روشی نوین برای طراحی فرمولاسیون لعاب با استفاده از برنامه‌ریزی ‌ریاضی

نوع مقاله : پژوهشی

نویسندگان

گروه مهندسی صنایع، دانشکده‌ی فنی مهندسی گلپایگان، دانشگاه صنعتی اصفهان، اصفهان، ایران.

چکیده

لعاب، یکی ‌از اصلی‌ترین مواد در تهیه‌ی ‌چینی‌آلات محسوب ‌می‌شود و همواره روش فرمولاسیون آن از مهم‌ترین‌ و چالش‌برانگیزترین کارها در صنعت ‌سرامیک بوده ‌است. تنظیم ‌فرمول ‌مناسب برای ‌تولید لعاب، هم ‌از نظر بهبود کیفیت محصولات‌ و هم از نظر کاهش هزینه‌های تولید، بسیار حائز اهمیت است. در پژوهش حاضر، که براساس تجربیات عملی در یکی از کارخانه‌های کشور ایران انجام شده است، برای اولین بار در جهان، مسئله‌ی فرمولاسیون لعاب با رویکرد پژوهش در عملیات، بررسی و تحلیل شده است. نتایج حاصل از مدل طراحی‌شده، آزمایش و در خط تولید پیاده‌سازی شده است. برای آنکه نتایج حاصل از پژوهش حاضر به‌صورت عملی در صنعت قابل استفاده باشند و کاربران به‌راحتی بتوانند از مزایای آن بهره‌مند شوند، یک نرم‌افزار کاربرپسند نیز برای آن طراحی و ایجاد شده است.

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

A Novel Method for Designing Glaze Formulation Using Mathematical Programming

نویسندگان [English]

  • Hossein Shams Shemirani
  • Hamid Reza Zahedi Neiestani
Industrial Engineering Group, Golpayegan College of Engineering, Isfahan University of Technology, Isfahan, Iran
چکیده [English]

Glaze is one of the fundamental components of ceramic products such as tiles, porcelain dishes, and sanitary ceramics. The formulation of glaze is a critical and complex process, representing one of the most significant and challenging aspects within the ceramic industry. Establishing the optimal formulation for glaze production is crucial for enhancing product quality and minimizing production costs. In this study, grounded in practical experiences from a factory setting, the issue of glaze formulation is examined and analyzed using an operations research approach for the first time globally. The outcomes of the developed model were tested and successfully implemented on the production line. To ensure the practical implementation of this research within the industry and to enhance user accessibility, a user-friendly software was developed. It is crucial to recognize that different factories employ a variety of raw materials in their glaze production processes. This variation arises from factors such as the unavailability of certain raw materials, the elevated costs associated with some materials, and the expenses related to transportation. The chemical composition of raw materials varies significantly, with the percentage of oxides differing based on the specific mine and the section of the mine from which they are sourced. Consequently, determining the optimal proportion of available raw materials for producing a glaze with a specific Seger formula necessitates repeated analysis. This iterative process is essential to identify the appropriate formula, which can then be implemented in the production line. In this study, conducted with real-world data and a thorough understanding of the problem through the production process, as well as an extensive review of relevant literature, the issue of designing a glaze formula is analyzed using operations research methodology. This paper presents a novel approach to glaze formulation, which can serve as a foundation for future research in this area.

کلیدواژه‌ها [English]

  • Glaze formulation
  • mathematical modeling
  • seger formula
  • batch formula
  • applied optimization

