Quality circle implementation to reduce defects in cast steel products in the heavy equipment industry

Sony Iskandar, Nora Azmi, Rahmi Maulidya

Abstract


Steel products produced from the metal casting process or commonly called cast steel are still very much needed in the industrial world, as components for production machines, power plants, automotives, heavy equipment and other needs. PT KX is a company that produces cast steel products, the products produced are targeted to be able to meet customer needs both for domestic needs and for export needs abroad. One of the problems currently faced by this company is the high defect ratio in several products currently produced. The defects that occur are porosity, gas holes, sand inclusions, cracks, and misruns. This company's good culture in implementing continuous improvement is well developed in all lines and all members of the organization so that this company continuously makes efforts to reduce defects that occur in products. The aim of this research is to analyze the causes of problems and make improvements to reduce the defect ratio. The method used by Quality Circle (QC) is as a method for making continuous improvements in reducing defects. One of the ways in which the verification process is carried out is by utilizing Electron Probe Micro Analyzer (EPMA) machine technology. This aims to make the analysis results more in-depth so that ultimately the defects that occur in a product can be reduced significantly.

Keywords


quality circle; improvement; EPMA technology; reduce defect

Full Text:

PDF

References


Ahmed, M., & Ahmad, N. (2011). An Application of Pareto Analysis and Cause-and-Effect Diagram (CED) for Minimizing Rejection of Raw Materials in Lamp Production Process. Management Science and Engineering, 5(3), 87. https://doi.org/10.3968/j.mse.1913035X20110503.320

Barot, R. S., Patel, J., Sharma, B., Rathod, B., Solanki, H., & Patel, Y. (2019). Lean six sigma feasibility and implementation aspect in cast iron foundry. Materials Today: Proceedings, 28, 1084–1091. https://doi.org/10.1016/j.matpr.2020.01.087

Calderón, J. C., Koch, L., Bandl, C., Kern, W., Jilg, J., Schilp, C., Moritzer, E., & Grundmeier, G. (2020). Multilayer coatings based on the combination of perfluorinated organosilanes and nickel films for injection moulding tools. Surface and Coatings Technology, 399. https://doi.org/10.1016/j.surfcoat.2020.126152

Chandra Kandpal, B., Johri, N., Kumar, B., Patel, A., Pachouri, P., Alam, M., Talwar, P., Sharma, M. K., & Sharma, S. (2021). Experimental study of foundry defects in aluminium castings for quality improvement of casting. Materials Today: Proceedings, 46, 10702–10706. https://doi.org/10.1016/j.matpr.2021.01.513

Chelladurai, C., Mohan, N. S., Hariharashayee, D., Manikandan, S., & Sivaperumal, P. (2020). Analyzing the casting defects in small scale casting industry. Materials Today: Proceedings, 37(Part 2), 386–394. https://doi.org/10.1016/j.matpr.2020.05.382

Dybowski, B., Kiełbus, A., & Poloczek, Ł. (2023). Effects of die-casting defects on the blister formation in high-pressure die-casting aluminum structural components. Engineering Failure Analysis. https://doi.org/10.1016/j.engfailanal.2023.107223

Goyal, A., Agrawal, R., & Kumar Sharma, A. (2022). Green quality circle: Achieving sustainable manufacturing with low investment. Resources, Conservation and Recycling Advances, 15. https://doi.org/10.1016/j.rcradv.2022.200103

Grover, V., Sengupta, P., Bhanumurthy, K., & Tyagi, A. K. (2006). Electron probe microanalysis (EPMA) investigations in the CeO 2-ThO2-ZrO2 system. Journal of Nuclear Materials, 350(2), 169–172. https://doi.org/10.1016/j.jnucmat.2006.01.001

Guleria, P., Pathania, A., Bhatti, H., Rojhe, K., & Mahto, D. (2021). Leveraging Lean Six Sigma: Reducing defects and rejections in filter manufacturing industry. Materials Today: Proceedings, 46, 8532–8539. https://doi.org/10.1016/j.matpr.2021.03.535

Hodbe, G. A., & Shinde, B. R. (2018). Design and Simulation of LM 25 Sand Casting for Defect Minimization. Materials Today: Proceedings, 5(2), 4489–4497. https://doi.org/10.1016/j.matpr.2017.12.018

Lal, R., Bolla, B. K., & Sabeesh, E. (2023). Efficient Neural Net Approaches in Metal Casting Defect Detection. Procedia Computer Science, 218, 1958–1967. https://doi.org/10.1016/j.procs.2023.01.172

Li, Y., Liu, J., Zhong, G., Huang, W., & Zou, R. (2021). Analysis of a diesel engine cylinder head failure caused by casting porosity defects. Engineering Failure Analysis, 127. https://doi.org/10.1016/j.engfailanal.2021.105498

Nwaogu, U. C., & Tiedje, N. S. (2011). Foundry Coating Technology: A Review. Materials Sciences and Applications, 02(08), 1143–1160. https://doi.org/10.4236/msa.2011.28155

Pastor-López, I., Sanz, B., Tellaeche, A., Psaila, G., de la Puerta, J. G., & Bringas, P. G. (2021). Quality assessment methodology based on machine learning with small datasets: Industrial castings defects. Neurocomputing, 456, 622–628. https://doi.org/10.1016/j.neucom.2020.08.094

Skryabin, M. L., & Likhanov, V. A. (2019). The study of casting defects in steel 35HGSL. Journal of Physics: Conference Series, 1399(4). https://doi.org/10.1088/1742-6596/1399/4/044063

Xu, Y., Li, G., Jiang, W., Zhan, J., Yu, Y., & Fan, Z. (2022). Investigation on characteristic and formation mechanism of porosity defects of Al–Li alloys prepared by sand casting. Journal of Materials Research and Technology, 19, 4063–4075. https://doi.org/10.1016/j.jmrt.2022.06.148

Yu, H., Li, X., Song, K., Shang, E., Liu, H., & Yan, Y. (2020). Adaptive depth and receptive field selection network for defect semantic segmentation on castings X-rays. NDT and E International, 116. https://doi.org/10.1016/j.ndteint.2020.102345




DOI: http://dx.doi.org/10.22441/oe.2023.v15.i3.094

Refbacks

  • There are currently no refbacks.


Copyright (c) 2023 Operations Excellence: Journal of Applied Industrial Engineering

Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Journal ISSN:

Portal ISSNPrint ISSN: 2085-4293
Online ISSN: 2654-5799

Tim Editorial Office
Operations Excellence: Journal of Applied Industrial Engineering

Magister Teknik Industri Universitas Mercu Buana
Jl. Raya Meruya Selatan No. 1 Kembangan Jakarta Barat
Email: [[email protected]]
Website: http://publikasi.mercubuana.ac.id/index.php/oe
Journal DOI: 10.22441/oe

The Journal is Indexed and Journal List Title by:

                 

 

 

Operations Excellence: Journal of Applied Industrial Engineering is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.