RUNGTA INTERNATIONAL OF JOURNAL OF MECHANICAL AND AUTOMOBILE ENGINEERING

• Volume 2 (Jan 2025- Dec 2025)
Issue 1

1. A Generative AI-Based CAPP Framework for Real-Time Adaptive Manufacturing

Sameer Singh-1

Anant Kumar-1, Kush Kumar Dewangan-2, Sanjay G Sakharwade-3, Rahul Mishra-4, Suraj Bandhekar-4

Author Affiliations
1234- Department of Mechanical Engineering, Rungta College of Engineering & Technology, Bhilai, India- 490024

ABSTRACT:
Smart Manufacturing (SM), a cornerstone of Industry 4.0 (I4.0), enhances autonomy across cyber physical systems on the production floor. Connectivity, powered by Digital Twinning (DT), the Industrial Internet of Things (IIoT), Cloud Computing, and advanced sensors, facilitates real-time monitoring and decision-making. DT plays a pivotal role in production and operations management by integrating with a novel CAPP-GPT (Computer-Aided Process Planning–Generative Pretrained Transformer) and production scheduling framework. This hybrid methodology addresses shop floor disruptions by enabling self-healing capabilities at the micro-CAPP level, dynamically adjusting process parameters and toolpaths based on real-time process signature data. Inspired by advancements in NLP and LLMs like ChatGPT, the framework analyzes CAD models and blueprints using a combination of operations research and predictive analytics for setup planning, operation sequencing, and grouping. A hybrid approach incorporating Optimization, Logical Analysis of Data, and Machine Learning (ML) is employed to heuristically generate and modify process plans. At the macro-CAPP level, integration with delayed product differentiation, lotsizing, and transfer line balancing supports batch production in Hybrid Manufacturing (HM) and Smart Assembly systems.

Keywords: CAPP-GPT, Macro-CAPP, Scheduling, Micro-CAPP, Smart Manufacturing, Maintenance 4.0, Quality 4.0, Machine Learning

Corresponding author’s email address: sameer.singh@rungta.ac.in

2. Developments in wire arc additively produced Al-Zn-Mg-Cu alloys: improving mechanical characteristics, refining grains, and metallurgical flaws.

Anant Kumar-1,

Sameer Singh-1, Suraj Kumar Bandhekar-2, Kush Kumar Dewangan-3, Sanjay G Sakharwade-4, Rahul Mishra-5

Author Affiliations
12345- Department of Mechanical Engineering, Rungta College of Engineering & Technology, Bhilai, India- 490024

ABSTRACT:
Wire Arc Additive Manufacturing (WAAM) is a promising technique for metal additive manufacturing due to its high deposition rate, cost-effectiveness, and ability to produce large-scale components. Aluminium alloys, particularly those in the Al-Zn-Mg-Cu system, have gained significant attention due to their high strength-to-weight ratio, excellent mechanical performance, and broad applicability in aerospace, automotive, and military industries. However, several challenges limit the widespread adoption of WAAM technology for high-performance alloys. One major issue is the presence of metallurgical defects, such as porosity and cracking, which can compromise the structural integrity and performance of the final components. Additionally, achieving grain refinement is crucial for enhancing the material’s strength, ductility, and resistance to fatigue and corrosion. Current research focuses on developing strategies to mitigate defects, promote grain refinement, and improve the mechanical properties of WAAM-fabricated Al-ZnMg-Cu components, including optimizing process parameters, exploring post-processing treatments, and incorporating innovative alloy design or reinforcement techniques.

Keywords: Al-Zn-Mg-Cu alloys, Wire arc additive manufacturing, Metallurgical defects, Cracking, Refining grains.

Corresponding author’s email address: anant.kumar@rungta.ac.in

3. Study on the effectiveness of Non-Newtonian fluid-based Speed Braker

Nivesh Agrawal-1,Manoj Kumar Soni-2, Ishwar Prasad Sahu-3, Anand Kumbhare-4, Y. Venkat Ramana-5

Author Affiliations
12345 – Department of Mechanical Engineering, Rungta College of Engineering and Technology, Bhilai, India- 490024

