Registration System Details for PCB’s and Stencils.

Introduction to PCB Registration

Printed Circuit Board (PCB) registration is a crucial process in the manufacturing of electronic devices. It ensures that the various layers of a PCB align precisely with each other, resulting in a functional and reliable end product. PCB registration is particularly important when using stencils for solder paste application, as misalignment can lead to poor solder joints and component placement issues.

In this article, we will explore the details of registration systems for PCBs and stencils, including the different types of registration marks, methods for achieving accurate alignment, and best practices for ensuring consistent results.

Types of PCB Registration Marks

Fiducial Marks

Fiducial marks are the most common type of registration mark used in PCB manufacturing. These marks are typically small, round, or cross-shaped features placed on the outer layers of a PCB. They serve as reference points for automated assembly equipment, allowing for precise alignment of the PCB during component placement and solder paste application.

Fiducial marks are usually made from copper or solder mask openings and are designed to be easily recognizable by machine vision systems. The size and shape of fiducial marks may vary depending on the specific requirements of the assembly process and the capabilities of the equipment being used.

Global Fiducial Marks

Global fiducial marks are used to align the entire PCB to the assembly equipment’s coordinate system. These marks are typically placed near the corners of the board and are used as the primary reference points for all other features on the PCB.

Local Fiducial Marks

Local fiducial marks, also known as component fiducials, are used to align individual components or groups of components to their respective footprints on the PCB. These marks are typically placed near the component’s location and are used in conjunction with global fiducial marks to ensure accurate placement.

PCB Panel Fiducial Marks

When multiple PCBs are manufactured on a single panel, panel fiducial marks are used to align the entire panel to the assembly equipment. These marks are typically placed near the corners of the panel and are used to ensure that all PCBs on the panel are accurately positioned relative to each other.

Stencil Registration

Stencil Fiducial Marks

Stencils used for solder paste application also require registration marks to ensure accurate alignment with the PCB. Stencil fiducial marks are typically placed in the same locations as the corresponding marks on the PCB, allowing for precise alignment between the stencil and the board.

Stencil Apertures

Stencil apertures are openings in the stencil that allow solder paste to be deposited onto the PCB’s solder pads. The size and shape of these apertures are carefully designed to match the corresponding pads on the PCB, ensuring that the correct amount of solder paste is applied to each pad.

Methods for Achieving Accurate Registration

Machine Vision Systems

Machine vision systems are widely used in PCB Assembly for achieving accurate registration between the PCB, stencil, and assembly equipment. These systems use cameras and image processing algorithms to detect and align the registration marks on the PCB and stencil.

Typical machine vision systems consist of the following components:

  1. Cameras: High-resolution cameras capture images of the PCB and stencil registration marks.
  2. Lighting: Consistent and uniform lighting is essential for accurate image capture and processing.
  3. Image processing software: Algorithms analyze the captured images to determine the location and orientation of the registration marks.
  4. Motion control systems: Based on the information provided by the image processing software, motion control systems adjust the position and orientation of the PCB or stencil to achieve accurate alignment.

2D vs. 3D Machine Vision

Machine vision systems can be classified as either 2D or 3D, depending on their capabilities:

  1. 2D machine vision systems: These systems use a single camera to capture a two-dimensional image of the registration marks. They are suitable for most PCB assembly applications, where the PCB and stencil are relatively flat and do not require depth information for accurate alignment.

  2. 3D machine vision systems: These systems use multiple cameras or specialized 3D imaging techniques to capture depth information in addition to the two-dimensional image. 3D systems are particularly useful for aligning components with significant height variations or for inspecting solder joint quality after reflow.

Importance of Lighting in Machine Vision

Proper lighting is critical for the accurate operation of machine vision systems in PCB assembly. Consistent and uniform lighting helps to eliminate shadows, glare, and reflections that can interfere with the accurate detection of registration marks.

Several types of lighting techniques are commonly used in PCB assembly, including:

  1. Bright-field illumination: This technique uses a single light source positioned directly above the PCB, creating a bright, uniform illumination of the surface. Bright-field illumination is suitable for detecting high-contrast features, such as copper fiducial marks on a solder mask background.

  2. Dark-field illumination: In this technique, the light source is positioned at an angle to the PCB surface, causing surface features to appear bright against a dark background. Dark-field illumination is useful for detecting low-contrast features or surface defects.

