A Novel Process to Setup Electronic Products Test Sites Based on Figure of Merit and Machine Learning

Abstract

Consumer electronic manufacturing (CEM) companies maintain a range of electronic products that are designed and tested according to the type and end-user requirements. These electronic products go through a validation and verification test for proof of design and a manufacturing test for checking reliability, quality, and manufacturing defects. Testing is carried out using test sites, designed based on the electronic product type. Currently, there is no standard approach for setting up a test site for electronic products. In this research, two processes are presented, for setting up new test sites and optimization of existing test sites for consumer and other electronic products. The proposed processes include a voice of customer (VoC) interface, that is based on a unique dataset and through machine-learning technique automatically translate customer information into customer requirements, and a figure of merit (FoM) presented as an outcome of this research using several key test-related parameters. These proposed processes are an important step towards defining a standard approach for setting test sites for consumer and other electronic products. The processes are implemented using a software application developed in LabVIEW, which is linked to a database containing test data for around 400 products collected as part of this research and form a knowledge base for the proposed processes. Finally, the processes are validated by setting up a new experimental test site for an RF receiver and optimization of an existing test site of an antenna system.

Keywords

• Consumer electronic manufacturing (CEM)
• electronic product test
• figure-of-merit (FoM)
• LabVIEW
• machine-learning
• voice of customer (VoC)