NUST Institutions Library Catalogue Search for 'an:"122372"'

Development of Continuous Drive Friction Welding (CDFW) model in ABAQUS for AA 6061-T6 alloy to verify experimental results and to predict behavior of similar and dissimilar alloys AA 6061-5083 /

By Elahi ,Muhammad Umar. . 42p. ; 30cm..

Place Hold on Development of Continuous Drive Friction Welding (CDFW) model in ABAQUS for AA 6061-T6 alloy to verify experimental results and to predict behavior of similar and dissimilar alloys AA 6061-5083 /

MENTAL WORKLOAD CALCULATION USING VACP METHOD AND DISCRETE EVENT SIMULATION /

By Zafar ,Muhammad Hassan. . 54p. ; 30cm..

Place Hold on MENTAL WORKLOAD CALCULATION USING VACP METHOD AND DISCRETE EVENT SIMULATION /

Development of Forward Flow Forming Model in ABAQUS for Al 7075 Alloy to Verify Experimental Results and Material Behavior Under Flow Forming Forces /

By Hassan, Zubair Islamabad : SMME- NUST; Soft Copy. . 53p. , Flow forming process is used to produce axis symmetric cylindrical parts with high precision. In the Aerospace sector, the flow forming method is employed extensively, particularly in the manufacture of missile casings and rocket motors. The nature of the process of flow forming is usually complex with high deformations with nonlinear behavior. Essentially, there are two processes of flow forming i.e. The forward flow forming and backwards flow forming. In this investigation the forward flow forming strategy was applied in which the roller and preform extrudes in the same direction. The present investigation will discuss the flow forming of Al 7075 alloy. A 3D Thermomechanical finite element model for forward flow forming of cylindrical workpiece of Al7075 alloy was developed in ABAQUS/Explicit Software. In order to correctly predict forces, instead of stress strain curve, the Johnson Cook material failure for Al7075 was used and its parameters were considered. The research work verified the experimental data with the Finite element analysis results. Changes in mandrel and feed speed were also examined for flow formation purposes. Additionally, the findings of the experiments were compared to the theoretical results. It was determined that the greatest force generated was axial, followed by radial and finally circumferential. In addition, the feed impact was investigated, and it was shown that an increase in feed also increases the axial force. 30cm.

Place Hold on Development of Forward Flow Forming Model in ABAQUS for Al 7075 Alloy to Verify Experimental Results and Material Behavior Under Flow Forming Forces /

Energy Analysis During Milling Operation of Aerospace Alloys/

By Zaidi, Syed Sajid Raza. . 249, p. 35 cm..

Place Hold on Energy Analysis During Milling Operation of Aerospace Alloys/

Effect of using sustainable Lubricants on Surface Roughness and Energy Consumption during Milling of Aerospace Alloys /

By Khan, Muhammad Ahsan Pervaiz. . 110p. , The manufacturing sector is increasingly seeking higher production rates, resulting in a greater demand for finished or near-finished components, where surface roughness serves as a crucial indicator of surface quality in machined parts. Alongside this, there is a robust effort to reduce energy consumption during machining processes, thereby lessening the carbon footprint associated with manufacturing. Milling is one of the most widely used cutting processes in the industry; however, the conventional lubricants used have raised significant health concerns. This study investigates the impact of sustainable lubricants, specifically sunflower oil, on surface roughness and energy consumption during the milling of aerospace alloys. In the present research, the machining parameters were varied using the Taguchi L9 array design of experiments, and their influence on the response parameters, including specific cutting energy and surface finish was ascertained under different conditions: dry, with conventional cutting oil, and using sustainable sunflower oil. Our analysis of variance revealed that feed per tooth (fz) was the most influential parameter, accounting for 55.46% and 65.69% of the variation in surface roughness and specific cutting energy, respectively. Notably, results indicated that sunflower oil as a lubricant not only decreased energy consumption but also offered an environmentally friendly alternative. Validation of the experimental design was achieved through confirmatory tests conducted under both optimal and suboptimal conditions, supporting the srobustness of our findings. 30cm.

Place Hold on Effect of using sustainable Lubricants on Surface Roughness and Energy Consumption during Milling of Aerospace Alloys /

Comparison of Different Machine Learning Models for Quality Control in Biscuit Manufacturing Industry of Pakistan /

By Awais, Muhammad . . 113p. , Ensuring consistent product quality is a critical challenge in the biscuit manufacturing industry, particularly in developing economies like Pakistan, where manual inspection remains the norm. This approach, however, is prone to human error, fatigue, and inconsistency, leading to variable quality control outcomes. This research proposes an intelligent, machine learning–based automated quality inspection system tailored for real-world biscuit production lines. A comprehensive dataset of 40,000 high-resolution images was curated, representing four popular biscuit varieties Rio, Sooper, Candy, and Marie captured under actual factory lighting conditions. The dataset includes both defective and non-defective samples, covering a wide range of defect types such as breakage, charring, deformation, and missing pieces. To ensure high-quality annotations with scalable efficiency, a semi-automated iterative annotation framework was developed, combining initial manual labeling with model-assisted annotation and human-in-the-loop refinement across multiple cycles. Multiple state-ofthe-art machine learning models were implemented, fine-tuned, and rigorously evaluated, including YOLOv8, YOLOv11, YOLOv12, Faster R-CNN (via Detectron2), and Vision Transformer (ViT-B/16). Models were assessed using key performance metrics such as mAP@0.5:0.95, precision, recall, F1-score, inference speed (FPS), and computational efficiency. The results demonstrate that modern deep learning models, particularly YOLOv12 and Vision Transformers, achieve high detection accuracy (mAP > 90%) while maintaining feasibility for real-time deployment when optimized. This study provides a comparative analysis of accuracy-speed trade-offs, offering actionable insights for manufacturers seeking cost-effective, scalable solutions. The research concludes with practical recommendations for integrating AI-driven inspection systems into existing production infrastructure in resource-constrained environments, balancing performance, hardware requirements, and long-term maintainability. 30cm.

Place Hold on Comparison of Different Machine Learning Models for Quality Control in Biscuit Manufacturing Industry of Pakistan /

Investigating the Impact of Process Parameters on the Hardness of UV Resin printed part in Stereo Lithography /

By Ahmed, Armaghan . . 81p. , his study examines the effect of major masked stereolithography (mSLA) process variables, namely, layer thickness, build orientation, and exposure time, on hardness of ultraviolet (UV) resin printed components. A Taguchi L9 orthogonal array design of experiments was used to perform nine experimental runs with Shore D hardness as the response variable measured per ASTM D2240. The parametric design allowed systematic testing of the parameteric effects with minimum number of trials. The results were interpreted using statistical methods, including analysis of variance (ANOVA), signal-tonoise (S/N) ratio analysis, regression modeling in order to determine the best processing conditions. Results show that exposure time is the most noticeable variable, with a contribution to the total variation in hardness of about 70 percent, build orientation and layer thickness added 13.5 per cent and 12.8 per cent respectively, and showed significant, but minor, effects on the response. The S/N ratios main effects plot indicated that the best parameter set to obtain maximum hardness is 0.100 mm layer thickness, 45deg build orientation, and 21 seconds exposure time. Finally, the exposure time is identified as the essential control parameter of the hardness, and orientation and thickness as the secondary refinements. The research provides a sound framework for process optimization within SLA. 360cm.

Place Hold on Investigating the Impact of Process Parameters on the Hardness of UV Resin printed part in Stereo Lithography /