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Information Journal Paper

Title

NUMERICAL AND EXPERIMENTAL INVESTIGATION OF INCREMENTAL SHEET METAL FORMING PARAMETERS AND MULTI­OBJECTIVE OPTIMIZATION USING NEURAL­ GENETIC ALGORITHM

Pages

  167-174

Abstract

 The INCREMENTAL SHEET METAL FORMING (ISMF) process is a new and flexible method that is well suited for small batch production or prototyping. In this study, after the process simulation with ABAQUS software and verification of results through experimental tests, the effects of three parameters including friction coefficient, tool diameter and vertical step size on three objectives including vertical force, minimum thickness of deformed sheet and amount of spring-back are investigated. A neural-network model is developed based on simulation data and the effects of parameters are studied on each objective. Also multi-objective genetic algorithm is performed to get the Pareto front of optimum points.

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  • Cite

    APA: Copy

    MOHAMMADI NAJAFABADI, HOSEIN, ATAI, ALI ASGHAR, & SHARIFIFAR, MASOUD. (2014). NUMERICAL AND EXPERIMENTAL INVESTIGATION OF INCREMENTAL SHEET METAL FORMING PARAMETERS AND MULTI­OBJECTIVE OPTIMIZATION USING NEURAL­ GENETIC ALGORITHM. MODARES MECHANICAL ENGINEERING, 14(2), 167-174. SID. https://sid.ir/paper/178377/en

    Vancouver: Copy

    MOHAMMADI NAJAFABADI HOSEIN, ATAI ALI ASGHAR, SHARIFIFAR MASOUD. NUMERICAL AND EXPERIMENTAL INVESTIGATION OF INCREMENTAL SHEET METAL FORMING PARAMETERS AND MULTI­OBJECTIVE OPTIMIZATION USING NEURAL­ GENETIC ALGORITHM. MODARES MECHANICAL ENGINEERING[Internet]. 2014;14(2):167-174. Available from: https://sid.ir/paper/178377/en

    IEEE: Copy

    HOSEIN MOHAMMADI NAJAFABADI, ALI ASGHAR ATAI, and MASOUD SHARIFIFAR, “NUMERICAL AND EXPERIMENTAL INVESTIGATION OF INCREMENTAL SHEET METAL FORMING PARAMETERS AND MULTI­OBJECTIVE OPTIMIZATION USING NEURAL­ GENETIC ALGORITHM,” MODARES MECHANICAL ENGINEERING, vol. 14, no. 2, pp. 167–174, 2014, [Online]. Available: https://sid.ir/paper/178377/en

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