IJLTEMAS International Journal of Latest Technology in Engineering, Management & Applied Science (IJLTEMAS) IJLTEMAS 2278-2540 IJLTEMAS 418 10.51583/IJLTEMAS.2026.150900067 Mechanical Technology A Survey of CNC Lathe Machining Parameters and Their Perceived Effects on Surface Finish and Tool Wear in Government Technical College Workshops in Rivers and Bayelsa States, South-South Nigeria Samson Oluwatimilehin Ariyo Department of Industrial Technical Education University of Nigeria Nsukka Nigeria Eteli Harold Imbasi Department of Industrial Technical Education University of Nigeria Nsukka Nigeria Ayodele Ajoze Emmanuel Department of Industrial Technical Education University of Nigeria Nsukka Nigeria Olushola Jacob Abraham Department of Industrial Technical Education University of Nigeria Nsukka Nigeria Yahaya Abdulmalik Ibrahim Department of Industrial Technical Education University of Nigeria Nsukka Nigeria Bala Illo Shamsuddeen Department of Industrial Technical Education University of Nigeria Nsukka Nigeria Emmanuel Eneojo Akuh Department of Industrial Technical Education University of Nigeria Nsukka Nigeria Yunusa Umar Department of Industrial Technical Education University of Nigeria Nsukka Nigeria 15 9 1871 1879 19 09 2026 24 09 2026 12 10 2026 Cutting Speed Feed Rate Depth of Cut CNC Lathe Machining Parameters Surface Finish Tool Wear Technical College Workshops Abstract

This study surveyed CNC lathe machining parameters such as cutting speed, feed rate, and depth of cut and their perceived effects on surface finish and tool wear in Government Technical College workshops in Rivers and Bayelsa States, South-South Nigeria. The general purpose of the study was to determine the extent to which these machining parameters are currently applied in the sampled workshops and how they are perceived to influence surface finish quality and tool wear. Three research questions were posed and three null hypotheses formulated to guide the study. A survey research design was adopted. The research was carried out in 8 Government Technical College workshops across Rivers and Bayelsa States: GSTC Okaka-Yenagoa, GSTC Swali, GTC Port Harcourt, GTC Tombia, GSTC Sampou, GSTC Ofoni, GTC Ahoada, and GSTC Ayamassa. The population of the study was 183 respondents, comprising 16 mechanical technology teachers, 8 workshop assistants, and 169 mechanical technology students. A 30-item structured questionnaire was used to collect data. The instrument was validated by experts from the Department of Industrial and Technical Education, University of Nigeria Nsukka, and yielded a Cronbach Alpha reliability coefficient of 0.78. Data were analyzed on a four-point scale using mean and standard deviation to answer the research questions, while Analysis of Variance (ANOVA) was used to test the null hypotheses at the 0.05 level of significance. Findings showed that respondents generally agreed that cutting speed, feed rate, and depth of cut are currently applied in their workshops, and that these parameters are perceived to influence both surface finish quality and tool wear. No significant difference was found in the perceptions of teachers, workshop assistants, and students across all three research questions, and all null hypotheses were therefore accepted. The study recommends the development of documented parameter charts and routine surface finish and tool wear inspection practices to strengthen consistency in machining outcomes.

