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A decision support system for the operational production planning and scheduling of an integrated pulp and paper mill

Title
A decision support system for the operational production planning and scheduling of an integrated pulp and paper mill
Type
Article in International Scientific Journal
Year
2015
Authors
Pedro Amorim
(Author)
FEUP
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Fábio Moreira
(Author)
FEP
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Journal
Vol. 77
Pages: 85-104
ISSN: 0098-1354
Publisher: Elsevier
Scientific classification
FOS: Engineering and technology
CORDIS: Technological sciences
Other information
Authenticus ID: P-00A-BSN
Resumo (PT): Production planning and scheduling in the process industry in general and in the pulp and paper (P&P) sector in particular can be very challenging. Most practitioners, however, address those activities relying only on spreadsheets, which is time-consuming and sub-optimal. The literature has reported some decision support systems (DSSs) that are far from the state-of-the-art with respect to optimization models and methods, and several research works that do not address industrial issues. We contribute to reduce that gap by developing and describing a DSS that resulted from several iterations with a P&P company and a thorough review of the process systems engineering literature. The DSS incorporates relevant industrial features (which motivated the development of a specific model), exhibits important technical details (such as the connection to existing systems and user-friendly interfaces) and shows how optimization can be integrated in real world applications, enhanced by key pre- and post-optimization procedures.
Abstract (EN): Production planning and scheduling in the process industry in general and in the pulp and paper (P&P) sector in particular can be very challenging. Most practitioners, however, address those activities relying only on spreadsheets, which is time-consuming and sub-optimal. The literature has reported some decision support systems (DSSs) that are far from the state-of-the-art with regard to optimization models and methods, and several research works that do not address industrial issues. We contribute to reduce that gap by developing and describing a DSS that resulted from several iterations with a P&P company and from a thorough review of the literature on process systems engineering. The DSS incorporates relevant industrial features (which motivated the development of a specific model), exhibits important technical details (such as the connection to existing systems and user-friendly interfaces) and shows how optimization can be integrated in real world applications, enhanced by key pre- and post-optimization procedures.
Language: English
Type (Professor's evaluation): Scientific
No. of pages: 20
Documents
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