Analysis of Priority Improvement in Draft Quality of Sizing Using Grey Theory in FMEA

Hendri Pujianto, Yunus Nazar, Mohadi Mohadi, Dora Virma Yolanda Gultom, Dana Nasihardani

Abstract


Draft quality is a crucial problem in the sizing section. There were 3889 warp yarn breaks for six months. The study aims to decrease quality draft defects by applying the grey theory in the traditional FMEA. After analyzing the flow process, 41 potential causes (PC) were found from 12 potential failure modes in 7 areas. There is no significant difference in the top 5 rankings of the RPN assessment on traditional FMEA and grey theory. However, there is a slight difference in ranking on 5 PC. The first priority (RPN= 48; GR=0.588) is in the beam shaft with the creel unaligned in the beam installation (pneumatic piston not parallel). The last priority (RPN= 4; GR=0.857) is a less oiling. This research can recommend an improvement sizing process based on the proposed repairs or maintenance list, using the Grey theory in the FMEA method to decrease the weaving industry defect rate. 
 

Keywords


FMEA; Grey theory; Draft quality; Sizing; Warp break

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References


Afdal, Z. A., & Linarti, U. (2023). Preventive Maintenance Analysis Using Monte Carlo Simulation and Failure Mode and Effect Analysis (FMEA). Jurnal Ilmiah Teknik Industri, 22(2), 251–262. https://doi.org/10.23917/jiti.v22i2.21900

Ahmed, T., & Uddin, S. (2023). Textile weaving dataset for machine learning to predict rejection and production of a weaving factory. Data in Brief, 47, 108995. https://doi.org/10.1016/j.dib.2023.108995

Al Masud, A., Hossain, M. A., & Biswas, S. (2021). Impact of human resource management practices on the performance of the textile employees in barishal region. Annals of the Romanian Society for Cell Biology, 5291–5304.

Ali, S. R., Al Masud, A., Hossain, Md. A., Islam, K. M. Z., & Shafiul Alam, S. M. (2024). Weaving a greener future: The impact of green human resources management and green supply chain management on sustainable performance in Bangladesh’s textile industry. Cleaner Logistics and Supply Chain, 10, 100143. https://doi.org/10.1016/j.clscn.2024.100143

Ayele, M., & Abay, A. G. (2023). Analyzing the Effect of Various Sizing Machine Settings on Abrasion Resistance and Size Pick-Up of Polyester/Cotton Blend Sized Yarn Using Box-Behnken Design. Journal of Natural Fibers, 20(1), 2165591. https://doi.org/10.1080/15440478.2023.2165591

Chang, C., Liu, P., & Wei, C. (2001). Failure mode and effects analysis using grey theory. Integrated Manufacturing Systems, 12(3), 211–216. https://doi.org/10.1108/09576060110391174

Devare, M. D., Turukmane, R. N., Gulhane, S. S., & Patil, M. L. C. (2016). International Journal on Textile Engineering and Processes ISSN 2395-3578 Vol. 2, Issue 4 October 2016. 2(4).

Ebeling, C. E. (2019). An introduction to reliability and maintainability engineering. Waveland Press.

Ervural, B., & Ayaz, H. I. (2023). A fully data-driven FMEA framework for risk assessment on manufacturing processes using a hybrid approach. Engineering Failure Analysis, 152, 107525. https://doi.org/10.1016/j.engfailanal.2023.107525

Fajriah, N., Mahfud, H., & Hayati. (2023). Analysis and Minimization of Waste in the Production Area of PT. XYZ with Lean Manufacturing Approach and System Simulation. 22(2), 229–233. https://doi.org/10.23917/jiti.v22i2.22464

Febianti, E., Ferdinant, P. F., Wahyuni, N., & Riyani, D. N. (2020). Usulan Penjadwalan Perawatan Mesin Menggunakan Metode Reliability Block Diagram. Performa: Media Ilmiah Teknik Industri, 19(1). https://doi.org/10.20961/performa.19.1.40983

G. Huang, L. Xiao, W. Pedrycz, G. Zhang, & L. Martinez. (2023). Failure Mode and Effect Analysis Using T-Spherical Fuzzy Maximizing Deviation and Combined Comparison Solution Methods. IEEE Transactions on Reliability, 72(2), 552–573. https://doi.org/10.1109/TR.2022.3194057

