A new holistic systems approach to the design of heat treated alloy steels using a biologically inspired multi-objective optimisation algorithm. (January 2015)

• Record Type: Journal Article
• Authors: Chen, Jun; Mahfouf, Mahdi; Sidahmed, Gaffour
• Is Part Of: Engineering applications of artificial intelligence. Volume 37(2015:Jan.)
• Page Start: 103
• Page End: 114
• Publication Date: 2015-01
• Subjects: Abs antibodies -- AIS artificial immune systems -- Al aluminium -- BEP back-error-propagation -- C Carbon -- Cr chromium -- FRBS fuzzy rule-based systems -- IMOFM an immune inspired multi-objective fuzzy modelling approach -- Mn manganese -- Mo molybdenum -- MOP multi-objective optimisation problems -- Ni nickel -- PAIA2 a modified population adaptive immune algorithm -- RMSE root mean square error -- ROA reduction of area -- S Sulphur -- Si silicon -- UTS ultimate tensile strength -- V vanadium; Multi-objective optimisation -- Fuzzy modelling -- Artificial Immune Algorithm -- 'Right-First-Time' production of alloy steels; Engineering -- Data processing -- Periodicals; Artificial intelligence -- Periodicals; Expert systems (Computer science) -- Periodicals; Ingénierie -- Informatique -- Périodiques; Intelligence artificielle -- Périodiques; Systèmes experts (Informatique) -- Périodiques; Artificial intelligence; Engineering -- Data processing; Expert systems (Computer science); Periodicals; 620.00285
• DOI: 10.1016/j.engappai.2014.08.014
• Languages: English
• ISSNs: 0952-1976

Abstract

Abstract: The primary objective of this paper is to introduce a new holistic approach to the design of alloy steels based on a biologically inspired multi-objective immune optimisation algorithm. To this aim, a modified population adaptive based immune algorithm (PAIA2) and a multi-stage optimisation procedure are introduced, which facilitate a systematic and integrated fuzzy knowledge extraction process. The extracted (interpretable) fuzzy models are able to fully describe the mechanical properties of the investigated alloy steels. With such knowledge in hand, locating the 'best' processing parameters and the corresponding chemical compositions to achieve certain pre-defined mechanical properties of steels is possible. The research has also enabled to unravel the power of multi-objective optimisation (MOP) for automating and simplifying the design of the heat treated alloy steels and hence to achieve 'right-first-time' production. Highlights: We model mechanical properties of heat treated alloy steel using interpretable fuzzy models. We demonstrate how to locate the 'best' processing parameters and chemical compositions. We demonstrate how to achieve certain mechanical properties. We demonstrated a holistic systems approach to achieve 'right-first-time' production. We unravel the power of multi-objective optimisation and interpretable fuzzy modelling.