Data mining by total ranking methods: a case study on optimisation of the "pulp and bleaching" process in the paper...

Area of Science:

• Decision Sciences
• Industrial Engineering
• Environmental Science

Background:

• Multicriteria decision making (MCDA) involves ranking alternatives using multiple, often conflicting, criteria.
• Total order ranking methods aggregate criteria into a scalar function for sorting alternatives.
• Traditional chlorine bleaching in the paper industry poses environmental risks due to dioxin production.

Purpose of the Study:

• To compare four total order ranking methods: Desirability functions, Utility functions, Dominance functions, and the Absolute Reference method.
• To evaluate the applicability of these MCDA techniques in selecting optimal paper bleaching processes.
• To identify superior alternatives to chlorine-based bleaching with high environmental impact.

Main Methods:

• Description and application of four distinct total order ranking methods.
• Comparative analysis of Desirability functions, Utility functions, Dominance functions, and Absolute Reference method.
• Evaluation of various paper bleaching processes using multiple criteria.

Main Results:

• The study demonstrates the practical application of four total order ranking methods in a real-world industrial problem.
• Comparison highlights the strengths and weaknesses of each method in handling conflicting criteria for process selection.
• Results provide insights into identifying environmentally friendlier bleaching alternatives.

Conclusions:

• Total order ranking methods offer robust frameworks for complex decision-making problems with multiple criteria.
• The choice of ranking method can influence the selection of the optimal alternative, emphasizing the need for careful consideration.
• The paper industry can benefit from these MCDA techniques to adopt sustainable bleaching processes.