Gandhi, K. L. (2020). Yarn preparation for weaving: Sizing. In Woven Textiles (pp. 119–166). Elsevier. https://doi.org/10.1016/B978-0-08-102497-3.00004-0

Genene Abay, A., & Ayele, M. (2023). Multiple response optimization of sizing machine settings and sized yarn tensile properties using advanced method of experimental design. Journal of Engineered Fibers and Fabrics, 18, 15589250231179621. https://doi.org/10.1177/15589250231179621

Huang, J., Guo, W., Shi, H., & Liu, H.-C. (2023). A social network analysis-based model for failure mode and effect analysis under linguistic preference relation environment. Engineering Applications of Artificial Intelligence, 126, 107119. https://doi.org/10.1016/j.engappai.2023.107119

Jahangir, D., & Hossain, M. S. (2023). Analysis of the Effect of Sizing Add-on% and Sizing Process Parameters on the Average Warp Breakage Rate for 30Ne 100% Cotton Warp Yarn. Journal of Engineering Science, 13(2), 111–115. https://doi.org/10.3329/jes.v13i2.63731

Ju, Y., Zhao, Q., Luis, M., Liang, Y., Dong, J., Dong, P., & Giannakis, M. (2024). A novel framework for FMEA using evidential BWM and SMAA-MARCOS method. Expert Systems with Applications, 243, 122796. https://doi.org/10.1016/j.eswa.2023.122796

Li, F., Zhang, L., Dong, S., Xu, L., Zhang, H., & Chen, L. (2024). Risk assessment of bolt-gasket-flange connection (BGFC) failures at hydrogen transfer stations based on improved FMEA. International Journal of Hydrogen Energy, 50, 700–716. https://doi.org/10.1016/j.ijhydene.2023.06.191

Liu, H.-C., Chen, X.-Q., Duan, C.-Y., & Wang, Y.-M. (2019). Failure mode and effect analysis using multi-criteria decision making methods: A systematic literature review. Computers & Industrial Engineering, 135, 881–897. https://doi.org/10.1016/j.cie.2019.06.055

Ma, Q., Zhu, X., Pu, Q., Liu, J., Fu, G., & Zhang, R. (2024). A method based on q-rung orthopair fuzzy cognitive map and TOPSIS method for failure mode and effect analysis considering risk causal relationships. Engineering Failure Analysis, 158, 107970. https://doi.org/10.1016/j.engfailanal.2024.107970

Minguito, G., & Banluta, J. (2023). Risk management in humanitarian supply chain based on FMEA and grey relational analysis. Socio-Economic Planning Sciences, 87, 101551. https://doi.org/10.1016/j.seps.2023.101551

Moon, S. K., Oh, H. S., Venture, J. A., Kim, J. K., & Yoon, Y.-J. (2013). Service reliability improvement in manufacturing and operating systems. International Journal of Precision Engineering and Manufacturing, 14(8), 1401–1406. https://doi.org/10.1007/s12541-013-0189-5

Nabi, G. (2022). Devices and Procedures Regulation in Medical Practice: Is There a Need for More transparency? Scottish Medical Journal, 67(1), 1. Scopus. https://doi.org/10.1177/00369330221080789

Nasrallah, I., Sabbah, I., Haddad, C., Ismaiil, L., Kotaich, J., Salameh, P., … Bawab, W. (2023). Evaluating the academic scientific laboratories’ safety by applying failure mode and effect analysis (FMEA) at the public university in Lebanon. Heliyon, 9(12), e21145. https://doi.org/10.1016/j.heliyon.2023.e21145

Ni, R., Meng, J., Cheng, M., Ke, Q., Zhao, Y., Li, X., & Zhao, Y. (2023). Recent advances of proteins extracted from agricultural and livestock wastes in biodegradable textile sizing applications. Process Safety and Environmental Protection, 177, 699–710. https://doi.org/10.1016/j.psep.2023.07.053

Ouyang, L., Che, Y., Yan, L., & Park, C. (2022). Multiple perspectives on analyzing risk factors in FMEA. Computers in Industry, 141, 103712. https://doi.org/10.1016/j.compind.2022.103712

Palange, A., & Dhatrak, P. (2021). Lean manufacturing a vital tool to enhance productivity in manufacturing. Materials Today: Proceedings, 46, 729–736. https://doi.org/10.1016/j.matpr.2020.12.193

