Machine condition monitoring for defect detection in fused deposition modelling process: a review

作者：Hao He, Zhi Zhu, Y.X. Zhang, Zhongpu Zhang, Tosin Famakinwa, Chunhui Yang · 发表于：The International Journal of Advanced Manufacturing Technology · 年份：2024 · DOI：10.1007/s00170-024-13630-8 · 被引用次数：30 · 研究领域：Additive Manufacturing and 3D Printing Technologies、Manufacturing Process and Optimization、Additive Manufacturing Materials and Processes

Abstract Additive manufacturing (AM), also known as 3D printing (3DP), refers to manufacturing technologies that build up the desired geometries by adding materials layer by layer. Common meltable and fusible materials such as polymers, metals, and ceramics could be used in 3DP processes. During decades of development, products made by 3DP can now achieve stringent industrial standards at comparable costs compared to those traditionally manufactured. Improving 3DP technologies is required to make them more competitive and acceptable than their counterparts. However, achieving this is challenging since the quality of printing products is still heavily dependent on many cost-driven factors. Inadequate quality, impaired functionality, and reduced service life are three main consequences of 3DP’s failures. To effectively detect and mitigate defects and failures of 3DP products, machine condition monitoring (MCM) technologies have been used to monitor 3D printing processes. With the help of those dedicated algorithms, it could also prevent failures from occurrence by alerting operators to take appropriate actions accordingly. This study systematically reviews the MCM technologies used in a typical 3DP process—the fused deposition modelling (FDM), identifying their advantages and disadvantages. The mentioned MCM technologies include but are not limited to traditional MCM (sensors only), aided with analytical and artificial intelligence (AI) tools. The MCM techniques focus on the de...