Data-Driven Optimization of CNC Manufacturing Using Simulation and DOE Techniques
In the highly competitive manufacturing environment of today, operational success depends on increasing efficiency and cutting waste. The goal of this research is to use Arena simulation software to model a CNC production system to assess and improve system performance. Three different parts are pro...
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-07-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/15/14/7637 |
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| author | Vijay Sevella Ahad Ali Abdelhakim Abdelhadi Ahmad Alkhaleefah |
| author_facet | Vijay Sevella Ahad Ali Abdelhakim Abdelhadi Ahmad Alkhaleefah |
| author_sort | Vijay Sevella |
| collection | DOAJ |
| description | In the highly competitive manufacturing environment of today, operational success depends on increasing efficiency and cutting waste. The goal of this research is to use Arena simulation software to model a CNC production system to assess and improve system performance. Three different parts are processed by the model, which also includes rework loops in which a portion of faulty products are sent back for further processing. Finding bottlenecks, evaluating important performance metrics such as output, queue lengths, waiting times, and machine utilization, and testing improvement scenarios are the primary goals. Study findings indicate that waiting times were greatly shortened and resource usage was balanced in alternative scenarios, which were accomplished by shifting workloads, line balancing, and modifying inter-arrival durations. The results demonstrate how well simulation can represent and resolve inefficiencies in intricate industrial systems. Manufacturers may optimize manufacturing processes without interfering with ongoing operations thanks to this method, which encourages educated decision-making. |
| format | Article |
| id | doaj-art-b152aaeaa65241a7ab17adc67ffdd005 |
| institution | Kabale University |
| issn | 2076-3417 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj-art-b152aaeaa65241a7ab17adc67ffdd0052025-08-20T03:32:31ZengMDPI AGApplied Sciences2076-34172025-07-011514763710.3390/app15147637Data-Driven Optimization of CNC Manufacturing Using Simulation and DOE TechniquesVijay Sevella0Ahad Ali1Abdelhakim Abdelhadi2Ahmad Alkhaleefah3A. Leon Linton Department of Mechanical, Robotics and Industrial Engineering, College of Engineering, Southfield, MI 48075, USAA. Leon Linton Department of Mechanical, Robotics and Industrial Engineering, College of Engineering, Southfield, MI 48075, USAEngineering Management Département, College of Engineering, Prince Sultan University, Riyadh 11586, Saudi ArabiaEngineering Management Département, College of Engineering, Prince Sultan University, Riyadh 11586, Saudi ArabiaIn the highly competitive manufacturing environment of today, operational success depends on increasing efficiency and cutting waste. The goal of this research is to use Arena simulation software to model a CNC production system to assess and improve system performance. Three different parts are processed by the model, which also includes rework loops in which a portion of faulty products are sent back for further processing. Finding bottlenecks, evaluating important performance metrics such as output, queue lengths, waiting times, and machine utilization, and testing improvement scenarios are the primary goals. Study findings indicate that waiting times were greatly shortened and resource usage was balanced in alternative scenarios, which were accomplished by shifting workloads, line balancing, and modifying inter-arrival durations. The results demonstrate how well simulation can represent and resolve inefficiencies in intricate industrial systems. Manufacturers may optimize manufacturing processes without interfering with ongoing operations thanks to this method, which encourages educated decision-making.https://www.mdpi.com/2076-3417/15/14/7637simulation modelingArenalayout designline balancingsystem bottleneck |
| spellingShingle | Vijay Sevella Ahad Ali Abdelhakim Abdelhadi Ahmad Alkhaleefah Data-Driven Optimization of CNC Manufacturing Using Simulation and DOE Techniques Applied Sciences simulation modeling Arena layout design line balancing system bottleneck |
| title | Data-Driven Optimization of CNC Manufacturing Using Simulation and DOE Techniques |
| title_full | Data-Driven Optimization of CNC Manufacturing Using Simulation and DOE Techniques |
| title_fullStr | Data-Driven Optimization of CNC Manufacturing Using Simulation and DOE Techniques |
| title_full_unstemmed | Data-Driven Optimization of CNC Manufacturing Using Simulation and DOE Techniques |
| title_short | Data-Driven Optimization of CNC Manufacturing Using Simulation and DOE Techniques |
| title_sort | data driven optimization of cnc manufacturing using simulation and doe techniques |
| topic | simulation modeling Arena layout design line balancing system bottleneck |
| url | https://www.mdpi.com/2076-3417/15/14/7637 |
| work_keys_str_mv | AT vijaysevella datadrivenoptimizationofcncmanufacturingusingsimulationanddoetechniques AT ahadali datadrivenoptimizationofcncmanufacturingusingsimulationanddoetechniques AT abdelhakimabdelhadi datadrivenoptimizationofcncmanufacturingusingsimulationanddoetechniques AT ahmadalkhaleefah datadrivenoptimizationofcncmanufacturingusingsimulationanddoetechniques |