Park, J., Park, C., & Ahn, S. (2018). Assessment of structural risks using the fuzzy weighted Euclidean FMEA and block diagram analysis. The International Journal of Advanced Manufacturing Technology, 99(9–12), 2071–2080. https://doi.org/10.1007/s00170-018-1844-x

Pravitasari, F., Kusumadewi, A., & Barat, J. (2023). Mitigation of Insert Separator Damage in Open-End Machines Penanggulangan kerusakan insert separators pada mesin open end. 05(01). http://dx.doi.org/10.37577/sainteks.v%vi%i.459

Pujianto, H. (2021). Reduksi Limbah Benang Cath Cord Pinggiran Kain untuk Penghematan Bahan Baku Benang Cath Cord dan Biaya Produksi pada Mesin Tenun Rapier PT XYZ dengan Percobaan Produksi pada Laboratorium Pertenunan AK-Tekstil Solo. 29.

Pujianto, H., Yulianto, B., Bintang, H. S., & Pramesti, D. A. (2023). Optimum Splice Thickness Ratio Splicer of a Winding Machine to PE20KT Thread Splicing Quality. Sainteks: Jurnal Sains dan Teknik, 5(2), 228–235. https://doi.org/10.37577/sainteks.v5i2.605

Rahayu, A. (2016). Evaluasi Efektivitas Mesin Kiln dengan Penerapan Total Productive Maintenance pada Pabrik II/III PT Semen Padang. Jurnal Optimasi Sistem Industri, 13(1), 454. https://doi.org/10.25077/josi.v13.n1.p454-485.2014

Rajput, S. K., Gulhane, S. S., Turukmane, R. N., & Basak, S. (2018). Benchmarking the End Breakage Rate of Sized Beam for Improving Loom Efficiency. 4(2).

Rashedul Islam, K. Md. (2023, May 27). Demystifying Most 25 Yarn Winding Defects and Remedies/ Effective Solution for Seamless Production. Retrieved 19 August 2023, from Winding Defects and Remidies website: https://textiletrainer.com/yarn-winding-defects-and-remedies/#google_vignette

Rong, Y., Yu, L., Liu, Y., Simic, V., Pamucar, D., & Garg, H. (2024). A novel failure mode and effect analysis model based on extended interval-valued q-rung orthopair fuzzy approach for risk analysis. Engineering Applications of Artificial Intelligence, 136, 108892. https://doi.org/10.1016/j.engappai.2024.108892

Shaju, K., Babu, S., & Thomas, B. (2023). Analysing effectiveness of grey theory-based feature selection for meteorological estimation models. Engineering Applications of Artificial Intelligence, 123, 106243. https://doi.org/10.1016/j.engappai.2023.106243

Sharma, R. K., Kumar, D., & Kumar, P. (2005). Systematic failure mode effect analysis (FMEA) using fuzzy linguistic modelling. International Journal of Quality & Reliability Management, 22(9), 986–1004. https://doi.org/10.1108/02656710510625248

Turukmane, R., Gulhane, S., & Patil, R. (2019). Impact of process parameters on sizing machine performance-A review. Melliand International, 25, 182–183.

Wan, X., Cen, L., Yue, W., Xie, Y., Chen, X., & Gui, W. (2024). Failure mode and effect analysis with ORESTE method under large group probabilistic free double hierarchy hesitant linguistic environment. Advanced Engineering Informatics, 59, 102353. https://doi.org/10.1016/j.aei.2024.102353

Wang, H., Zhang, Y.-M., & Yang, Z. (2019). A risk evaluation method to prioritize failure modes based on failure data and a combination of fuzzy sets theory and grey theory. Engineering Applications of Artificial Intelligence, 82, 216–225. https://doi.org/10.1016/j.engappai.2019.03.023

Yu, Y., Yang, J., & Wu, S. (2023). A novel FMEA approach for submarine pipeline risk analysis based on IVIFRN and ExpTODIM-PROMETHEE-II. Applied Soft Computing, 136, 110065. https://doi.org/10.1016/j.asoc.2023.110065

Zhou, Q., & Thai, V. V. (2016). Fuzzy and grey theories in failure mode and effect analysis for tanker equipment failure prediction. Safety Science, 83, 74–79. https://doi.org/10.1016/j.ssci.2015.11.013




DOI: http://dx.doi.org/10.22441/ijiem.v6i1.29858

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