implies expansion without a corresponding increase in resources, particularly human resources. Too often, additive manufacturing operations expand linearly, requiring a proportional increase in workforce, which limits scalability. Overcoming this challenge demands automation at every stage of the process, from data preparation and machine operations to optimal scheduling and postprocessing. The entire ecosystem must work together to achieve this, embracing greater openness and collaboration. This includes increasing interoperability between software and hardware, expanding material options, and granting access to key machine parameters. At Materialise, we have taken a bold step in this direction by opening up the algorithms behind Magics, our flagship software for data and build preparation. By enabling users to create fully customized workflows, we help manufacturers optimize their processes for efficiency and scalability.
A key obstacle to scaling up is the availability of a qualified workforce. Additive manufacturing remains a highly specialized field, requiring skilled professionals to operate and optimize processes. To facilitate broader adoption, the industry must demystify additive manufacturing by sharing knowledge and best practices, particularly about what works well in real-world applications. For example, Layer Analysis has proven valuable in quality and process control, providing deeper insights into the printing process. Emerging technologies like AI will further enhance process understanding, enabling operators to make informed decisions with less reliance on highly specialized expertise. By lowering the barrier to entry for skilled labor, we can make scaling additive manufacturing more achievable.
Successfully scaling up also depends on applying lean
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