ISSN 2466-4677; e-ISSN 2466-4847
Journal Menu
Archive
Last Edition
Acp-mo: a novel metaheuristic optimization algorithm based on an advanced ceramic processing metaphor for optimization
Authors:
Jincheng Zhang1
1Faculty of Science and Technology, Rajabhat Maha Sarakham University, Maha Sarakham 44000, Thailand
Received: 30 April 2025
Revised: 12 June 2025
Accepted: 24 June 2025
Published: 30 June 2025
Abstract:
In the field of modern optimization, heuristic algorithms are widely used in
various optimization tasks due to their excellent performance on complex
problems. This paper proposes a new heuristic optimization algorithm, the
Advanced Ceramic Process Heuristic Optimization Algorithm (ACP-MO).
Inspired by the ceramic machining process, the algorithm uses forming
operations and reverse design repair strategies to simulate the dynamic
process in ceramic machining. By optimizing 10 typical test functions, the
experimental results show that ACP-MO outperforms multiple common
algorithms in terms of optimization accuracy. ACP-MO refers to the three-
stage optimization process of the advanced ceramic manufacturing process,
which includes the forming stage, sintering stage and repair stage. These
three stages correspond to exploration, quality assessment and local
refinement, respectively. A new integration of temperature control
convergence, Gaussian perturbation and inverse design heuristic correction
mechanism is introduced, which provides a new perspective for the design
and development of meta-heuristic algorithms.
Keywords:
Heuristic optimization, Ceramic technology, Global optimization, Algorithm comparison, Metaheuristic algorithm
References:
[1] E. Trojovská, M. Dehghani, P. Trojovský, Zebra Optimization Algorithm: A New Bio-Inspired Optimization Algorithm for Solving Optimization Algorithm. IEEE Access, 10, 2022: 49445–49473.
https://doi.org/10.1109/ACCESS.2022.3172789
[2] L. Abualigah, A. Diabat, S. Mirjalili, M. Abd Elaziz, A.H. Gandomi, The Arithmetic Optimization Algorithm. Computer Methods in Applied Mechanics and Engineering, 376, 2021: 113609.
https://doi.org/10.1016/j.cma.2020.113609
[3] D.E. Finkel, DIRECT Optimization Algorithm User Guide. Center for Research in Scientific Computation, North Carolina State University, 2(1), 2003: 1-14.
[4] P.C. Fourie, A.A. Groenwold, The Particle Swarm Optimization Algorithm in Size and Shape Optimization. Structural and Multidisciplinary Optimization, 23(4), 2002:259–267. https://doi.org/10.1007/s00158-002-0188-0
[5] A.-b. Meng, Y.-c. Chen, H. Yin, S.-z. Chen, Crisscross Optimization Algorithm and Its Application. Knowledge-Based Systems, 67, 2014: 218–229. https://doi.org/10.1016/j.knosys.2014.05.004
[6] M. Khishe, M.R. Mosavi, Chimp Optimization Algorithm. Expert Systems with Applications, 149, 2020: 113338. https://doi.org/10.1016/j.eswa.2020.113338
[7] D. Wang, D. Tan, L. Liu, Particle Swarm Optimization Algorithm: An Overview. Soft Computing, 22(2), 2018: 387–408. https://doi.org/10.1007/s00500-016-2474-6
[8] A. Faramarzi, M. Heidarinejad, B. Stephens, S. Mirjalili, Equilibrium Optimizer: A Novel Optimization Algorithm. Knowledge-Based Systems, 191, 2020: 105190. https://doi.org/10.1016/j.knosys.2019.105190
[9] T. Rahkar Farshi, Battle Royale Optimization Algorithm. Neural Computing and Applications, 33, 2021: 1139–1157. https://doi.org/10.1007/s00521-020-05004-4
[10] Q. Bai, Analysis of Particle Swarm Optimization Algorithm. Computer and Information Science, 3(1), 2010: 180. https://doi.org/10.5539/cis.v3n1p180
[11] Y. Zhang, S. Wang, G. Ji, A Comprehensive Survey on Particle Swarm Optimization Algorithm and Its Applications. Mathematical Problems in Engineering, 2015(1), 2015: 931256.
