Abstract
A process optimization method based on partial least squares (PLS) has been used in pharmaceutical processes. However, its applicability and performance are limited because PLS cannot cope with nonlinearity and changes in process characteristics. In this research, a new process optimization method based on locally weighted PLS (LW-PLS) is proposed. To solve a nonlinear optimization problem based on LW-PLS, in which any global model is not constructed, self-adaptive differential evolution (jDE) is adopted. The validity of the proposed method is demonstrated through a numerical example and an industrial case study of a pharmaceutical granulation process.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
