Parametric study and optimization of a food can corrugation design using a response surface method

• Published in: Journal of mechanical science and technology Vol. 27; no. 7; pp. 2043 - 2052
• Main Authors: Jongpradist, Pattaramon, Rojbunsongsri, Rattharong, Kamnerdtong, Thoatsanope, Wongwises, Somchai
• Format: Journal Article
• Language: English
• Published: Dordrecht Springer Netherlands 01.07.2013; Springer Nature B.V; 대한기계학회
• Subjects: Control; Corrugating; Corrugation; Design engineering; Dynamical Systems; Engineering; Foods; Industrial and Production Engineering; Mathematical models; Mechanical Engineering; Optimization; Strength; Vibration; Weight reduction; 기계공학; Finite element analysis; Structural optimization; Response surface method; Corrugation design; Buckling analysis
• ISSN: 1738-494X; 1976-3824
• DOI: 10.1007/s12206-013-0519-7

This paper presents the parametric design and functional optimization of a thin-walled food container with a corrugated surface. The configuration of the can corrugation should be designed to minimize the use of raw material subject to the constraints of the targeted structural performance. In the present study, the failure behaviors and the buckling strengths of a commercial food can under paneling pressure and axial loading are investigated with a series of experiments and finite element analyses. Full factorial design is implemented to study the effects of the geometric parameters of the corrugation (e.g., depth, radius, spacing and number of beadings) on its strength. Parameter optimization using a rotatable central composite design is employed to identify an optimal corrugation design by approximating the response surfaces of the can strength in terms of the significant design variables. The obtained surfaces are derived through the analysis of variance, and the suitability of the response is justified. A light- weight can body is then achieved by reduction of the can body thickness according to the required strength characteristics. Finite element analysis of the optimal model is also performed to confirm the predicted results. By using the proposed procedure, the can-body weight can be reduced by up to 12% compared with the original design.