Analisis Validitas CNC (Computer Numerical Control) Pick and Place pada Trainer Smart Manufacturing Industry 4.0 (SMI) T201 The Validity Analysis of CNC (Computer Numerical Control) Pick and Place on the Trainer Smart Manufacturing Industry 4.0 (SMI) T201

Main Article Content


Abstract

This study is motivated by the need to evaluate the validity and reliability of the automated control program in the CNC Pick and Place system on the Smart Manufacturing Industry 4.0 (SMI) T201 Trainer to ensure precise and efficient performance in the context of industrial automation. A quantitative experimental method was employed, involving stepwise testing of the system's main components, namely the suck pump, X- and Y-axis servo motors, and pneumatic cylinder. Data were collected from 15 trials, documented in video format, and analyzed quantitatively based on operational time and accuracy. The control logic was developed using flowcharts and state diagrams in the TIA Portal software, with performance standards referencing the ability to place 100 SMD components per hour. Instrument validity was assessed using the Pearson correlation coefficient at a 5% significance level, while criterion validity was determined by comparing machine outputs with manual standards. The results demonstrated that the system operates with stability, accuracy, and efficiency, as shown by an average arrangement time of 14.24 minutes for 25 bottles and a standard deviation of ±0.0065 minutes. All main components functioned optimally, the system’s validity was proven to be strong and significant, and operational reliability was confirmed through repeated testing. These findings affirm that the CNC Pick and Place system on the SMI T201 Trainer is a viable and reliable automation solution for intelligent technology-based industrial environments.

Keywords:
Download Full-Text PDF Direct PDF file • 6015.pdf

Share Article:

Citation Metrics:

Scopus

Downloads

Download data is not yet available.

Citation Metrics & Similar Scopus Articles

Data source Crossref
0
citations
Citation counts are source-specific and may differ because database coverage, reference matching, and update schedules are different. Counts are not added together. Crossref values represent citation links registered and matched by Crossref.
Check Secondary Documents in Scopus
Open this article in Scopus, then check the Secondary documents tab. Use Manual Citation Fallback only for counts you have verified manually.
Open in Scopus
Similar Scopus Articles
Scopus
  1. Shamuratov S.X. (2027)
    Sigmoid Neutralization Response of Acidic Soapstock Waste by Mineralized Phosphorite Residues: A 4-Parameter Logistic Approach
    Kompleksnoe Ispolzovanie Mineralnogo Syra, 342(3), 80-89
  2. Kazhikenova S.S. (2028)
    Modelling and Solving Problems of Sustainable Efficiency of Technological Processes in Metallurgy
    Kompleksnoe Ispolzovanie Mineralnogo Syra, 344(1), 65-78
  3. Merkibayev Y.S. (2028)
    Optimization of Aluminum Casting Process Using PLA-Based Casting Patterns and Analysis of their Thermal Behavior
    Kompleksnoe Ispolzovanie Mineralnogo Syra, 345(2), 5-15

Article Details

How to Cite
Prasetya, W. A., & Jaya, P. (2025). Analisis Validitas CNC (Computer Numerical Control) Pick and Place pada Trainer Smart Manufacturing Industry 4.0 (SMI) T201. TSAQOFAH, 5(3), 2793-2803. https://doi.org/10.58578/tsaqofah.v5i3.6015

References

Bogue, R. (2018). The Role of Robotics in Manufacturing. Industrial Robot: An International Journal, 45(6), 687–695.
Cano, J., Gonzalez, A., & Perez, L. (2020). Robotic Systems in Manufacturing: A Review. Robotics and Computer-Integrated Manufacturing, 61, 101844. https://doi.org/10.1016/j.rcim.2019.101844
Gonzalez, J., Smith, A., & Wang, Q. (2019). Object Recognition and Localization for Robotic Pick-and-Place. IEEE Transactions on Robotics, 35(4), 872–884. https://doi.org/10.1109/TRO.2019.2912345
Jiang, Y.-K. (2015). Application Research of PLC in the CNC System. Proceedings of the International Symposium on Research in Mechanical Engineering (ISRME-15), 231, 20.
Liu, H., Zhang, L., & Chen, X. (2019). Adaptation in Robotic Pick-and-Place Operations. International Journal of Advanced Robotics Systems, 16(5), 1–12. https://doi.org/10.1177/1729881419875123
Riaz, M., Khan, R., & Ahmed, Z. (2020). Automation in Food Processing: Current Trends. Food Control, 110, 107000. https://doi.org/10.1016/j.foodcont.2019.107000
Schilling, R. J. (2018). Fundamentals of Robotics: Analysis and Control. Prentice Hall.
Schwab, K. (2016). The Fourth Industrial Revolution (pp. 139–142). Crown Business.
Sutarman. (2018). Computer Numerical Control (CNC) Milling and Turning for Machining Process in Xintai Indonesia. Quest Journals: Journal of Research in Mechanical Engineering, 3(5), 1–7. http://www.questjournals.org/jrme/papers/vol3-issue5/A350107.pdf
Zhao, Y., Li, F., & Wang, M. (2019). Robotic Solutions for Warehouse Automation. Journal of Logistics Research, 1(2), 33–45.