<p>Intelligent manufacturing systems compatible with STEP-NC have demonstrated their ability to reduce production time and costs for manufacturing enterprises. In addition to ensuring high-quality production, rapid response times are crucial for determining the success or failure of small and medium-sized enterprises (SMEs) engaged in non-standard automation. A significant body of research has utilized Automated Computer-Aided Process Planning (ACAPP) techniques to integrate computer-aided design (CAD), computer-aided manufacturing (CAM), and computer numerical control (CNC) machining, aiming to provide comprehensive, automatic, rapid, and accurate process information to manufacturing enterprises. However, due to the inherent dynamics and complexity of the process, spanning from design to machining, current automated process planning technologies have not yet been able to offer viable solutions for SMEs. To address this challenge, this paper proposes a novel solution for automated process planning in STEP-NC manufacturing. The approach incorporates a machining feature recognition(MFR) method based on a simplified attribute adjacency graph (AAG) for stepwise decomposition, alongside an automatic engineering drawing recognition technique based on contour extraction and optical character recognition, ensuring input for automated process planning. Building upon this foundation, the solution leverages historical process data and integrates CAM as a service, enabling the automatic generation of toolpaths and the evaluation of machining time and cost. Finally, the effectiveness of the proposed method is validated through a case study of automated process planning for part manufacturing in a domestic non-standard automation enterprise, utilizing a collaborative edge-cloud system supporting STEP-NC.</p>