 A statistical monitoring strategy for a pulp and paper industryPulkit Rana, Anupam Das, Swarnambuj Suman and Jhareshwar Maiti International Journal of Industrial and Systems Engineering, 2018, vol. 28, issue 4, 530-545 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 T 2 chart; diagnostic statistic; unified control chart. (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:ids:ijisen:v:28:y:2018:i:4:p:530-545 Access Statistics for this article More articles in International Journal of Industrial and Systems Engineering from Inderscience Enterprises Ltd |
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