Towards a Data-Driven Smart Assembly Design: State-of-the-Art

With the increase of customer requirements and customized products needs, mechanical systems are becoming more sophisticated and equipped with intelligent parts. With this level of intelligence the mechanical systems become more and more complex and also their assembly processes becomes tedious. Therefore, the Industry 4.0 promotes efficient and smart assembly design to support commissioning automation and consequently customer satisfaction. This paper de-scribes the different challenges of assembly design, before presenting the advances on data analysis and Industry 4.0 technologies that can support intelligent assembly design. After analyzing these approaches, an innovative framework is proposed to provide the designer with a tool to address the different challenges of assemblies, based on the one hand on data from smart parts in operation (equipped with RFID sensors) transmitted by the Industrial Internet of Things and Cloud Computing, and on the other hand on the analysis of these massive data and the use of deep learning algorithms.