Application of case-based reasoning and multi-criteria decision-making methods for material selection in petrochemistry

Abstract

This paper describes a decision support approach for selecting construction materials in the field of petrochemistry. The correct selection of construction materials is the basis for the provision of durability, long lifetime, and the safety of the designed and upgraded equipment. The proposed hybrid approach is based on the joint application of case-based reasoning and multi-criteria decision-making methods, particularly the aggregation and ranking alternatives nearby the multi-attribute ideal situation (ARAMIS) and aggregation of individual ranking/ complex of aggregation of individual ranking (AIR/CAIR) methods are used. In turn, ARAMIS enables the processing of individual preferences, which are represented in the form of numeric and verbal estimates, and AIR/CAIR is used for processing rankings (strictly or partially ordered sets of alternatives). The primary advantage of this approach is that it considers the experience of previous successful solutions of the materials selection problem, demonstrates the validity of the obtained results using the mathematical theory of multi-criteria decision making and explains the decision making process. The approach is implemented in the form of the expert system. The case model, algorithms, and an illustrative example of application of the proposed approach are also presented.

Selection of candidate materials for reactor pressure vessels: Application of irradiation embrittlement prediction models and a stringency level methodology

“…In equations (2) and 3, the SMD term is related to stable matrix defects, which are defined as complex vacancy solute clusters and nanovoids that do not fully dissolve over an extended period of time. 26 The CRP term is associated with copper-rich precipitates responsible for hardening, and the Bias term is a fluxtime parameter.…”

“…1 The correct selection of materials is needed for providing durability, long lifetime, and structural safety. 2 There is a vast array of materials with diverse mechanical, physical, and chemical properties from which the design engineer has to select the most suitable material complying with different design requirements. 3,4 Essentially, material selection for any engineering component or product, in general, is subject to various constraints and fulfillment of certain goals of design.…”

A systematic review on material selection methods

“…Additionally, they combined the CBR strategy with constraint-based adaptation within the HSM field. Berman et al 12 discussed the integration of CBR with aggregation and ranking alternatives nearby the multi-attribute ideal situation (ARAMIS) and aggregation of individual ranking (AIR/CAIR) in developing a decision support approach in the form of an expert system. The primary advantage of this approach is that it is capable of considering past successful experience and solutions of the materials selection problem, demonstrates the validity of the obtained results, and provide transparency in the decision-making process.…”

“…8 Indubitably, a deep understanding of the functional requirements is essential, and multiple trade-offs are required between criteria during the selection process. Therefore, an in-depth evaluation in material selection is needed and for this reason, various methods and techniques such as the cost per unit property method, 3 chart method (Ashby method), 8,9 questionnaire method, 10 knowledge-based system (KBS), 11 life cycle analysis (LCA), case-based reasoning (CBR), 12 multi-criteria decision making (MCDM), optimisation and mathematical approaches have been proposed to aid in material selection processes.…”

Integrated product-process design: Material and manufacturing process selection for additive manufacturing using multi-criteria decision making

“…All the literature discussed above focused on the integrated approach with more emphasis on modification of DFM for AM and using a combination of the design criteria (e.g., function, cost and environment) and the DFM/DfAM guidelines for successful generation and utilization of the design requirements and attributes. In case of MPS problem which is also an integral decision-making aspect of DFM itself, a lot of work has been done on traditional domain with researches involving cost per unit property methods [35] , material and process selection charts [36] , casebased reasoning [37] , material selection programs [38] , knowledgebased systems [39] , AHP [40] , Technique of Ranking Preferences by Similarity to Ideal Solution (TOPSIS) [41] , and ELECTRE III [42] , but very little in the AM area. For example, the AHP was used by Mancanares et al [43] to select AM processes based on the requirements generated from a part.…”