Mak, Weng Yee and Kamarul, Asri Ibrahim
(2004)
Fault detection and diagnosis using Multivariate Statistical Process Control (MSPC).
In:
The 4th Annual Seminar of National Science Fellowship NSF 2004 Proceedings.
Penerbit Universiti Sains Malaysia, Pulau Pinang, Malaysia, pp. 515-520.
Abstract
Currently, chemical plants face numerous challenges like stringent requirements are needed on the desired final product quality, utilization of a lot of energy, must be environmentally friendly and fulfill safety requirements. High operation cost is needed in order for chemical plants to overcome the stated challenges. Any faults that are present in a chemical process will yield higher operation cost on the plant due to increase in production of waste, re-work, re-processing and consumption of utilities. Therefore, accurate process fault detection and diagnosis (FDD) on a chemical process at an early stage is important to reduce the cost of operation due to present of faults.
Actions (login required)
 |
View Item |