مراجع

1. Teodosiu, C.I., Sima, C., Croitoru, C. and Bode, F., 2022. Experimental investigation and optimization of a glazed transpired solar collector. Applied Sciences, 12(22), p.11392.https://doi.org/10.3390/app122211392
2. Isaia, F., Fiorentini, M., Serra, V. and Capozzoli, A., 2021. Enhancing energy efficiency and comfort in buildings through model predictive control for dynamic façades with electrochromic glazing. Journal of Building Engineering, 43, p.102535. https://doi.org/10.1016/j.jobe.2021.102535
3. Krarti, M., 2022. Design optimization of smart glazing optical properties for office spaces. Applied Energy, 308, p.118411.https://doi.org/10.1016/j.apenergy.2021.118411
4. Lantonio, N.A. and Krarti, M., 2022. Simultaneous design and control optimization of smart glazed windows. Applied Energy, 328, p.120239.https://doi.org/10.1016/j.apenergy.2022.120239
5. Araújo, G.R., Teixeira, H., Gomes, M.G. and Rodrigues, A.M., 2023. Multi-objective optimization of thermochromic glazing properties to enhance building energy performance. Solar Energy, 249, pp.446-456. https://doi.org/10.1016/j.solener.2022.11.043
6. Yang, R., Li, D., Wei, W. and Wang, F., 2020. A Mie optimization model to determine optical properties of PCM based nanofluids for solar thermal applications of glazing window. Optik, 212, p.164664. https://doi.org/10.1016/j.ijleo.2020.164664
7. Hong, X., Shi, F., Wang, S., Yang, X. and Yang, Y., 2021, December. Multi-objective optimization of thermochromic glazing based on daylight and energy performance evaluation. In Building Simulation(Vol. 14, No. 6, pp. 1685-1695). Beijing: Tsinghua University Press.https://doi.org/10.1007/s12273-021-0778-7
8. Zhou, Y. and Zheng, S., 2020. Stochastic uncertainty-based optimisation on an aerogel glazing building in China using supervised learning surrogate model and a heuristic optimisation algorithm. Renewable Energy, 155, pp.810-826. https://doi.org/10.1016/j.renene.2020.03.122
9. Zhou, Y. and Zheng, S., 2020. Climate adaptive optimal design of an aerogel glazing system with the integration of a heuristic teaching-learning-based algorithm in machine learning-based Renewable Energy, 153, pp.375-391. https://doi.org/10.1016/j.renene.2020.01.133
10. He, W., 2020. Fuzzy-PID Control Technology in Glaze Firing Process Control System of Roller Kiln for Bone China. In Big Data Analytics for Cyber-Physical System in Smart City: BDCPS 2019, 28-29 December 2019, Shenyang, China(pp. 1587-1593). Springer Singapore. http://dx.doi.org/10.1007/978-981-15-2568-1_221
11. Rosendahl, P.L., Staudt, Y., Schneider, A.P., Schneider, J. and Becker, W., 2019. Nonlinear elastic finite fracture mechanics: Modeling mixed-mode crack nucleation in structural glazing silicone sealants. Materials & Design, 182, p.108057.https://doi.org/10.1016/j.matdes.2019.108057
12. Yang, X., Li, D., Yang, R., Ma, Y., Duan, Y., Zhang, C., Hu, W. and Arıcı, M., 2023. Parameter global optimization and climatic adaptability analysis of PCM glazed system for long-term application. Renewable Energy, 217, p.119161.https://doi.org/10.1016/j.renene.2023.119161
13. Zhou, Y., 2022. A multi-stage supervised learning optimisation approach on an aerogel glazing system with stochastic uncertainty. Energy, 258, p.124815. https://doi.org/10.1016/j.energy.2022.124815
14. Mirhadi, B., 2001. Glaze theory and technology, in: B. Mirhadi, ed., Glaze Theory and Technology, 1st edn., Amirkabir University of Technology Press, Tafresh, Iran, pp. 1–32. [In Persian]
15. Mirhadi, B., 2001. Glaze raw materials, coloring, and calculation, in: B. Mirhadi, ed., Glaze Raw Materials, Coloring, and Calculation, 1st edn., Amirkabir University of Technology Press, Tafresh, Iran, pp. 33–60. [In Persian]
16. Burleson, M., 2003. Glaze formulation and application techniques, in: The Ceramic Glaze Handbook: Materials, Techniques, Formulas, 1st edn., Lark Books, Asheville, NC, USA, pp. 1–176.

فایل ها

هم رسانی

ارجاع به این مقاله

آمار