Darzin International Company Multidisciplinary Engineering Science Open 1 Serial Number 1 2024 03 01 Soft Robotics for Manufacturing: Materials, Architectures, and Control—From Lab Prototypes to Factory Deployment Soft Robotics for Manufacturing: Materials, Architectures, and Control—From Lab Prototypes to Factory Deployment 1 13 EN Journal Article 2023 12 23 <p class="Abstract" style="line-height: 150%;"><span style="font-size: 8.0pt; line-height: 150%;">This review aims to synthesize recent advances in soft robotics with a focus on material systems, structural architectures, and control mechanisms that enable the transition from laboratory prototypes to industrially deployable manufacturing solutions. This study employed a qualitative systematic review design to examine state-of-the-art developments in soft robotics relevant to manufacturing. Data were collected exclusively through a comprehensive literature review conducted across major databases, including Scopus, Web of Science, IEEE Xplore, and ScienceDirect. Using predefined inclusion criteria, 14 peer-reviewed articles published between 2010 and 2025 were selected for in-depth qualitative analysis. Data were coded and analyzed using NVivo 14 software through open, axial, and selective coding until theoretical saturation was achieved. The review followed the PRISMA framework to ensure transparency and replicability in data selection and synthesis. Four major themes emerged: (1) Material systems and functional integration revealed the evolution from passive silicone elastomers to hybrid composites with embedded sensing and self-healing capabilities; (2) Architectural design and adaptability highlighted advances in multi-chamber, fiber-reinforced, and bio-inspired morphologies that enhance compliance and dexterity; (3) Control, sensing, and learning mechanisms emphasized the rise of AI-driven, model-free, and hybrid control strategies that handle nonlinear deformations through reinforcement learning and proprioceptive sensing; and (4) Industrial translation challenges identified barriers such as durability, scalability, and regulatory standardization, along with solutions including hybrid rigid–soft integration and digital twin simulation. Soft robotics represents a paradigm shift in industrial automation, offering safety, adaptability, and intelligence for next-generation manufacturing systems. Despite significant advancements in materials, architectures, and control, large-scale industrial adoption requires further standardization, actuation optimization, and system-level integration with digital manufacturing ecosystems.</span></p> https://jmesopen.com/index.php/jmesopen/article/download/5/3