Published March 1, 2017
| Version 10006890
Journal article
Open
Optimal Performance of Plastic Extrusion Process Using Fuzzy Goal Programming
Creators
Description
This study optimized the performance of plastic extrusion process of drip irrigation pipes using fuzzy goal programming. Two main responses were of main interest; roll thickness and hardness. Four main process factors were studied. The L18 array was then used for experimental design. The individual-moving range control charts were used to assess the stability of the process, while the process capability index was used to assess process performance. Confirmation experiments were conducted at the obtained combination of optimal factor setting by fuzzy goal programming. The results revealed that process capability was improved significantly from -1.129 to 0.8148 for roll thickness and from 0.0965 to 0.714 and hardness. Such improvement results in considerable savings in production and quality costs.
Files
10006890.pdf
Files
(242.3 kB)
| Name | Size | Download all |
|---|---|---|
|
md5:bb69912218dd916d256a622ef41721b4
|
242.3 kB | Preview Download |
Additional details
References
- Phadke MS, "Quality Engineering Using Robust Design," Englewood Cliffs, NJ: Prentice-Hall, 1989.
- Tarng YS, Yang WH and Juang SC,"The use of fuzzy logic in the Taguchi method for the optimisation of the submerged arc welding process," Int J Adv Manuf Technol, Vol 16, 2000, pp. 688–694.
- Ramakrishnan R and Karunamoorthy L.," Modeling and multi-response optimization of Inconel 718 on machining of CNC WEDM process," J Mater Process Technol., Vol. 207, 2008, pp. 343–349.
- Lin HC, Su CT, Wang CC, Chang BH, Juang RC (2012), " Parameter optimization of continuous sputtering process based on Taguchi methods, neural networks, desirability function, and genetic algorithms," Expert Systems with Applications, Vol. 39, No. 17, pp. 12918–12925.
- Sun J-H., Fang Y-C. and Hsueh B-R., "Combining Taguchi with fuzzy method on extended optimal design of miniature zoom optics with liquid lens,". Optik, Vol. 123(19), 2012, pp. 1768– 1774.
- Sivasakthivel T, Murugesan K., Thomas HR (2014), " Optimization of operating parameters of ground source heat pump system for space heating and cooling by Taguchi method and utility Concept," Applied Energy, Vol. 116, pp. 76–85.
- Muthuramalingam T, Mohan B (2014), "Application of Taguchi-grey multi responses optimization on process parameters in electro erosion," Measurement, Vol. 58, pp. 495–502.
- Tsai T.N., "Improving the fine-pitch stencil printing capability using the Taguchi method and Taguchi fuzzy-based model, " Robotics and Computer-Integrated Manufacturing, Vol. 27, 2014, pp. 808–817.
- Venkatesh C. and Venkatesan R., "Optimization of process parameters of hot extrusion of SiC/Al 6061 composite using Taguchi's technique and upper bound technique, " Materials and Manufacturing Processes, Vol. 30 (1): 2015, pp. 85-92. [10] Al-Refaie A., Li M-H and Tai K-C., "Optimizing SUS 304 wire drawing process by grey analysis utilizing Taguchi method," Journal of University of Science and Technology Beijing, Mineral, Metallurgy, Material, Vol. 15(6), 2009, pp. 714–722. [11] Al-Refaie A., "Optimizing SMT performance using comparisons of efficiency between different systems technique in DEA," IEEE Transactions on Electronics Packaging Manufacturing, Vol. 32(4), 2009, pp. 256–264. [12] Al-Refaie A., "Super-efficiency DEA approach for optimizing multiple quality characteristics in parameter design. International Journal of Artificial Life Research, Vol. 1(2), 2010a, pp. 58–71. [13] Al-Refaie A.,"A Grey-DEA approach for solving the multiresponse problem in Taguchi Method. Journal of Engineering Manufacture, "Vol. 224(1), 2010b, pp. 147–158. [14] Al-Refaie A.," Optimizing correlated QCHs using principal components analysis and DEA techniques. Production Planning & Control, " Vol. 22(07), 2011, pp. 676–689. [15] Al-Refaie A. and Al-Tahat M., "Solving the multi-response problem in Taguchi method by benevolent formulation in DEA. Journal of Intelligent Manufacturing, Vol. 22(4), 2011, pp. 505–521. [16] AL-Refaie A., Chen T., Al-Athamneh R., Wu H.C., " Fuzzy neural network approach to optimizing process performance by using multiple responses," Journal of Ambient Intelligence and Humanized Computing, Vol. 7 (6), 2016, pp. 801-816. [17] Al-Refaie A. and Diabat A., "Optimizing convexity defect in a tile industry using fuzzy goal programming, " Measurement, Journal of the International Measurement Confederation, Vol. 46 (8), 2013, pp. 2807-2815. [18] Al-Refaie A., "A proposed satisfaction function model to optimize process performance with multiple quality responses in the Taguchi method. Journal of Engineering Manufacture, 2013. doi: 10.1177/0954405413498583. [19] Al-Refaie A., "A proposed weighted additive model to optimize multiple quality responses in the Taguchi method with applications," Journal of Process Mechanical Engineering, Vol. 228(2), 2014a, pp. 291–301. [20] Al-Refaie A., "FGP model to optimize performance of tableting process with three quality responses," Transactions of the Institute of Measurement and Control, Vol. 36(3), 2014b, pp. 336–346. [21] Al-Refaie A., Li M. H., Jarbo M., Yeh, C. H., and Bata N., " Imprecise data envelopment analysis model for robust design with multiple fuzzy quality responses," Advances in Production Engineering & Management, Vol. 9(2), 2014a, pp. 83–94. [22] Al-Refaie A., W. Al-Alaween, A. Diabat, M.H. Li, " Solving dynamic systems with multi-responses by integrating desirability function and data envelopment analysis," Journal of Intelligent Manufacturing, 2014b. doi:10.1007/s10845-014-0986-4. [23] Al-Refaie A, "Optimizing multiple quality responses in the Taguchi method using fuzzy goal programming: modeling and applications," International Journal of Intelligent Systems, Vol. 30(6), 2015a, pp. 651–675. [24] Al-Refaie A., "Optimal performance of plastic pipes' extrusion process using Min-Max model in fuzzy goal programming," Journal of Process Mechanical Engineering, 2015b. doi: 10.1177/0954408915620988.