https://doi.org/10.1155/2015/931256
[12] M. Ghaemi, M.R. Feizi-Derakhshi, Forest Optimization Algorithm. Expert Systems with Applications, 41(15), 2014: 6676–6687. https://doi.org/10.1016/j.eswa.2014.05.009
[13] A.G. Gad, Particle Swarm Optimization Algorithm and Its Applications: A Systematic Review. Archives of Computational Methods in Engineering, 29, 2022: 2531–2561. https://doi.org/10.1007/s11831-021-09694-4
[14] F.H. Zhou, Z.Z. Liao, A Particle Swarm Optimization Algorithm. Applied Mechanics and Materials, 303-306, 2013: 1369–1372. https://doi.org/10.4028/www.scientific.net/AMM.303-306.1369
[15] R. Rao, Jaya: A Simple and New Optimization Algorithm for Solving Constrained and Unconstrained Optimization Problems. International Journal of Industrial Engineering Computations, 7(1), 2016: 19–34. https://doi.org/10.5267/j.ijiec.2015.8.004
[16] T. Liao, T. Stützle, M.A.M. de Oca, M. Dorigo, A Unified Ant Colony Optimization Algorithm for Continuous Optimization. European Journal of Operational Research, 234(3), 2014: 597–609.
https://doi.org/10.1016/j.ejor.2013.10.024
[17] L. Abualigah, D. Yousri, M. Abd Elaziz, A.A. Ewees, M.A. Al-Qaness, A.H. Gandomi, Aquila Optimizer: A Novel Meta-Heuristic Optimization Algorithm. Computers & Industrial Engineering, 157, 2021: 107250. https://doi.org/10.1016/j.cie.2021.107250
[18] A.R. Mehrabian, C. Lucas, A Novel Numerical Optimization Algorithm Inspired from Weed Colonization. Ecological Informatics, 1(4), 2006: 355–366. https://doi.org/10.1016/j.ecoinf.2006.07.003
[19] M. Khishe, M. Nezhadshahbodaghi, M.R. Mosavi, D. Martín, A Weighted Chimp Optimization Algorithm. IEEE Access, 9, 2021:158508–158539. https://doi.org/10.1109/ACCESS.2021.3130933
[20] H. Jia, H. Rao, C. Wen, S. Mirjalili, Crayfish Optimization Algorithm. Artificial Intelligence Review, 56(Suppl 2), 2023: 1919–1979. https://doi.org/10.1007/s10462-023-10567-4
[21] F.A. Hashim, K. Hussain, E.H. Houssein, M.S. Mabrouk, W. Al-Atabany, Archimedes Optimization Algorithm: A New Metaheuristic Algorithm for Solving Optimization Problems. Applied Intelligence, 51, 2021: 1531–1551. https://doi.org/10.1007/s10489-020-01893-z
[22] Y. Shi, An Optimization Algorithm Based on Brainstorming Process. In: Emerging Research on Swarm Intelligence and Algorithm Optimization. IGI Global, 2015: 1–35. https://doi.org/10.4018/978-1-4666-6328-2.ch001
[23] J.E. Onwunalu, L.J. Durlofsky, Application of a Particle Swarm Optimization Algorithm for Determining Optimum Well Location and Type. Computational Geosciences, 14, 2010: 183–198.
https://doi.org/10.1007/s10596-009-9142-1
[24] M.H. Amiri, N. Mehrabi Hashjin, M. Montazeri, S. Mirjalili, N. Khodadadi, Hippopotamus Optimization Algorithm: A Novel Nature-Inspired Optimization Algorithm. Scientific Reports, 14(1), 2024: 5032. https://doi.org/10.1038/s41598-024-54910-3
[25] S. Bandyopadhyay, S. Saha, U. Maulik, K. Deb, A Simulated Annealing-Based Multiobjective Optimization Algorithm: AMOSA. IEEE Transactions on Evolutionary Computation, 12(3), 2008: 269–283. https://doi.org/10.1109/TEVC.2007.900837
[26] B. Abdollahzadeh, N. Khodadadi, S. Barshandeh, P. Trojovský, F.S. Gharehchopogh, E.-S.M. El-kenawy, L. Abualigah, S. Mirjalili, Puma Optimizer (PO): A Novel Metaheuristic Optimization Algorithm and Its Application in Machine Learning. Cluster Computing, 27(4), 2024: 5235–5283.
