Purpose: 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. 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) IHO algorithm performed as appropriate optimization method better 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. The production throughput forecasting
result is useful information for management team to respond to any changes in production
processes and resources allocation. However, a practical 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 Basic
Application on Microsoft Excel© to develop preliminary forecasting system for testing and
verification process. The experimental result shows that the proposed model is superior to the
performance of the current forecasting system.
