NUST Institutions Library Catalogue Search for 'kw,wrdl: (su-br:"Engineering inspection.")'

Manufacturing Engineering and Technology /

By Kalpakjian, Serope,. Upper Saddle River, NJ : Prentice Hall, 2001 . xx, 1148 p. : 26 cm.. 0201361310

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Fundamentals of Modern Manufacturing : Materials, Processes, and Systems /

By Groover, Mikell P.,. New York : John Wiley & Sons, 2002 . x, 1008 p. : 26 cm.. 9788126512669

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Manufacturing Engineering and Technology /

By Kalpakjian, Serope,. New York : Prentice Hall, 2010 . xxiv, 1176 p. : 26 cm.. 9788177581706

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Power equipment engine technology /

By Abdo, Edward.. Clifton Park, NY : Delmar/Cengage Learning, 2011 . 1 online resource (xii, 398 pages) : , Includes index. 9781418053888

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Hot and cold water supply /

By Garrett, R. H.. Chichester, West Sussex, U.K. ; | Ames, Iowa : Wiley-Blackwell, 2008 . x, 411 p. : , Includes index 25 cm.. 9781405130028 (pbk. : alk. paper) | 1405130024 (pbk. : alk. paper)

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Underwater inspection and repair of bridge substructures /

Washington, D.C. : Transportation Research Board, National Research Council, 1981 . 77 p. : , "December 1981." 28 cm.. 0309034078 (pbk.) :

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Shock transmission units in construction /

By Patel, Dinesh J.,. . xviii, 208 pages : 26 cm.. 9780727757135 (hardcover) | 072775713X (hardcover)

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FIELD INSPECTION HANDBOOK, AN ON THE JOB GUIDE FOR CONSTRUCTION INSPECTORS CONTRACTOR ARCHITECTURE AND ENGINEERING

By SUTCLIFFE, LYSTRE L, BROCK, DAN S. NEWYORK MCGRAW HILL 1986 . XII,210-17P 0-07-007932-3

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Analysis of Adhesive Joints using Digital Image Correlation (DIC) /

By Farooq, Muhammad Kashif . . 83p. , In this study, the effect of cork particles on the failure behavior of SLJs was investigated experimentally through tensile testing and non-contact digital image correlation (DIC) methods. Cork particles within size range of 125-250 μm were added at 0, 0.25, 0.50, 0.75 and 1.0% wt. in a brittle epoxy. SLJs with and without cork particles were tested under a displacement control condition of 1.3 mm/min and digital images were captured during the deformation in order to analyze the fracture process. VIC 2D 7 software was used to determine the peel and shear strain distributions in the overlapped area of bonded joints. Tensile test and DIC results reveal that cork particles enhance the strength and ductility of adhesive joints. However, the effect of cork particles on ductility is more significant than strength of joint. The visual inspection of the captured images shows cork particles act as crack stopper and slow down the crack propagation along the bondline. 30cm.

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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.

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Development of Decision Support System for Non-Destructive Fruit Quality Estimation /

By Zeb, Ayesha. Rawalpindi, MCS (NUST), 2020 . xii, 143 p

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