IJPEM

Multi-scale Fabrication Techniques of Collagen Hydrogel for Developing Physiological 3D In vitro Barrier Model


김동성/POSTECH




  • Keywords : Collagen hydrogel, Multi-scale fabrication techniques, Self-assembly, Physical reshaping, In vitro barrier model
  • Life-like 3D in vitro barrier models, which recapitulate complex tissue compartments bridging the outside environments with the internal tissue, have garnered great attention because they provide tools for a better understanding of in vivo tissue physiology and pathology as well as more realistic drug and toxicity tests. Recent advancements in collagen hydrogel fabrication techniques offer immense possibilities in reproducing such 3D in vitro barrier models by providing well-defined extracellular matrix (ECM) analogs with physiological biochemical and biophysical microenvironments. This review focuses on multiscale fabrication techniques of collagen hydrogels to generate various geometries to reproduce structural microenvironments of the in vivo organ containing an epithelial barrier. The engineered collagen hydrogel created by the multiscale fabrication techniques enables the construction of in vivo-like tissue compartments (epithelium, connective tissue, and blood vessel) and their surrounding ECM, leading to the development of physiologically relevant in vitro barrier models. An overview of the state-of-the-art in vitro barrier models is presented based on the collagen hydrogels, which reproduce the epithelial barrier, epithelium–connective tissue interface, and epithelium–blood vessel barrier.
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[Free Access Period: 22. 4. 3. ~ 22. 5. 31.]
IJPEM-GT

Challenges in Minimizing Copper Dissolution for Lead Free Wave Soldering in Surface Mount Technology Going Towards Green Manufacturing


Mageswaran Arunasalam/Universiti Putra Malaysia




  • Keywords : Copper dissolution, Solderbility, Wave soldering, Turbulence, Preheating, Rework soldering
  • In surface mount technology, development toward green manufacturing by converting all leaded soldering processes to lead free soldering process has created a lot of challenges mainly in wave soldering process which led to copper dissolution to assemble board causing it to be scrapped if not contained. The paper aims to propose a workable and practical solution to reduce extensive copper dissolution in assemble board and expand the cycle of allowable rework in assemble board. The work was carried out using Six Sigma methodology with defining the problem and research goals, measure the details in various aspects of current process, analyse data to identify potential root cause in a process, improve the process and control the process through experimental approaches. Main factors contributing to copper dissolution were identified and analysed. Total of five factors were identified namely the printed circuit board (PCB) finishing and copper layer construction in PCB, component terminal and led finishing, soldering flux usage and solder alloy composition, environment control with the use of Nitrogen tunnelling and the last factor was on the process itself which was from the in-contact process with molten turbulence soldering or non-contact process with intrusive soldering. Combined controlled factors contributing to minimization of copper dissolution by reducing the direct contact time to molten solder with optimize solder alloy composition and process control was formulated. An increase of sixty percentage of boards with lower copper dissolution going through the lead free wave soldering and rework soldering were obtained, another forty percent reduction of board being scrapped were also obtained with boards going through the molten solder up to triple times.
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[Free Access Period: 22. 4. 3. ~ 22. 5. 31.]
IJPEM-GT

State of the Art in Defect Detection Based on Machine Vision


Fengzhou Fang/University College Dublin




  • Keywords : Machine vision, Defect detection, Image processing, Deep learning
  • Machine vision significantly improves the efficiency, quality, and reliability of defect detection. In visual inspection, excellent optical illumination platforms and suitable image acquisition hardware are the prerequisites for obtaining high-quality images. Image processing and analysis are key technologies in obtaining defect information, while deep learning is significantly impacting the field of image analysis. In this study, a brief history and the state of the art in optical illumination, image acquisition, image processing, and image analysis in the field of visual inspection are systematically discussed. The latest developments in industrial defect detection based on machine vision are introduced. In the further development of the field of visual inspection, the application of deep learning will play an increasingly important role. Thus, a detailed description of the application of deep learning in defect classification, localization and segmentation follows the discussion of traditional defect detection algorithms. Finally, future prospects for the development of visual inspection technology are explored.
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[Free Access Period: 22. 4. 3. ~ 22. 5. 31.]