 References Aggarwal, D., & Singh, R. (2018). Investigation on Effect of Material Hardness in High-Speed CNC End Milling Process. PMC. Ahmed, H., & Hussain, M. (2025). Effect of Cutting Speed, Feed Rate, and Depth of Cut on Surface Roughness in CNC Milling of Aluminium 6061.ResearchGate Ayed, M. T. (2011). CNC Machines, Overview and General Aspects. School of Engineering, Design and Technology, University of Bradford, UK. Breaz, R. E., et al. (2024). "Impact of Process Parameters on CNC Milling Machine Operation to Optimize the Response Parameter Surface Roughness Using DOE Met." International Journal of Research Publication and Reviews, 5(12), pp. 4553-4559. Chen, T., Lee, J., & Wang, Y. (2021). Integrated Design of Spindle Speed Modulation and Cutting Vibration Suppression Controls Using Disturbance Observer for Thread Milling. MDPIJournal Csiszár, S., & Bányai, D. (2023). Comparative Analysis of Cutting Forces in CNC Milling of MDF: The Role of Tool Coatings, Cutting Speed, and Feed Per Tooth. MDPI Journal Das, S. R., Panda, A., Dhupal, D., & Kumar, A. (2017). Experimental investigation of surface roughness, flank wear, and cutting forces in machining of hardened steel. Manufacturing Review, 4(12), 1–9. https://doi.org/10.1051/mfreview/2017011 Ekengwu, I. E., &Emeruwa, K. I. (2024). Comprehensive Review of Computer Numerical Control (CNC) Systems. International Research Journal of Scientific Studies, 1(1), 50–55. Retrieved from https://irjss.com/index.php/j/article/view/8 Emeli, A. N., & Emeli, N. A. (2021). Practical Skills Acquisition in Technical Education: The Role of Workshop Facilities. Journal of Vocational and Technical Studies, 15(2), 45-58. Eyong, A. (2021). Assessment of the technical college workshop as a facility for effective technical and vocational education and training. [Unpublished master's thesis]. University of Calabar. Groover, M. P. (2020). Fundamentals of Modern Manufacturing: Materials, Processes, and Systems (7th ed.). Wiley. Hazir, E. (2018). "Optimization of CNC cutting parameters using design of experiment (DOE) and desirability function." Gazi University Journal of Science, 31(4), pp. 297-308. International Organization for Standardization ISO, (1993). Tool-life testing with single-point turning tools. Second edition. ISO 3685:1993. Geneva, Switzerland: Kiran, C., Clement, S., & Chelladurai, H. (2016). "Experimental Investigation on Determination of CNC Machining Parameters for MDF." International Journal of Scientific Research in Science, Engineering and Technology. Kumar, R., & Kumar, R. (2015). Design, Analysis and Testing of Spindle for high-speed CNC Lathe Machine. International Journal of Advanced Research in Engineering, Science andManagement.Ijarasem Li, C. (2024). Influence of tool wear and workpiece diameter on surface quality in turning. Metals, 14(3), 612. https://doi.org/10.3390/met14030612 Loh, M. W., Ooi, C. C., & Low, Y. G. (2020). Relationship between Cutting Depth and Spindle Speed on Cutting Accuracy of Aluminum 6061 on the TU-3A Retrofit CNC Machine. MDPI. National Board for Technical Education. (2013). Standards for the accreditation of diploma programmes in polytechnics and similar post-secondary technical institutions in Nigeria. NBTE. https://www.nbte.gov.ng/nbte/sites/default/files/2024- Pérez-Salinas, C., López de Lacalle, L. N., Urbicain, G., & Martínez, S. (2024). The relationship between the cutting-edge, tool wear, and chip formation: An updated review. The International Journal of Advanced Manufacturing Technology, 126(5–6), 3127–3149. https://doi.org/10.1007/s00170-023-12694-y Putra, Y. M., Wicaksono, S., & Nugroho, A. (2022). Optimization of machining parameters using Taguchi method in turning processes. Journal of Manufacturing Engineering, 7(2), 45–53. https://doi.org/10.5281/zenodo.7110245 Saini, N., & Singh, R. (2023). Optimisation of Machining Parameters for CNC Milling of FibreReinforced Polymers. ResearchGate. Soori, M., & Arezoo, B. (2022). Cutting Tool Wear Prediction in Machining Operations, A Review. Journal of New Technology and Materials, 12(2), 15–26. Srivastava, A. K., & Veldhuis, S. C. (2007). "Modelling geometric and thermal errors in a five-axis CNC machine tool." International Journal of Advanced Manufacturing Technology, 34(3), pp. 325-339. Usca, U. A., Yazici, H., & Cengiz, M. (2022). Tool wear, surface roughness, cutting temperature and machinability characteristics in turning operations: A review. Journal of Manufacturing Processes, 82, 437–459. https://doi.org/10.1016/j.jmapro.2022.08.017 Uwaifo, O. V. (2005). Provision of workshop tools and equipment: A necessity for technical and vocational education graduates’ skills acquisition. Journal of Technology and Education in Nigeria, 10(1), 121–126. V. K. Jain (2017). Tool-Wear Analysis Using Image Processing of the Tool Flank. Machines, 5(4), 31.