Additive Manufacturing Process Optimization
Summary
Additive manufacturing (AM), commonly known as 3D printing, builds components layer by layer from digital designs. Process optimization in AM seeks to enhance part quality, reduce build time and material waste, and lower overall production costs. Key levers include the selection and tuning of machine parameters (such as laser power, scan speed and layer thickness), the determination of optimum build orientation to minimise support structures, and the grouping of parts into batches or nests to maximise machine utilisation. Advanced algorithms—from mixed integer programming to metaheuristics—are increasingly employed to address complex scheduling, nesting and orientation problems. Concurrently, data-driven approaches, including machine-learning models, are applied to predict defects and adjust process parameters in real time. Together, these strategies drive improvements across aerospace, automotive, medical and consumer-goods industries, offering bespoke production with faster lead times and reduced environmental impact.
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Additive Manufacturing Process Optimization publication trend
The graph below shows the total number of articles in additive manufacturing process optimization across all publications each year (not limited to Nature Index journals).
Technical terms
Makespan: The total time required to complete a set of manufacturing jobs from start to finish.
Mixed Integer Linear Programming (MIP): A mathematical optimisation technique that models decisions with both continuous and discrete variables under linear constraints.
Matheuristic: A hybrid approach that combines exact mathematical programming methods with heuristic algorithms to solve complex optimisation problems efficiently.
Nesting: The arrangement of multiple parts within a build platform to maximise material use and minimise waste.
Batching: The grouping of parts into build sets based on compatibility, geometry and process requirements to optimise machine utilisation and throughput.
References
- Scheduling for additive manufacturing with two-dimensional packing and incompatible items. Omega (2024).
- Nesting and scheduling optimization of additive manufacturing systems: Mapping the territory. Computers & Operations Research (2024).
- The collaborative batching problem in multi-site additive manufacturing. International Journal of Production Economics (2022).
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