ABSTRACT:
The study investigates the effectiveness of non-Newtonian fluid (NNF) based speed breakers as an innovative solution to enhance road safety and traffic control. Traditional speed breakers, while effective in reducing vehicle speed, often cause discomfort to drivers and can lead to vehicle damage over time. Non-Newtonian fluids, with their unique property of viscosity change under stress, offer a promising alternative. This research focuses on the development, testing, and analysis of a speed breaker prototype utilizing NNF technology. The study explores the fluid’s behaviour under varying vehicle loads and speeds, the mechanical design of the speed breaker, and its potential benefits compared to conventional rigid speed bumps. The results show that the NNFbased speed breaker provides a smoother driving experience while still effectively reducing vehicle speed. Furthermore, the adaptive nature of the non-Newtonian fluid allows for variable resistance, potentially enhancing the comfort and safety of road users. This study also highlights the environmental sustainability of the proposed system, as NNF-based speed breakers can be designed with eco-friendly materials and components. The findings suggest that NNF-based speed breakers could offer a viable solution to modernizing traffic control systems, balancing efficiency, safety, and user experience. Further research is recommended to refine the system and evaluate its performance under diverse environmental conditions.

Keywords: Non-Newtonian fluid, speed breaker, road safety, traffic control, vehicle speed, adaptive resistance, sustainable design.

Corresponding author’s email address: nivesh.agrawal@rungta.ac.in

4.Generation of Low Carbon Steel: Synthesis and Characterization

Anand Kumbhare-1, Manoj Soni-2, Nivesh Agrawal-3, Ishwar Sahu-4, Venkat Ramana-5, Gauri Kumbhare-6

Author Affiliations
123456- Department of Mechanical Engineering, RCET Bhilai
Department of Science, GDRCST Bhilai

ABSTRACT:
In the present investigation, multiphase microstructures containing a combination of ferrite, martensite, retained austenite and carbides have been produced by altering the cooling rate in low alloy steels. The mechanical properties have been evaluated and correlated with ensuing microstructural features. The quench interruption temperature was optimized with consideration of the ideal carbon concentration in untransformed austenite after partitioning to lower the Ms temperature to room temperature. After partitioning at an appropriate temperature, a significant fraction of austenite was retained through the enrichment of carbon into the untransformed austenite. Three samples have been heat treatment by following the cycle of quenching and partitioning. The samples were then compared with each other. In the first set, before going for Q & P treatment, samples were annealed. Then Q& P temperature was taken for 450 C and 350 C. Also, Q & P has been performed for fully and partially austenitization sample at 450 C. It has been observed that a significant reduction in grain size can be observed after Q&P heat treatment of the steel. Also, the hardness shows an efficient increase in comparison to annealed low carbon steel. This also gives evidence of the development of advanced high strength low carbon steel. Even though the less Q & P temperature shows more amount of martensite in the martensite which leads to high hardness then higher Q & P temperature. Austenitization temperature also have an effect on the mechanical properties as complete austenitization leads to have higher amount of martensite and retained austenite then partial austenitization sample, hence the increase in hardness can be observed in fully austenized Q&P sample.

Keywords: Quenching and Partitioning; low carbon steel; Microstructure; Hardness; Grain size analysis

Corresponding author’s email address: anand.kumbhare@rungta.ac.in

5. Artificial Intelligence in SOLIDWORKS: Applications and Impacts

Sanjay G Sakharwade-1, Kush Kumar Dewangan-2, Suraj Bandhekar-3, Rahul Mishra-4, Sameer Singh-5, Anant Kumar-6

Author Affiliations
123456- Department of Mechanical Engineering, Rungta College of Engineeing and Technology, Bhilai, India- 490024

ABSTRACT:
The integration of Artificial Intelligence (AI) and Machine Learning (ML) into SOLIDWORKS has revolutionized mechanical engineering workflows, enabling unprecedented efficiency, creativity, and precision in product design. This paper explores SOLIDWORKS’ AI-driven tools, their applications, and their transformative impact on the field. SOLIDWORKS 2025 introduces Aura AI, a context-aware assistant embedded directly into the CAD environment. Aura automates repetitive tasks, generates design alternatives, and provides real-time regulatory compliance insights, allowing engineers to focus on innovation. AI reduces repetitive tasks, allowing engineers to dedicate 40% more time to creative problem-solving. However, human oversight remains critical. SOLIDWORKS aims to expand industry-specific AI customization, particularly for aerospace and medical devices, while improving predictive maintenance algorithms using IoT sensor data. This synergy positions SOLIDWORKS as a leader in smart manufacturing, driving innovation while maintaining the critical role of engineering expertise.

Keywords: Solidworks; digital manufacturing; artificial intelligence; industry 4.0

Corresponding author’s email address: Sanjay.sakharwade@rungta.ac.in

RUNGTA INTERNATIONAL OF JOURNAL OF MECHANICAL AND AUTOMOBILE ENGINEERING