A decision support tool for intelligent manufacturing systems via an elevator kinematic optimisation based method. (1st October 2022)

• Record Type: Journal Article
• Authors: Luangpaiboon, Pongchanun; Aungkulanon, Pasura; Montemanni, Roberto
• Is Part Of: Expert systems with applications. Volume 203(2022)
• Publication Date: 2022-10-01
• Subjects: Compromise multi response surface optimisation -- Taguchi method -- Elevator kinematic optimisation -- Resistance welding; Expert systems (Computer science) -- Periodicals; Systèmes experts (Informatique) -- Périodiques; Electronic journals; 006.33
• DOI: 10.1016/j.eswa.2022.117576
• Languages: English
• ISSNs: 0957-4174

Abstract

Highlights: CM-RSOM merges robust designs and analyses for product and process improvements. Interactive approach can be used to satisfy the decision maker's preferences. EKO generates flexi-design plans to prevent designing new Taguchi arrays. EKO provides various parameter estimations for the prediction model. An industrial example demonstrates the utility of the proposed approach. Abstract: This paper presents a novel centralised method to solve the manufacturing parameter design problem based on evolutionary computation elements using a novel elevator kinematic optimisation algorithm . The new method is referred to as compromise multi response surface optimisation method . Its evolutionary computation nature simultaneously produces several flexi-design plans to prevent a high number of experiments and is used within the design phase of Taguchi arrays. The new method also provides various channels via available information for choosing the parameter levels during the analysis phase without new individual fitting sets. The industrial application used for benchmarking the new approach revealed that the proposed design and analysis method could lead to better optimal solutions for complex processes such as resistance welding than those of a conventional Taguchi method.