Improvement of Process Quality via Integration of Statistical Process Control and Engineering Process Control in Batch Process

Abstract

Batch process is one of a main type of process in the chemical industry alongside continuous process. However, it is difficult for production and process engineers to complete the task of achieving optimal performance of industrial batch processes. Batch processes have many major issues such as they are big batch-to-batch variations, highly non-linear dynamics, and difficulty in real-time measurement. It is significant to control the process in real-time, in order to avoid many issues such as off-spec product. While the study of EPC and SPC is garnering attraction in controlling strategy, the implementing of the integration is still rare compare to continuous process. The objective of this study is to develop a methodology that integrates two important techniques of Statistical Process Control (SPC) and Engineering Process Control (EPC) for quality improvement. Integrating SPC/EPC is a very effective way since the features from both SPC and EPC could give a complementary performance to improve product quality in industrial process by on-line monitoring, regulating and correcting actions. The approach is applied to data collected from experimentation process of carboxylmethyl carbon, as a case study where it is a batch process. SPC method used is EWMA control chart meanwhile EPC method used Integral (I) controller of feedforward with bounded chart. Based on result, the implementation of integration of SPC and EPC managed to reduce the process variation by 32.8% and reduced the standard deviation by 18%. λ of 0.5 was the best option with target = 0.89209, stand deviation = 0.05983, variance = 0.00358 and PM = 0.00367. Therefore, EWMA of bounded chart produced new average that is closer to target, variance that is smaller, standard deviation that is improved and performance measure that has the smallest value.