Lab‐Scale Fabrication Process Selection for Soft Robotics: Benchmarking, Tradeoffs, and Guidelines for Formative Manufacturing of Soft Silicone Components

To close the gap between conceptual ideas and applied solutions, soft roboticists must build physical hardware. How that hardware is built meaningfully impacts its performance, as soft robots are highly sensitive to manufacturing. When fabricating components, researchers must select a high‐level process and numerous implementation details but currently lack both characterization data to make informed choices and a strategy for evaluating process tradeoffs. This paper addresses both gaps for molding soft elastomeric components, comparing injection molding (IM) and hand casting (HC) across molds from three additive manufacturing technologies: fused filament fabrication (FFF), stereolithography (SLA), and PolyJet (PJ). Using a representative inflatable geometry, actuators, molds, and test coupons are characterized with cycle testing, optical microscopy, profilometry, and 3D imaging. Lab‐scale, soft robotics‐specific criteria for evaluating fabrication strategies are defined and applied. Results demonstrate no universally best strategy exists; appropriate choices are context‐dependent. For example, SLA and PJ molds produced inflatable actuators lasting 2.5–3× longer than FFF, but at orders‐of‐magnitude greater cost and longer design‐to‐test times. Similarly, IM yielded better‐aligned internal cores than HC but with higher consumable costs and more hands‐on time. Synthesizing these criteria with characterization data and representative fabrication scenarios provides concrete process selection recommendations for matching fabrication with application.