Extensions of the TOPSIS for group decision-making under fuzzy environment
Fuzzy Sets and Systems
Fuzzy Multiple Attribute Decision Making: Methods and Applications
Fuzzy Multiple Attribute Decision Making: Methods and Applications
Information Sciences—Informatics and Computer Science: An International Journal
Is there a need for fuzzy logic?
Information Sciences: an International Journal
Expert Systems with Applications: An International Journal
Fuzzy axiomatic design extension for managing model selection paradigm in decision science
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
A new multi-attribute decision making method: Hierarchical fuzzy axiomatic design
Expert Systems with Applications: An International Journal
Toward a generalized theory of uncertainty (GTU)--an outline
Information Sciences: an International Journal
Editorial: Modelling uncertainty
Information Sciences: an International Journal
| Hi-index | 0.07 |
Managing the verification of primary design projects for ship machinery systems is one of the crucial stages in ship building processes. In particular, the design of operator-system interfaces such as remote controls, displays, alarms, workstations, and labels requires a high level of technical expertise and systematic control. This paper focuses on structuring a ship design project approval mechanism (SDPAM) based on fuzzy axiomatic design (FAD) methodology which is concerned with the system design of relevant interfaces on an engine room control console. Design characteristics such as accessibility and operational requirements are treated as ''hard'' constraints being encountered in this complex problem. Hence, the proposed methodology requires performance assessment using fuzzy values. This study provides original contributions to the existing approval procedures of classification societies, which are non-governmental construction and classification organizations in the shipping industry. Furthermore, the study proposes a new approach to handle uncertainty and vagueness by an axiomatic design extension to ship project execution problems.