Continuous Improvement of Injection Moulding Systems Through the Integration of the A3 Problem-Solving Framework with a PLC-Based Magnetic Self-Cleaning Filter System in the Automotive Industry
DOI:
https://doi.org/10.32734/jsti.v28i4.26330Keywords:
A3 Problem-Solving, Injection Moulding, Magnetic Self-Cleaning Filter, PLC Automation, Continuous ImprovementAbstract
Metal contamination in plastic resin is a critical issue in automotive injection moulding production systems. This contamination leads to product defects, check ring damage, cushion value instability, and high maintenance costs. This study aims to implement a continuous improvement approach using the A3 Problem-Solving method, centred on the design and implementation of a Programmable Logic Controller (PLC) based automated Preventive Magnetic Cleaning (PMC) system. This study addresses findings regarding design gaps in a PLC-based (Mitsubishi) self-cleaning magnetic filter system, integrated with the A3 problem-solving framework. The system automatically executes a cleaning cycle whenever material transfer occurs, thereby proactively preventing the magnetic shielding phenomenon without requiring manual intervention. The A3 framework was utilized to systematically identify the root cause via fishbone analysis, revealing the magnetic shielding phenomenon as the primary failure mechanism. As a technical solution, a neodymium magnet-based self-cleaning filter system was designed and installed on the auto-feed line of an 850T servo injection machine, controlled by a Mitsubishi PLC using ladder logic. Results demonstrated the elimination of manual cleaning interventions (2 hours/cycle), stabilization of cushion values from an average of 4.2 to 8.4 (within the standard range of 6–8), the capture of 100 grams of metal contaminants per week, and savings of IDR 47,000,000 in check ring replacement costs, with a payback period of 0.4–1.5 months. This study highlights the effectiveness of integrating lean management tools with automation technology as a sustainable continuous improvement strategy.
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[1] C. Jaqin, H. Kurnia, H. H. Purba, T. D. Molle, and S. Aisyah, “Lean Concept to Reduce Waste of Process Time in the Plastic Injection Industry in Indonesia,” Niger. J. Technol. Dev., vol. 20, no. 2, pp. 73–82, 2023, doi: 10.4314/njtd.v18i4.1396.
[2] R. Thorat and G. T. Mahesha, “Improvement in productivity through TPM Implementation,” Mater. Today Proc., vol. 24, pp. 1508–1517, 2020, doi: 10.1016/j.matpr.2020.04.470.
[3] F. Y. Agung and A. Siahaan, “Overall Equipment Effectiveness (OEE) Through Total Productive Maintenance (TPM) Practices: a Case Study in Chemical Industry,” Emerg. Mark. Bus. Manag. Stud. J., vol. 7, no. 1, pp. 23–36, 2020, doi: 10.33555/ijembm.v7i1.124.
[4] A. Zulaihan and N. Siswanto, “Modeling of Supplier Selection Strategy And Raw Material Order Allocation With Analytic Hierarchy Process Approach and Linear Programming at PT. IKSG,” Eduvest - J. Univers. Stud., vol. 5, no. 4, pp. 4079–4090, 2025, doi: 10.59188/eduvest.v5i4.17484.
[5] M. A. Yafi, S. Kustiwan, and T. N. Wiyatno, “Efisiensi Waktu Change Model Injection Molding Machine Menggunakan Metode Single Minute Exchange of Dies (SMED) di PT. XYZ,” G-Tech J. Teknol. Terap., vol. 8, no. 3, pp. 1859–1868, 2024, doi: 10.33379/gtech.v8i3.4610.
[6] P. Saothong, B. Ninchan, K. Sriroth, K. Rattanaporn, and W. Vanichsriratana, “Kinetics of saccharomyces cerevisiae fermentation under metal ions stress during ethanol production,” Walailak J. Sci. Technol., vol. 18, no. 6, pp. 1–10, 2021, doi: 10.48048/wjst.2021.9133.
[7] L. Setiawan and S. Hasibuan, “Improve Ramp-Up Performance on the Sewing Process in a Sports Shoe Factory Using 8-Disciplines and Lean Manufacturing,” Qual. Innov. Prosper., vol. 25, no. 2, pp. 19–36, 2021, doi: 10.12776/qip.v25i2.1516.
[8] K. B. Juliantoro, H. Kurnia, and S. R. Feriaty, “Reduction of changeover time and solvent cleaning cost in tank cleaning process in paint manufacturing industry in Indonesia,” TEKNOSAINS J. Sains, Teknol. dan Inform., vol. 12, no. 2, pp. 191–203, 2025, doi: 10.37373/tekno.v12i2.1520.
[9] H. Kurnia, K. Budi, and A. T. Zy, “Combination of Lean Thinking and A3 Problem-Solving Methods to Reduce the Cost of Purchasing Cleaning Agents in the Paint Industry in Indonesia,” Sinergi, vol. 5, no. July, pp. 1–12, 2023, doi: 10.22441/sinergi.2024.1.011.
[10] M. Kumar, R. Vaishya, and Parag, “Real-Time Monitoring System to Lean Manufacturing,” Procedia Manuf., vol. 20, pp. 135–140, 2018, doi: 10.1016/j.promfg.2018.02.019.