https://doi.org/10.1007/s10586-023-04221-5
[27] M. Dehghani, Z. Montazeri, E. Trojovská, P. Trojovský, Coati Optimization Algorithm: A New Bio-Inspired Metaheuristic Algorithm for Solving Optimization Problems. Knowledge- Based Systems, 259, 2023: 110011. https://doi.org/10.1016/j.knosys.2022.110011
[28] A.E. Ezugwu, J.O. Agushaka, L. Abualigah, S. Mirjalili, A.H. Gandomi, Prairie Dog Optimization Algorithm. Neural Computing and Applications, 34, 2022: 20017–20065. https://doi.org/10.1007/s00521-022-07530-9
[29] A.A. Heidari, S. Mirjalili, H. Faris, I. Aljarah, M. Mafarja, H. Chen, Harris Hawks Optimization: Algorithm and Applications. Future Generation Computer Systems, 97, 2019: 849–872.
https://doi.org/10.1016/j.future.2019.02.02
[30] S. He, Q.H. Wu, J.R. Saunders, Group Search Optimizer: An Optimization Algorithm Inspired by Animal Searching Behavior. IEEE Transactions on Evolutionary Computation, 13(5), 2009: 973–990.
https://doi.org/10.1109/TEVC.2009.2011992
[31] B. Abdollahzadeh, F.S. Gharehchopogh, A Multi-Objective Optimization Algorithm for Feature Selection Problems. Engineering with Computers, 38(Suppl 3), 2022: 1845–1863. https://doi.org/10.1007/s00366-021-01369-9
[32] T.S. Ayyarao, N.S.S. Ramakrishna, R.M. Elavarasan, N. Polumahanthi, M. Rambabu, G. Saini, B. Khan, B. Alatas, War Strategy Optimization Algorithm: A New Effective Metaheuristic Algorithm for Global Optimization. IEEE Access, 10, 2022:25073–25105. https://doi.org/10.1109/ACCESS.2022.3153493
[33] J.S. Pan, L.G. Zhang, R.B. Wang, V. Snášel, S.C. Chu, Gannet Optimization Algorithm: A New Metaheuristic Algorithm for Solving Engineering Optimization Problems. Mathematics and Computers in Simulation, 202, 2022: 343–373. https://doi.org/10.1016/j.matcom.2022.06.007
[34] https://github.com/JJJJGOOD/ACP-MO ” (Access: 23 June 2025)
© 2025 by the author. This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0)
Volume 10
Number 2
June 2025
Last Edition
Volume 10
Number 2
June 2025
How to Cite
J. Zhang, ACP-MO: A Novel Metaheuristic Optimization Algorithm Based on an Advanced Ceramic Processing Metaphor for Optimization. Applied Engineering Letters, 10(2), 2025: 109-124.
https://doi.org/10.46793/aeletters.2025.10.2.5
More Citation Formats
Zhang, J. (2025). ACP-MO: A Novel Metaheuristic Optimization Algorithm Based on an Advanced Ceramic Processing Metaphor for Optimization. Applied Engineering Letters, 10(2), 109-124.
https://doi.org/10.46793/aeletters.2025.10.2.5
Zhang, Jincheng. ACP-MO: “A Novel Metaheuristic Optimization Algorithm Based on an Advanced Ceramic Processing Metaphor for Optimization.“ Applied Engineering Letters, vol. 10, no. 2, 2025, pp. 109-124.
https://doi.org/10.46793/aeletters.2025.10.2.5
Zhang, Jincheng. 2025. ACP-MO: “A Novel Metaheuristic Optimization Algorithm Based on an Advanced Ceramic Processing Metaphor for Optimization.“ Applied Engineering Letters, 10 (2): 109-124.
https://doi.org/10.46793/aeletters.2025.10.2.5
Zhang, J. (2025). ACP-MO: A Novel Metaheuristic Optimization Algorithm Based on an Advanced Ceramic Processing Metaphor for Optimization. Applied Engineering Letters, 10(2), pp. 109-124.
doi: 10.46793/aeletters.2025.10.2.5.
