Optimization of Packaging Process Parameters Using Combined Taguchi Method-present Worth Method/Inflationary Factor Validated

Authors

  • S.A. Oke University of Lagos, Lagos, Nigeria
  • I.O. Fagbolagun University of Lagos, Nigeria

DOI:

https://doi.org/10.24002/ijieem.v2i2.3785

Keywords:

Taguchi method, signal to noise ratio, interest rate, inflation rate, optimization.

Abstract

In a previous article, the packaging optimization literature illustrated how to optimize the packaging parameters using the classical Taguchi approach. Notwithstanding, it is compelling to bridge the gap created in the article for further advancement. Thus, this paper contributes to expanding scholarship regarding the area. The paper targets the Taguchi methodical optimization literature in which several scores of research across engineering disciplines and beyond have been undertaken. At present, evaluation using the Taguchi method often stops at the determination of the optimal settings from the response table through a chain of steps from factor-level selection, orthogonal array choice, signal-to-noise determination, and response table evaluation to emerge the optimal parameters. There is no information on the economic aspects of the parameters, yet processes are expected to be sustainable while economic factors play a central role. A novel idea of the present work is introduced where the interest rate and inflationary factor with levels are used to determine the economic strength of each parameter through ranking. Data was collected from a brewery process, and literature data concerning cold arc welding parametric evaluation was used. The outcome demonstrates the workability of the method in the packaging plant and cold arc welding process. The work is useful for packaging managers and welding engineers for planning purposes.

Author Biographies

S.A. Oke, University of Lagos, Lagos, Nigeria

Oke lectures in mechanical engineering

I.O. Fagbolagun, University of Lagos, Nigeria

Studied Mechanical Engineering

References

Abafi, J., & Oke, A. (2020). Analysis of downtime in a typical Nigerian multinational bottling company. Journal of Engineering Studies and Research, 26(3), 88-96.

Aerts, G., & Smits, T. (2017). The package size effect: How package size affects young children’s consumption of snacks differing in sweetness. Food Quality and Preference, 60, 72-80.

Almetwally, A.A. (2020). Multi-objective optimization of woven fabric parameters using Taguchi–grey relational analysis. Journal of Natural Fibers, 17(10), 1468-1478.

Al-Refaie, A. (2014). Optimisation of multiple responses in the Taguchi method using fuzzy regression. Artificial Intelligence for Engineering Design, Analysis, and Manufacturing, 28, 99-107.

Al-Refaie, A. (2015). A proposed weighted additive model to optimise multiple quality responses in the Taguchi method with applications. Proceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering, 229(3), 168-178.

Anthony, J. (2001). Simultaneous optimisation of multiple quality characteristics in manufacturing processes using Taguchi’s quality loss function. The International Journal of Advanced Manufacturing Technology, 17(2), 134-138.

Appadoo, S.S. (2014). Probabilistic fuzzy net present value model and application, mathematical problems in Engineering. Mathematical Problem in Engineering, 2014, 1-11.

Athreya, S., & Venkatesh, Y.D. (2012). Application of Taguchi method for optimization of process parameters in improving the surface roughness of lathe facing operation. International Refereed Journal of Engineering and Science, 1(3), 13-19.

Blackhall, R.B., Ritchie, J.M., Baxter, L.F., & Black, I. (2006). The novel combination of Taguchi methods and texture profile analysis applied to the optimisation of laboratory-based biscuit manufacturing. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 220(2), 273-293.

Candan, G., & Yazgan, H.R. (2015). Genetic Algorithm parameter optimisation using Taguchi method for a flexible manufacturing system scheduling problem. International Journal of Production Research, 53(3), 897-915.

Chomsamutr, K., & Jongprasithporn, S. (2012). Optimisation parameters of tool-life model using taguchi approach and response surface methodology. International Journal of Computer Science Issues, 9(1), 120.

Chandrasekar, V., Kannan, K., Priyavarshini, R., & Gayathri, R. (2015). Application of Taguchi method in optimization of process factors of ready to eat peanut (Arachis Hypogaea) Chutney. International Food Research Journal, 22(2), 510-516.

Chen, F.C., Tzeng, Y.F., Chen, W.R., & Hsu, M.H. (2009). The use of the Taguchi method and principal component analysis for the sensitivity analysis of a dual-purpose six-bar mechanism. Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, 223(3), 733-741.

Chen, F.C., & Huang, H.H. (2006). Taguchi-fuzzy-based approach for the sensitivity analysis of a four-bar function generator. Proceedings of the Institution of Mechanical Engineers Part C: Journal of Mechanical Engineering Science, 220(9), 1413-1421.

Chiu, C.Y., & Park, C.S. (1994). Fuzzy cash flow analysis using present worth criterion. The Engineering Economist: A Journal Devoted to the Problems of Capital Investment, 39(2), 113-138.

Doss, D.A., Jones, D.W., Sumrall, W., Henley, R., McErneath, D., Lackey, H., & Gokaraju, B. (2015). A net present worth analysis of considered academic programs at a private regional higher educational institution. Journal of Interdisciplinary Studies in Education, 4(1), 55-77.

Dwiwedi, A.K.R., & Kumar, S. (2015). Practical application of Taguchi method for optimization of process parameters in Injection molding machine for PP material. International Research Journal of Engineering and Technology, 2(4), 264-268.

