An automated process for designing test sites for electronic products based on figure on merit and machine learning

Abstract

The manufacturing industry plays an important role in the development of a country by employing its skilled and semi-skilled workforce. Electronic manufacturing companies launch new products frequently and spend a lot of time verifying their designs. These designs are verified through rigorous validation carried out using several pre-manufacturing tests. The products are ready for manufacturing after passing these tests. These companies focus on maintaining a good standard of their products which can be achieved through the manufacturing test. At this stage, companies setup test sites for testing these products, which are different from validation tests. To compete with similar companies, the manufacturing companies need to have an optimized electronic product testing system. Products are tested for manufacturing faults and functionality to maintain quality control which is a continuous process. Both consumer electronics and other products go through a similar process.

In the first part of the research, a process is presented for the automated design of electronic product test sites. Currently, there is no standard approach for setting up a test site for 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 translates 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.