# CAD-Based Feature Recognition for Process Monitoring Planning in Assembly
## 1 Introduction  
In recent years, industrial production has increasingly demanded customized and high-quality products. Therefore, flexible and reconfigurable production systems (i.e., flexible and reconfigurable manufacturing systems (FMS and RMS)) are emerging to meet customer requirements while maintaining high quality standards. In addition to increasing customer demands for high product quality, stricter regulations and standards mean that companies have to control their processes better [1, 2]. In particular, safety standards and regulations have become stricter in the production of electronic components with a high safety relevance and medical devices (e.g., due to the MDR - Medical Device Regulation (MDR) 2017/745) [3]. In addition, the increasing awareness of sustainable production and the avoidance of waste (i.e., material and resources) requires an increased reproducibility of the production processes. To meet these requirements, process data need to be recorded and analyzed. Assembly is one of the most important phases of manufacturing, accounting for a significant portion of the total production time and total manufacturing costs [4]. A large proportion of the costs are incurred in assembly, where faulty production processes cause high costs. Assembly involves upstream value-adding processes, so defects are particularly noticeable here. Quality control or inspection only after the assembly process is time-consuming and cost-intensive. Additional inspection processes have to be designed, which cost time and add no value to the product. To improve the assembly quality andreduce the overall assembly time and cost, an efficient approach to monitoring the assembly process is essential. Process monitoring has been studied as a possible approach for quality control [5]. More flexible and reconfigurable production systems can adapt an existing production configuration for the assembly of a new product variant while also integrating sensors for process monitoring. Unfortunately, this often requires a great deal of manual effort and expert knowledge to identify the resources and sensors capable of monitoring the processes directly (e.g., monitoring a joining process with a force-torque sensor) or indirectly (e.g., monitoring a joining process with sensors integrated into the robot axes). Different assembly processes and ways to assemble a product also influence the ability to monitor these processes. Determining monitoring requirements is the first step in process monitoring planning in assembly and is dependent on product, process, and resource information. To reduce the manual effort and expert knowledge required, automation approaches are needed to manage this complexity. This paper presents an approach that addresses precisely this issue (i.e., a reduction in effort and required expert knowledge) through the automated identification of monitoring requirements. It is structured as follows: after the introduction in Section 1, a literature review on process monitoring and inspection planning is given in Section 2. This section analyzes the literature to show the need for action regarding why the automatic generation of process monitoring requirements with feature recognition is relevant. Computer-aided approaches in process and inspection planning are also considered to identify the benefits that can be applied to process monitoring planning. Finally, product and process features (i.e., geometric and process-specific) and feature-based approaches required for process planning are described. Section 3 gives an overview of the overall system developed and then goes into detail about the individual modules (e.g., feature extraction and feature recognition) for generating monitoring requirements. The results are presented in Section 4, leading to a discussion of the system and results in Section 5. Finally, Section 6 summarizes the publication and presents an outlook for future research.