Fang, Z., Zhao, Y., Warner, R.D., & Johnson, S.K. (2017). Active and intelligent packaging in meat industry. Trends in Food Science and Technology, 61, 60-71.

Fagbolagun, I.O., & Oke, S.A. (2020). The optimisation of packaging system process parameters using Taguchi method. International Journal of Industrial Engineering and Engineering Management, 2(1), 1-13.

Ganesan, V. & Kaliyamoorthy, B. (2020). Utilization of Taguchi technique to enhance the interlaminar shear strength of wood dust filled woven jute fiber reinforced polyester composites in cryogenic environment. Journal of Natural Fibers, 17(8), 1-12.

Grobbel, J.P., Dikeman, M.E., Hunt, M.C., & Williken, G.A. (2008). Effects of packaging atmospheres on beef instrumental tenderness, fresh color stability, and internal cooked color. Journal of Animal Science, 86(5), 1191-1199.

Hamdar, B.C., Khalil, A., Bissani, M., & Kalaydjian, N. (2018). Economic assessment of the impact of packaging design on consumption. Economics, 7(2), 27-33.

Heide, M., & Olsen, S.O. (2017). Influence of packaging attributes on consumer evaluation of fresh cod. Food Quality and Preference, 60, 9-18.

Ishrat, S.I., Khan, Z.A., Siddiquee, A.N., Badruddin, I.A., Algahtani, A., Javaid, S., & Gupta, R. (2019). Optimising parameters for expanded polystyrene based pod production using Taguchi method, Mathematics, 7(9), 847.

Jou, Y.T., Lin, W.T., Lee, W.C., & Yeh, T.M. (2014). Integrating the Taguchi method and response surface methodology for process parameter optimization of the injection molding. Applied Mathematics & Information Sciences, 8(3), 1277-1285.

Karabegović, E., & Đuzelić, R. (2019). The optimization of thermoforming process parameters in the packaging of medical products. Advanced Technologies and Materials, 44(2), 21-24.

Karimi, P., Mahdieh, O., & Rahmani, M. (2013). The study of relationship between packaging elements and purchase behaviour-consumers of good, cosmetics and health products. Interdisciplinary Journal of Contemporary Research in Business, 5(3), 281-295.

Kahraman, C. (2001). Capital budgeting techniques using Discounted Fuzzy Cash Flows. In D. Ruan, J. Kacprzyk, & M. Fedrizzi, Soft Computing for Risk Evaluation and Management: Studies in Fuzziness and Soft Computing. Heidelberg: Physica.

Kuchta, D. (2008) Optimization with Fuzzy Present Worth analysis and applications. In C. Kahraman, Fuzzy Engineering Economics with Applications: Studies in Fuzziness and Soft Computing. Heidelberg: Springer.

Maravas, A., & Pantouvakis, J.P. (2018). A new approach to studying net present value and the internal rate of return of engineering projects under uncertainty with three-dimensional graphs. Advances in Civil Engineering, 2018, 1-9.

McMillin, K.W. (2017). Advancements in meat packaging. Meat Science, 132, 153-162.

Sabdin, S.D., Husein, N.I.S., Sued, M.K., Ayob, M.S., Rahiim, M.A.S.A., & Fadzil, M. (2019). Effects of cold arc welding parameters on the trestle strength of high-strength steel plate investigated using the Taguchi approach. Journal of Mechanical Engineering and Sciences, 13(2), 4846-4856.

Silayoi, P., & Speece, M. (2007). The importance of packaging attributes: A conjoint analysis approach. European Journal of Marketing, 41(11-12), 1495-1517.

Sousa, M.R.S., Lora-García, J., López-Pérez, M.F., Santafé-Moros, A., & Gozálvez-Zafrilla, J.M. (2020). Operating conditions optimization via the Taguchi method to remove colloidal substances from recycled paper and cardboard production wastewater. Membranes, 10(8), 170.

Steenis, N.D., Herpen, E., van der Lans, I.A., Ligthart, T.N., & van Trijp, H.C.M. (2017). Consumer response to packaging design: The role of packaging materials and graphics in sustainability perceptions and product evaluations. Journal of Cleaner Production, 162, 286-298.

Üstüntağ, S., Şenyiğit, E., Mezarcıöz, S., & Türksoy, H.G. (2020). Optimization of coating process conditions for denim fabrics by Taguchi method and Grey relational analysis. Journal of Natural Fibers, 17(8), 1-15.

Zagloel, T.Y., & Al-Aina, F. (2009). Gram optimisation using Taguchi method of parameter design and neural network process model in packaging industry. Proceedings of 2nd Asia Pacific Conference in Manufacturing System, Indonesia.

Zizlavsky, O. (2014). Net present value approach: Method for economic assessment of innovation projects. Procedia-Social and Behavioral Sciences, 156, 506-512.

Downloads

Published

2020-12-13

How to Cite

Oke, S., & Fagbolagun, I. (2020). Optimization of Packaging Process Parameters Using Combined Taguchi Method-present Worth Method/Inflationary Factor Validated. International Journal of Industrial Engineering and Engineering Management, 2(2), 1–16. https://doi.org/10.24002/ijieem.v2i2.3785

Issue

Section

Articles