Product: Management and Development
https://pmd.igdp.org.br/article/doi/10.4322/pmd.2018.002
Product: Management and Development
Original Article

Web platform for casting process selection

Juliana Ilha Zimmermann, Danielle Bond, Régis Kovacs Scalice

Downloads: 1
Views: 1194

Abstract

The choice of the right process for casting components is a complex activity that directly impacts on the product’s design and manufacturing. A single failure in the casting process selection can increase design and production time and, in critical cases, result in a collapse of the manufacturing and assembly of components. In this context, our goal is to adapt a previously developed method for casting process selection into a Web platform to aid the casting process selection. The adopted selection method uses Quality Function Deployment (QFD) and Design for Manufacturing (DFM) principles to provide a structure to support casting selection decision based on part features and process demands. The proposed software was developed for the Web using HTML and JavaScript, providing better usability than the previously proposed selection method format using spreadsheets. For validation, ferrous and nonferrous cast parts were analyzed using the proposed Web platform. The results showed a good relation to other methods, also providing a quantitative classification (prioritization) of the results. In addition, this software supports the design of the manufacturing process by means of a checklist to adapt the part to the metal casting process presented to the designer.

Keywords

casting process, process selection, web platform, quality function deployment, design for manufacturing

References

AKARTE, M. M.; RAVI, B. Casting product-process-producer compatibility evaluation and improvement. International Journal of Production Research, v. 45, n. 21, p. 4917- 4936, 2007. http://dx.doi.org/10.1080/00207540600887661.

AMERICAN FOUNDRY SOCIETY – AFS. Illinois, 2015. Available from: . Access in: 21 Sep 2015.

ASHBY, M. F. Materials selection in mechanical design. 3rd ed. Oxford: Butterworth-Heinemann, 2005. ASSOCIAÇÃO BRASILEIRA DE FUNDIÇÃO – ABIFA. Índicesde mercado ABIFA. São Paulo, 2012. Available from: . Access in: 23 July 2014.

BOOTHROYD, G.; DEWHURST, P.; KNIGHT, W. A. Product design for manufacture and assembly. New York: CRC Press, 2011.

BRALLA, J. G. Design for manufacturability handbook. New York: McGraw-Hill, 1998.

CHANG, D.; CHEN, C.-H. Understanding the influence of customers on product innovation. International Journal of Agile Systems and Management, v. 7, n. 3-4, p. 348- 364, 2014.

COCHRAN, D. S. et al. Incorporating design improvement with effective evaluation using the Manufacturing System Design Decomposition (MSDD). Journal of Industrial Information Integration, v. 2, p. 65-74, 2016. http://dx.doi. org/10.1016/j.jii.2016.04.005.

DARWISH, S. M.; TAMIMI, A. A.; AL-HABDAN, S. A knowledge base for metal welding process selection. International Journal of Machine Tools & Manufacture, v. 37, n. 7, p. 1007-1023, 1997. http://dx.doi.org/10.1016/ S0890-6955(96)00073-9.

DYNACAST. Die casting design. California, 2014. Available from: . Access in: 20 Apr 2014.

ELGH, F. Automated engineer-to-order systems: a taskoriented approach to enable traceability of design rationale. International Journal of Agile Systems and Management, v. 7, n. 3-4, p. 324-347, 2014.

ER, A.; DIAS, R. A rule-based expert system approach to process selection for cast components. Knowledge-Based Systems, v. 13, n. 4, p. 225-234, 2000. http://dx.doi. org/10.1016/S0950-7051(00)00075-7.

FERREIRA, J. M. C. Tecnologia da fundição. Lisboa: Fundação Calouste Glubenkian, 1999.

JONES, S.; YUAN, C. Advances in shell moulding for investment casting. Journal of Materials Processing Technology, v. 135, n. 2-3, p. 258-265, 2003. http://dx.doi. org/10.1016/S0924-0136(02)00907-X.

KARTHIK, S. et al. Methodology for metalcasting process selection. Pennsylvania: SAE International, 2003. SAE Technical Paper 2003-01-0431. http://dx.doi. org/10.4271/2003-01-0431.

KNIGHT, B.; COWELL, D.; PREDDY, K. An objectoriented support tool for the design of casting procedures. Engineering Applications of Artificial Intelligence, v. 8, n. 5, p. 561-567, 1995. http://dx.doi.org/10.1016/0952- 1976(95)00037-2.

KUMAR, V.; MADAN, J.; GUPTA, P. A system for design of multicavity die casting dies from part product model. International Journal of Advanced Manufacturing Technology, v. 67, p. 1-25, 2013.

LOVATT, A. M.; SHERCLIFF, H. R. Manufacturing process selection in engineering design. Part 1: the role of process selection. Materials & Design, v. 19, n. 5-6, p. 205-215, 1998a. http://dx.doi.org/10.1016/S0261-3069(98)00038-7.

LOVATT, A. M.; SHERCLIFF, H. R. Manufacturing process selection in engineering design. Part 2: a methodology for creating task-based process selection procedures. Materials & Design, v. 19, n. 5-6, p. 217-230, 1998b. http://dx.doi. org/10.1016/S0261-3069(98)00039-9.

MEEHANITE. Casting design as influenced by foundry practice. Grafton, 2007. Available from: . Access in: 21 Aug 2014.

NICHOLDS, B. A.; MO, J. P. T.; BRIDGER, S. Determining an action plan for manufacturing system improvement: a case study. International Journal of Agile Systems and Management, v. 7, n. 1, p. 1-25, 2014. http://dx.doi. org/10.1504/IJASM.2014.059145.

PULLAN, T. T. Decision support tool using concurrent engineering framework for agile manufacturing. International Journal of Agile Systems and Management, v. 7, n. 2, p. 132-154, 2014.

SANTOS, A. E. et al. Proposal and evaluation of a selection procedure for cast parts. Journal of the Brazilian Society of Mechanical Sciences and Engineering, v. 39, n. 8, p. 3151- 3163, 2017. http://dx.doi.org/10.1007/s40430-017-0755-3.

SETTI, D. Método multicriterial para seleção de processos de fundição de metais. 2010. 184 f. Tese (Doutorado em Engenharia)-Programa de Pós-graduação em Engenharia de Produção, Universidade Federal do Rio Grande do Sul, Porto Alegre, 2010.

SUN, J. et al. Virtualisation and automation of curved shell plates’ manufacturing plan design process for knowledge elicitation. International Journal of Agile Systems and Management, v. 7, n. 3-4, p. 282-303, 2014.

SWIFT, K. G.; BOOKER, J. D. Process selection: from design to manufacture. 2nd ed. Oxford: Butterworth-Heinemann, 2003.

VOSNIAKOS, G.-C. et al. The scope of artificial neural network metamodels for precision casting process planning. Robotics and Computer-integrated Manufacturing, v. 25, n. 6, p. 909-916, 2009. http://dx.doi.org/10.1016/j. rcim.2009.04.018.

WANG, Q. et al. The research and development of integrating database in casting process. Advanced Science Letters, v. 4, n. 8-9, p. 2946-2950, 2011. http://dx.doi.org/10.1166/ asl.2011.1532.

5b87ed690e88258a35e4c8a0 pmd Articles
Links & Downloads

Product

Share this page
Page Sections