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The method of grey-fuzzy logic for optimizing multi-response problems during the manufacturing process: a case study of the light guide plate printing process

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Abstract

In this paper, a method of grey-fuzzy logic based on the orthogonal array is proposed to achieve the optimization of multi-response characteristics during the manufacturing process. The optimal procedure proposed for solving the optimal multi-response problem applies the grey relational coefficient in each machining response and converts a grey-fuzzy reasoning grade so as to evaluate multiple-machining responses. One real case study performed in the light guide plate (LGP) printing process verifies that the optimum procedure proposed in this study is feasible and effective. Through the grey-fuzzy logic analysis, the printing processing parameters, namely mixed rate of ink, velocity and pressure of printing process, and material and angle of scraper, are optimized with considerations to the multiple machining responses, including illumination, homogeny, value of variance for the illumination and printing ink thickness. The experimental results using the optimal setting easily clarified that the above-mentioned optimum procedure greatly improved the manufacturing process in this study.

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References

  1. Taguchi G (1990) Introduction to quality engineering. Asian Productivity Organization, Tokyo

    Google Scholar 

  2. Ross PJ (1996) Taguchi techniques for quality engineering. McGraw-Hill International Editions, Singapore

    Google Scholar 

  3. Bendell A, Disney J, Pridmore WA (1989) Taguchi methods: Applications in world Industry. IFS Publication, UK

    Google Scholar 

  4. Tarng YS, Yang WH (1998) Optimization of the weld bead geometry in gas tungsten arc welding by the Taguchi method. Int J Adv Manuf Technol 14:549–554

    Article  Google Scholar 

  5. Deng CS, Chin JH (2005) Hole roundness in deep hole drilling as analysed by Taguchi methods. Int J Adv Manuf Technol 25:420–426

    Article  Google Scholar 

  6. Gaitonde VN, Karnik SR, Achyutha BT, Siddeswarappa B (2007) Methodology of Taguchi optimization for multi-objective drilling problem to minimize burr size. Int J Adv Manuf Technol 34:1–8

    Article  Google Scholar 

  7. Deng JL (1982) Control problems of grey systems. Sys Control Lett 52:88–294

    Google Scholar 

  8. Deng JL (1989) Introduction to grey system. J Grey Sys 1(1):1–24

    MATH  Google Scholar 

  9. Lin JL, Lin CL (2002) The use of orthogonal array with Grey relational analysis to optimize the electrical discharge machining process with multiple performance characteristics. Int J Adv Manuf Technol 42:237–244

    Google Scholar 

  10. Singh PN, Raghukandan K, Pai BC (2004) Optimization by Grey relational analysis of EDM parameters on machining Al-10%SiCp composites. J Mater Process Technol 155–156:1658–1661

    Article  Google Scholar 

  11. Zadeh L (1965) Fuzzy sets. Inf Contr 8:338–353

    Article  MATH  MathSciNet  Google Scholar 

  12. Zimmermann HJ (1985) Fuzzy set theory and its applications. Kluwer, London

    Google Scholar 

  13. Lin CL, Lin JL, Ko TC (2002) Optimisation of the EDM process based on the orthogonal array with fuzzy logic and grey relational analysis method. Int J Adv Manuf Technol 19:271–277

    Article  Google Scholar 

  14. Lin JL, Lin CL (2005) The use of grey-fuzzy for the optimization of the manufacturing process. J Mater Process Technol 160:9–14

    Article  Google Scholar 

  15. Wang WP, Peng YH, Li XY (2002) Fuzzy-grey prediction of cutting force uncertainty in turning. J Mater Process Technol 129:663–666

    Article  Google Scholar 

  16. Albert WL, Yao SC, Chen CK (2005) Development of an integrated Grey-fuzzy-based electricity management system for enterprises. Energy 30:2759–2771

    Article  Google Scholar 

  17. Karmakar S, Mujumdar PP (2006) Grey fuzzy optimization model for water quality management of a river system. Adv Water Resour 29:1088–1105

    Article  Google Scholar 

  18. O’Mara WC (1993) Liquid crystal flat panel display: manufacturing science & technology. Van Nostrand Reinhold, New York

    Google Scholar 

  19. Lin CS, Wu WZ, Lay YL, Chang MW (2001) A digital image-based measurement system for LCD backlight module. Opt Laser Technol 33:499–505

    Article  Google Scholar 

  20. Feng D, Jin G, Yan Y, Fan S (2004) High-quality light guide plates that can control the illumination angle based on microprism structures. Appl Phys Lett 85(24):6016–6018

    Article  Google Scholar 

  21. Fisher RA (1925) Statistical method for research worker. Oliver & Boyd, London

    Google Scholar 

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Correspondence to Ko-Ta Chiang.

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Liu, NM., Horng, JT. & Chiang, KT. The method of grey-fuzzy logic for optimizing multi-response problems during the manufacturing process: a case study of the light guide plate printing process. Int J Adv Manuf Technol 41, 200–210 (2009). https://doi.org/10.1007/s00170-008-1448-y

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  • DOI: https://doi.org/10.1007/s00170-008-1448-y

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