Using lean manufacturing to improve process efficiency in a fabrication company
Authors:
Andra Maria Popa1
, Kapil Gupta1
1University of Johannesburg, Mechanical and Industrial Engineering Technology, Johannesburg, South Africa
Received: 29 June 2024
Revised: 20 September 2024
Accepted: 26 September 2024
Published: 30 September 2024
Abstract:
This article presents a case study on improving process efficiency in a mining equipment part fabrication company. The company was facing issues concerning communication, organisation, and workflow processes. This study investigated that ineffective communication among departments was the major weakness which was responsible for the long lead or idle time. This lead time was a waste that affected the company’s productivity. A great amount of time was spent on non-value-added processes. The Kanban Centralised Communication System was implemented. Time study and value stream mapping were also used. A significant improvement in process efficiency from 34% to 85% was achieved by reducing lead time from 4200 minutes to 1680 minutes after streamlining the communication in the company using Kanban.
Keywords:
Lean manufacturing, Kanban, Optimization, Process efficiency, Production lead time, Value stream mapping
References:
[1] A. Belhadi, F.E. Touriki, S. Elfezazi, Evaluation of critical success factors (CSFs) to implement Lean implementation in SMES using AHP: A case study. International Journal of Lean Six Sigma, 10(3), 2019: 803-829. https://doi.org/10.1108/IJLSS-12-2016-0078
[2] K.S. Minh, S. Zailani, M. Iranmanesh, S. Heidari, Do lean manufacturing practices have a negative impact on job satisfaction. International Journal of Lean Six Sigma, 10(1), 2019: 257-274. https://doi.org/10.1108/IJLSS-11-2016-0072
[3] K. Das, M. Dixon, Lean manufacturing and service. CRC Press, Boca Raton, 2024. https://doi.org/10.1201/9781003121688
[4] S. Gupta, P. Chanda, A case study concerning the 5S Lean technique in a scientific equipment manufacturing company. Grey Systems: Theory and Application, 10(3), 2020:339-357. https://doi.org/10.1108/GS-01-2020-0004
[5] J.P. Davim, Progress in Lean Manufacturing. Springer Cham, 2018. https://doi.org/10.1007/978-3-319-73648-8
[6] L. Dubey, K. Gupta, Lean manufacturing based space utilization and motion waste reduction for efficiency enhancement in a machining shop: A case study. Applied Engineering Letters, 8(3), 2023: 121-130. https://doi.org/10.18485/aeletters.2023.8.3.4
[7] Y. Shi, X. Wang, X. Zhu, Lean manufacturing and productivity changes: the moderating role of R&D. International Journal of Productivity and Performance Management, 69(1), 2019:169-191. https://doi.org/10.1108/IJPPM-03-2018-0117
[8] S. Sahoo, S. Yadav, Lean implementation in small- and medium-sized enterprise. Benchmarking: An International Journal, 25(4), 2018: 1121-1147. https://doi.org/10.1108/BIJ-02-2017-0033
[9] S. Caceres-Gelvez, M.D. Arango-Serna, J.A. Zapata-Cortes, Evaluating the performance of a cellular manufacturing system proposal for sewing department of a sportswear manufacturing company: A simulation approach. Journal of Applied Research and Technology, 20(1), 2022: 68-83. https://doi.org/10.22201/icat.24486736e.2022.20.1.1335
[10] H.H. Berhe, Application of Kaizen philosophy for enhancing manufacturing industries’ performance: exploratory study of Ethiopian chemical industries. International Journal of Quality & Reliability Management, 39(1),2022: 204-235. https://doi.org/10.1108/IJQRM-09-2020-0328
[11] C. Hemalatha, K. Sankaranarayanasamy, N. Durairaaj, Lean and agile manufacturing for work-in-process (WIP) control. Materials Today Proceedings, 46(20), 2021: 10334-10338. https://doi.org/10.1016/j.matpr.2020.12.473
[12] J. Singh, H. Singh, A. Singh, J. Singh, Managing industrial operations by Lean thinking using value stream mapping and six sigma in manufacturing unit. Management Decision, 58(6), 2019: 1118-1148. https://doi.org/10.1108/MD-04-2017-0332
[13] C. Veres, L. Marian, M.S. Moica, K. Al-Akel, Case study concerning 5S method impact in an automotive company. Procedia Manufacturing, 22, 2018: 900-905. https://doi.org/10.1016/j.promfg.2018.03.127
[14] J.C-C. Chen, C.-Y. Cheng, Solving social loafing phenomenon through Lean-Kanban: A case study in non-profit organization. Journal of Organizational Change Management, 31(5), 2017: 984-1000. https://doi.org/10.1108/JOCM-12-2016-0299
[15] T. Bandoophanit, S. Pumprasert, The paradoxes of just-in-time system: an abductive analysis of a public food manufacturing and exporting company in Thailand. Management Research Review, 45(8), 2022: 1019-1043 https://doi.org/10.1108/MRR-04-2021-0262
[16] S. Gawande, J.S. Karajgikar, Implementation of Kanban, a Lean tool, In Switchgear Manufacturing Industry – A Case Study. Proceedings of the International Conference on Industrial Engineering and Operations Management, July 26-27, 2018, Paris, France, 2335-2348.
