Title: A statistical monitoring strategy for a pulp and paper industry

Authors: Pulkit Rana; Anupam Das; Swarnambuj Suman; Jhareshwar Maiti

Addresses: Department of Industrial Engineering, Gautam Buddha University, Gr. Noida, Uttar Pradesh, India ' Department of Mechanical Engineering, National Institute of Technology Patna, Patna, Bihar 800005, India ' Department of Mechanical Engineering, National Institute of Technology Patna, Patna, Bihar 800005, India ' Department of Industrial and Systems Engineering, Indian Institute of Technology Kharagpur, Kharagpur, West Bengal, India

Abstract: The current article features the endeavour to develop a monitoring strategy for paper and pulp industry. The complexity involved in production of better quality pulp warrants the close monitoring of the process characteristics associated with the process. Partial least square regression (PLSR) which is a multivariate statistical projection-based technique is used for building the process representation which aids in the simultaneous monitoring of multiple correlated characteristics. Individual Hotelling T2 chart has been developed to monitor each grade of paper being produced. However this leads to implementation of different control charts for different grades of paper adding to the dexterity of the methodology. In order to solve the above problem methodology hence developed is further extended to develop a combined control chart to monitor all the grades of paper simultaneously. Furthermore a comparative study of the competence of the developed unified control chart with respect to the individual charts is done.

Keywords: process monitoring; partial least square regression; PLSR; Hotelling T2 chart; diagnostic statistic; unified control chart.

DOI: 10.1504/IJISE.2018.090449

International Journal of Industrial and Systems Engineering, 2018 Vol.28 No.4, pp.530 - 545

Received: 09 Dec 2015
Accepted: 06 May 2016

Published online: 19 Mar 2018 *

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