A production throughput forecasting system in an automated hard disk drive test operation using GRNN
Abstract: The goal of this
paper is to develop a pragmatic system of a production throughput forecasting
system for an automated test operation in a hard drive manufacturing plant. The
accurate forecasting result is necessary for the management team to response to
any changes in the production processes and the resources allocations.
Design/methodology/approach: In this study, we design a production
throughput forecasting system in an automated test operation in hard drive
manufacturing plant. In the proposed system, consists of three main stages. In
the first stage, a mutual information method was adopted for selecting the
relevant inputs into the forecasting model. In the second stage, a generalized
regression neural network (GRNN) was implemented in the forecasting model
development phase. Finally, forecasting accuracy was improved by searching the
optimal smoothing parameter which selected from comparisons result among three
optimization algorithms: particle swarm optimization (PSO), unrestricted search
optimization (USO) and interval halving optimization (IHO).
Findings: The experimental result shows that (1) the developed production
throughput forecasting system using GRNN is able to provide forecasted results
close to actual values, and to projected the future trends of production
throughput in an automated hard disk drive test operation; (2) An IHO algorithm
performed as superiority appropriate optimization method than the other two
algorithms. (3) Compared with current forecasting system in manufacturing, the
results show that the proposed system’s performance is superior to the current
system in prediction accuracy and suitable for real-world application.
Originality/value: The production throughput volume is a key performance
index of hard disk drive manufacturing systems that need to be forecast.
Because of the production throughput forecasting result is useful information
for management team to respond to any changing in production processes and
resources allocation. However, a practically forecasting system for production
throughput has not been described in detail yet. The experiments were conducted
on a real data set from the final testing operation of hard disk drive
manufacturing factory by using Visual Basics Application on Microsoft Excel© to
develop preliminary forecasting system on testing and verification process. The
experimental result shows that the proposed model is superior to the
performance of the current forecasting system.
Keywords: forecasting system,
GRNN, production throughput, smoothing parameter, hard disk drive manufacturing
Author: Nara Samattapapong,
Nitin Afzulpurkar
Journal Code: jptindustrigg160009
