Multivariate process modeling of a high volume manufacturing of consumer electronics

摘要

As production volumes continue to increase and the global market for consumer electronics is getting fiercer, the need for a reliable and essentially fault-free production process is becoming a necessity to survive. The manufacturing processes of today are highly complex and the increasing amount of process data produced is making it hard to unravel the useful information extracted from a huge data set. We have used multivariate and nonlinear process modeling to examine the surface mount production process in a high volume manufacturing of mobile telephones and made an artificial neural network model of the process. As input parameters to the model we have used process data logged by nan automatic test equipment (ATE) and the result variables come from an Automatic Inspection system placed after the board manufacturing process. Using multivariate process modeling has enabled us to identify parameters. which contributes haveily to the quality of the product and can further be implemented to optimize the manufacturing process for system production faults.