[11] D. Sjarifudin and H. Kurnia, “The PDCA Approach with Seven Quality Tools for Quality Improvement Men’s Formal Jackets in Indonesia Garment Industry,” J. Sist. Tek. Ind., vol. 24, no. 2, pp. 159–176, 2022, doi: 10.32734/jsti.v24i2.7711.
[12] G. M. Santos Filho and L. E. Simão, “A3 methodology: going beyond process improvement,” Rev. Gest., vol. 15, no. 4, pp. 1–15, 2022, doi: 10.1108/REGE-03-2021-0047.
[13] S. Perdana and D. Santoso, “Implementation of repairing production machine productivity of spare parts speaker based on OEE value achievement,” J. Appl. Res. Ind. Eng., vol. 6, no. 1, pp. 26–32, 2019, doi: 10.22105/JARIE.2019.169386.1075.
[14] S. Jaskó, A. Skrop, T. Holczinger, T. Chován, and J. Abonyi, “Development of manufacturing execution systems in accordance with Industry 4.0 requirements: A review of standard- and ontology-based methodologies and tools,” Comput. Ind., vol. 123, 2020, doi: 10.1016/j.compind.2020.103300.
[15] T. N. Wiyatno and H. Kurnia, “Increasing Overall Equipment Effectiveness in the Computer Numerical Control Lathe Machines Using the Total Productive Maintenance Approach,” J. Optimasi Sist. Ind., vol. 15, no. 2, pp. 284–292, 2022, doi: 10.31315/opsi.v15i1.7284.
[16] X. Li, Y. Wang, D. Lu, X. Zheng, and X. Gao, “Optimization of airflow field for pneumatic drum magnetic separator to improve the separation efficiency,” Minerals, vol. 11, no. 11, pp. 1–9, 2021, doi: 10.3390/min11111228.
[17] R. Cheng, T. Zhu, and L. Mao, “Three-dimensional and analytical modeling of microfluidic particle transport in magnetic fluids,” Microfluid. Nanofluidics, vol. 16, no. 6, pp. 1143–1154, 2014, doi: 10.1007/s10404-013-1280-z.
[18] M. Ghasemi, M. Govahi, and H. R. Litkohi, “Investigating the high gradient magnetic separator function for highly efficient adsorption of lead salt onto magnetic mesoporous silica microspheres and adsorbent recycling,” Int. J. Biol. Macromol., vol. 12, no. 4, pp. 1–23, 2024, doi: 10.1016/j.cep.2019.107770.
[19] L. Lin, W. Jiang, X. Xu, and P. Xu, “A critical review of the application of electromagnetic fields for scaling control in water systems: mechanisms, characterization, and operation,” npj Clean Water, vol. 3, no. 1, pp. 1–19, 2020, doi: 10.1038/s41545-020-0071-9.
[20] D. Sjarifudin, H. Kurnia, A. Nuryono, and E. B. M. Tambunan, “Hazard Identification Risk Assesment and Determining Control ( HIRADC ) Method for Shoe Cutting Dies Production,” J. Sist. Tek. Ind., vol. 25, no. 09, pp. 322–333, 2023, doi: 10.32734/jsti.v25i2.12186.
[21] M. E. Beatrix and N. E. Triana, “Improvement Bonding Quality of Shoe Using Quality Control Circle,” Sinergi, vol. 23, no. 2, p. 123, 2019, doi: 10.22441/sinergi.2019.2.005.
[22] A. I. Faria, J. C. Sá, M. T. Pereira, J. E. Sordan, and O. Mcdermott, “Assessing the Impact of Lean Tools on Sustainability — A Case Study,” J. Mech. Eng. Manuf., vol. 10, no. 4, pp. 1–25, 2026, doi: 10.53941/jmem.2026.100015.
[23] I. Zulkarnaen, A. Vendhy, A. Nuryono, and O. Widhi, “Benefits of implementing Industry 4 . 0 technology in health services,” J. Ind. Serv., vol. 10, no. 2, pp. 295–306, 2024, doi: 10.62870/jiss.v10i2.28364.
[24] S. A. Alif, A. I. Sakib, S. Shakur, S. Rafin, and B. Alam, “PLC Based Monitoring and Prediction : A Case Study of Injection Molding,” Proc. Int. Conf. Ind. Mech. Eng. Oper. Manag., vol. 26, no. 4, pp. 435–443, 2021.
[25] B. Tomar, N. Kumar, and M. Sreejeth, “A Smart PLC and SCADA based control framework for automated assembly line in process industry with effluent ratio control strategy,” Sadhana - Acad. Proc. Eng. Sci., vol. 50, no. 3, pp. 1–22, 2025, doi: 10.1007/s12046-025-02878-9.
[26] X. An, B. Huang, and D. Shi, “Cushioning properties and application of expanded polystyrene for a dynamic nonlinear system,” Eng. Reports, vol. 5, no. 9, pp. 1–12, 2023, doi: 10.1002/eng2.12648.
[27] B. Silva et al., “Enhance the Injection Molding Quality Prediction with Artificial Intelligence to Reach Zero-Defect Manufacturing,” Processes, vol. 11, no. 1, pp. 1–24, 2023, doi: 10.3390/pr11010062.
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