Work

Manufacturing data-driven process adaptive design method

Year: 2020

Type: article

Abstract: Previous design methods are mostly based on simulation and experiment, so product/process design has poor adaptability to the manufacturing environment. A data-driven approach can provide feedback information in manufacturing to design. Therefore, this paper researches the method of data-driven process design based on data mining. We propose a backward design pattern of ”data + knowledge + decision,” which can fully dig up the potential value of manufacturing data. Therefore we expound the steps and methods of manufacturing data mining and takes the welding process as an example to demonstrate the driving role of data mining in process adaptive design.

Source: Procedia CIRP

DOI: 10.1016/j.procir.2020.02.230

Authors: Wei Wei, Jun Yuan, Ang Liu

Institutions: Beihang University, UNSW Sydney

Language: English

Topic: Manufacturing Process and Optimization

Subfield: Industrial and Manufacturing Engineering

Field: Engineering

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: diamond

Funders: National Natural Science Foundation of China, Aeronautical Science Foundation of China, State Key Lab of Digital Manufacturing Equipment and Technology, National Key Research and Development Program of China