[17] M.A. Habib, R. Rizvan, S. Ahmed, Implementing Lean manufacturing for improvement of operational performance in a labeling and packaging plant: A case study in Bangladesh. Results in Engineering, 17, 2023:100818. https://doi.org/10.1016/j.rineng.2022.100818
[18] A.K. Das, M.C. Das, Productivity improvement using different Lean approaches in small and medium enterprises (SMEs). Management Science Letters, 13, 2023: 51-64. https://doi.org/10.5267/j.msl.2022.9.002
[19] P.A. Marques, D. Jorge, J. Reis, Using Lean to Improve Operational Performance in a Retail Store and E-Commerce Service: A Portuguese Case Study. Sustainability, 14(10), 2022: 5913. https://doi.org/10.3390/su14105913
[20] F. Khair, M. A. S. Putra, I. Rizkia, Improvement and analysis of aircraft maintenance flow process using Lean manufacturing, PDCA, PICA, and VSM for sustainable operation system. IOP Conf. Series: Earth and Environmental Science, 1324, 2024: 012071. https://doi.org/10.1088/17551315/1324/1/012071
[21] I. Rizkya, K. Syahputri, R.M. Sari, D.S. Situmorang, Lean Manufacturing: Waste Analysis in Crude Palm Oil Process. IOP Conference Series: Materials Science and Engineering, 851, 2020: 012058. https://doi.org/10.1088/1757-899X/851/1/012058
[22] A. Pradeep, K. Balaji, Reduction of lead time in an automobile rubber component manufacturing process through value stream mapping. Proceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering, 236(6), 2022:2470-2479. https://doi.org/10.1177/09544089221094094
[23] D. Cabezas, I. Muelle, E. Avalos-Ortecho, Implementation of Lean Manufacturing to Increase the Machine’s Availability of a Metalworking Company. 7 th North American International Conference on Industrial Engineering and Operations Management, June 12-14, 2022, Orlando, Florida, USA.
[24] W. Kosasih, I.K. Sriwana, E.C. Sari, C.O. Doaly, Applying value stream mapping tools and kanban system for waste identification and reduction (case study: a basic chemical company). IOP Conference Series: Materials Science and Engineering, 528, 2019: 012050. https://doi.org/10.1088/1757-899X/528/1/012050
[25] B.S. Patel, M. Sambasivan, R. Panimalar, R. Krishna, A relationship analysis of drivers and barriers of Lean manufacturing. The TQM Journal, 34(5), 2022: 845-876. https://doi.org/10.1108/TQM-12-2020-0296
© 2024 by the author. This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0)
Volume 10
Number 2
June 2025
Last Edition
Volume 10
Number 2
June 2025
How to Cite
V.H. Quan, Research and Optimization of Sport Utility Vehicle Aerodynamic Design. Applied Engineering Letters, 9(2), 2024: 105-115.
https://doi.org/10.46793/aeletters.2024.9.2.5
More Citation Formats
Quan, V.H. (2024). Research and Optimization of Sport Utility Vehicle Aerodynamic Design. Applied Engineering Letters, 9(2), 105-115.
https://doi.org/10.46793/aeletters.2024.9.2.5
Quan, Vu Hai, “Research and Optimization of Sport Utility Vehicle Aerodynamic Design.“ Applied Engineering Letters, vol. 9, no. 2, pp. 2024, 105-115.
https://doi.org/10.46793/aeletters.2024.9.2.5
Quan, Vu Hai, 2024. “Research and Optimization of Sport Utility Vehicle Aerodynamic Design.“ Applied Engineering Letters, 9 (2):105-115.
https://doi.org/10.46793/aeletters.2024.9.2.5
Quan, V.H. (2024). Research and Optimization of Sport Utility Vehicle Aerodynamic Design. Applied Engineering Letters, 9(2), pp. 105-115.
doi: 10.46793/aeletters.2024.9.2.5.