The synthesis of nanoparticles (NPs) via laser ablation synthesis in solution (LASiS) is a promising method for sustainable and efficient nanoparticle fabrication. This work investigates the transition from one-factor-at-a-time experimentation to a more efficient, multivariate approach for optimising NP production efficiency. By applying the Industry 4.0 principles, the objective is to digitise and automate laboratory processes to increase productivity and robustness. Design of Experiments (DoE) strategies, Taguchi orthogonal arrays and full-factorial design (FFD), have been employed to enhance laser ablation processes. Both models confirmed that increasing laser power led to higher colloid absorbance, with the Taguchi DoE offering rapid initial process mapping and FFD providing a higher-resolution analysis. The optimal laser repetition rate of 30 kHz was identified as a balance between pulse energy and thermal effects on the target, maximising ablation efficiency. The Taguchi model had a prediction of NP size with an R2 value of 0.49, while the FFD struggled with accurate size prediction. Additionally, this study introduced a recirculation flow regime as a rapid test platform for predicting optimal conditions for continuous flow production. Using a semi-autonomous DoE platform decreased the operator involvement and increased the process selectivity. This proof-of-concept for on-the-bench NP rapid manufacturing demonstrated how efficient NP synthesis processes can be developed by clarifying the effects of varying parameters on colloid productivity, paving the way for broader industrial applications in the future.