  3. Diffuse illumination: This technique uses a large, diffuse light source to minimize shadows and provide even illumination across the PCB surface. Diffuse illumination is particularly useful for detecting subtle surface features or variations in color.

MDMANDuJAGXwB9K3hLUCDSdRkgTULTaDDqEJt5C2fk3AjIx9ay5IzExjIwVJH4U6GTyZFyOVb6dDVnUY5D5V7j91c5UEYIDIMYzXbBlXKBB/KkBNKGAHPSkwCcg5rqixjsikwO/4UvHWgDd9KpsAHcio3c5AwSfbmrAA6AU9YSCCw68gdTWTqJDI44XZS4U8cn6VK8E0YHmRSIWAK7kYZB78iu58E6XdLcT380LRwC38uAyKQWdmB3JnsAD+ddvdQrcW1zCyq4lhkQKwBBLKR3rzJ5koT5UrjPBt4ztYY9D1pdyk4rRu7L7OWt7iJo5422uGGD+FZMkRQ5XO0+vNenTqxmuZDsStjtzQMn8Kn063F7K8e/YEjL527icMoxjI9avGwsCONSgx65jP/ALPWU8ZSpy5ZPX0Z1U8FWqx54rT1S/NmTkDGaV/kwevetZNKspORexyY67NpH44epJNJtQpL3KooHVgAAOnUtis/7Qod/wAH/kX/AGdiOy/8Cj/mQ6XqcaFbWbaqsf3L8Abifuv/AENWtS1MQbre2INwR8zdViB9ff8Az9c86Vp3ONUt8dOfLJ/PzKUafpy5zq9rz1yYsk/UyV50oYSdb2t36We/3Hrwq46FD2KS9eaO33meBySSSzEszMckk9yTTsc+laAsdP7atan8Yz/7Up4sLHr/AGnbn8Y//jlemsdQWl39z/yPJeX4h9F/4FH/ADM3b7U3gZ+ta32Gx/6CNvj6x/8AxdRtpunE5OpwfnH/APHKf1+h3f3P/IP7OxHZf+BR/wAzN5PTpS9AKu3GnJbwLPFcCdWfYuxRt6NzuDEdqpxguSCOn8+tb068Kq5oPQ5a1GdGXLUVn9/5CZIpSe9Ti3EgzuxtPOMH3qM2zscbxz0q+dGJCCevpT8lhipBZyKCC30J4/nSLazc7WUEeuSDTU49xjQnHPNAAGal8mXodv596ieGcMCOR+HFVdCEGBwD6/4005xmnbWyM0EfpVXENBPenZNJ1BP/ANejnrTGLknFOHcenBpm70FAzxTAePvc0rDGMU0ZJJpcg80AJluf/wBVMYmn5zRj0GaTAltdy53HP9KVtzSEDqfpUtsgIZnO0AZz61GSN5Kj1x3rGTKR20sr2WnaZpFk6xz3W6R59oBX5QSRtHU5/SuOuE16KeeM394xR2UskzbTg9RnNdBJGuqWUDJKYru3RQmSBjj7ozVWPTdUVQG8rd3xJn+YrF3NC4CcgVZyQvNRRrnJqYZ7ivMkzzwV88YqRQD2qNQN3SrA24rHmHYPLUjmmGEMelOzT1alzDsVXtEIJzise9tvvYPSt93AzxWTeuu1uM5pXNEjnH8wB1IPcfhVULg5NaxUHOarNEORQiyoRuFaumAvbS9fkkOD+tUtoxjFaFliOC55PzAEDsDjFbRJMmXiWQHgh24P1q4Zw+kpAy/6u5Lr1A5yO31qjcktcyFuMkE447VdkIXTlVR8xmHPsOtd0AM4qCf6UbABx1/OlOetJluo6V1wKHgAD9KlQfLkj6VCCeRUi7ulKQFmCNc5J4616D4a0C1SAanqCIchmiSYL5aIv/LRt3FUvCfh3T721TUboyPItw6pGCAmEx97jvmrvjnUZLO1sbGMhY7pnMwUDJjiK7FA9M/yrwcZXak4Ie+gmq+NIomkg0uEOUIUXEo/d8cEIg59MZP4Vkw+NddR8zpbSx918vYcexU1zySQPH+HHGKj4zXkSkacqPSjHovizT3dVCzqMbiB50EmOAxA5X/P084v9PuLOee1nQrJE7KxIOGAPDLnsa3PDFy1tqtptYhbh/s8q5wCJBgfrj8q2/Gdh5rafdRgeY2+3k5wCF+df6/5FdWFryUuVPQl6HD6NEI7qYj/AJ4MD+LrXTeHvC0Ooql3dLsslyqKvDSkccH0H+fbEsIvLuZgfvCNgehGdy12Hia+Gj6Rp+mWYCG4iaNygAxCqgPxjqxPX6+ta1Kko1JandW/3an6v9B11q3hDSHe3tLNJZUBVvskUaqCDjDSnkn86ht/FegyHZc6dNErHG4eXKuDx82dp/Q1wYeQ+3rnmpA+PvEVwyk76M4+VHoOpeFtE1SFrrT1iimkTdE0IUQSnOfmUDrXml/YNC8ivGUljZkdGBBUjg8V2/g/VJI7kaa7FoLgM0OTxHIqluM+tTeNbBPNs7yOMZmV4piOMsmCCfw/lXZhMRUhLlvoJnnVpHukClBnPWun0jQpNWnaGJQkSYM0xXIUHjA96yIV2ucLy3yr9Sa9Wtks/DmjB5QFMUSyT85Mlw4A2g49eBxXficTKOiJKUPhTwtpsRlvAkmPvS3kgSMH2AIH86Y0fw8nPk40ok/IAv7s/g64/nXC6tq15qty9xcOdvIiiU4SNc8ACqCMrHkYrx5VpX3LUe51l7ogkmvLDTAvl2wNzEhYvuQgMUQjry3H0rlp7V4JG7NkhwQQVYHBBFdX4XuorWayEpwtyZbVWJ4V3kLr+ZGPxp/jHTFgmivokVYrltkwH/PfLMWx7iunC4qUXyvY7ccvej/hX5HKWMYlubWA8ie4ijbHBwzbe9erR+G/DqAAafCcDBLl2Jx3OTXmujIf7U0nGB/xMLP9ZQK9bvLy1sbeW5uXCRRjJJ6k9lX3NdFarzHmsym8L+Gy277CoP8AsyS4/Itio28I+HCc/ZpPoJWx+tclqfifUdRdxFK9tbbmCJExRivTLsME1nRX2oxOJYry4Vwc581zn65Nec6rvozXlZ3Z8H+HSciGZf8Adk/xFZOueFNMtNPu7y1edZLdQ5WV1ZGXIBAwoPf1rW8Oa7LqayW90F+0wqGDjA85SSCdoGMjj/61W/EnOh6t/wBcQfXkOprWnWqXVpMjVOzPIpdgBA4OTVU4PFWJDuLnuefxquetfW03eKYhAOMClo4HNAHrXQgDBAowOpPTtSk4pDjtTAVcGg9cUAAd+aQqScjrSYgPHSpoUByznj3zikjjOCWHAoaQt8oyBngVnJgPkk5Kr93tSxIc726A8U+OAlDIwIC+x5omlGwKFx+uazGgkvZI2XZng9akGr3ndmYk5J+WqJAI5owoo5S7nZwsMDGMc9OlWlKkYrI0ufz4PmYFlZgTxyM5rSBx0NeRI5CYqlOCiohnvUqkkVzsBDGe1IVZRxTskVG8pANSWiGViBzWReSDGOtXJ7huc81kzTFzyKRoiIsSMVG3AzTiaYRk5NOJQhwccc1qpEkOkyXjD+NgvXlfu/zrPhgluJY0jxywHpxWt4huLS30+DTYSMgxtJ3+Uc/qa6YIzOTLFnye/firTN+5VCeASwHvVQcsMfnU7H5VBrvghELHnGeKVSKRqEBAOa6oooUHn+VSZIGaZxTxjFTIZ33gjXLKCCXTbuby5HuTJbFwdjbxgqW/Ada0PGNnHI+l3cqBoovOhfPIDHDL/X8q8zTHrj0PTBr07w/qdnr2mf2bfOHvIoykgfbvdBkJJGcdQP8AHvXz2NpNS5mUjiZobIsGhUp13A5x+ApiwZPBzmunvfCWpRuxtGjniySASEcc8DB4/WoLXwxrsjndCkAGPmmcAc+gXJ/SvKlE0uRaBp8kmq2B2sEik+0OwBIHljeMn3PH41teN7nyLbSolJEktxLICOCFjTaf/QhW9Y2Fno1rKzy8KheeeQADCj0HavNvEutLrGoNJCzfZLZTDag8E92fHua6sLRcpXREncr6Y5e5nzz+7Y5PX7y8Guh8YbjqmkrKG8mSyRUP8IcSuD/MVy2jEm7m9DA5/Hetd/bG18VaJbNIUF/aKAW7pKBjJ4+6+Af/ANVViE1Ud/I7qv8Au1P1f6HIXVlHGPlx+HHvWO1vMxJXPf1rqL+0v4HMM1rKNh+8qMyMOmVbGMU200y8uW/cW8jDjJ2ELz6seK45WOUp+FYppda09BkGGRpnPXCoOR+Ndj41cJpVsc4b7bGR6lfKkBx+Yq/o2iw6dvncK13KgWRgBtRepVTj864rxnrC3l8tnA2YLHcrEdGmJwx/DpW1CLcrmcmYunPEL/TxMf3QuoTIDx8u8E133jZi1np8R+492zsfdI2AH6mvLkkdXDr1Ugj1yOa9amWDxRocEsDBZHAlTdj5LiMFWRsdj9OnNdOKuKO5540MeeB/Wozb/hVm4gntZpIbhGjljYqwYEDIOOPao/MBxzXnNG5ZhV1trLafnjuN6nJGCHb0rufF4jOjPu+8LiEx/wC9hv6Zrn/Dtkl7cWiy5CQF7llIPz7XwF/HIqx451IA2unRkHZ/pUxBHBO6NV49OfzragnzXOnHu8oL+6vyOe0UZ1XSMdft9px7CQGuu8ZmWRNMtkJKFp5pFHcrtVSR+J/OuO8O4k1rRwT/AMvcbf8AfPzV6H4hs3ntUmij3y27Fjjr5RU7uvviuitoefHc84aJc4x0pmwgjbV9kRue/f61LFbRNyeteebk2gyvFqumEA5aURNjPKyAqc/nXaeJH2aFqzYzmAJ/326p/Wue0HT3kv4ZMER2rGVn6ZOMKorb8WZGgaiAM7vs4/8AIyGtae6M5bnksg/rmoTirEjDlf8A69V2xzzX29L4ESIeRSdDmgbsHH60Gt4oQuc0oUimYp4Jq7CAKAferUCoDuk6Dt1zVVevXrUxJC1lJiHzOXYquAgPGKt6bZ209xCl1KYYG8wvJwuNqlhy1UYl3Fi3+RU00nn7FAwEXbjtWTAddXKvI0duzG1jcrGWGGcA43H61Uckt+mKcQE+tRbsk8U0hjjj8aaSM9aXIpMrWiiBNpl4befnPlPw/Xj3rsUZWVWBBDAEEc8HmvPwSOhxW7peopGphnf5cr5bHOAPSvHkjA6fdgU5ZFz1qh9oB+6cj86YZ+eDXPKIGqzrjrVOWZQDzVVrk4PNU5J855rJotD55CenrVJiDnPWlMjFjnpSMq45NTYsjJUe/wBKQgninhR2p4TA3NwB+FXGIFrTfKtGku52A2LiJST34JNYd/cG7uZZP4SzbTzyCc85pbq9Z2aNP9WOM9cnr3qmMlsc4rspxJJUXvnpQcnPtQPloLdTXdCIEYzzuxweMZpwBPWkZgelOB/Ot0UJjB609SabgHnNLwCKmQC5x9alglmhkjmhdkljIZGUkFSD2IqLqcnpSc54rnlSU9GCPVdC8W6ZeRJBfXMcN1GqBpLgrGkx5yQcBQa1r/W9KsbG5vRcQTiJCUSGVHMjnhVG0nv7V4upU8EZFJhFzgc9h2H51wSy6LejGbGr6/q2sMxuZdtuHJitosCNfTJHJ/E1jk8DGaN24YPWlIArsp4eNNWiBpaMB9plb/pg3/oaVBpuq32lTLPaylH27WyAwZfRgcj9KsaNxcyf9cG/9DSskhSAT1wK5VSU6s4vyO+tphqfq/0PTLPx5pEiKL6Ke3lx8xjXzYSfbB3fpXRaZrOj6sJBYXKzNGA0ibHRlDcA4cCvEgdoqaCWSN98UjxnBGYyVOD7iuaWXQ6M4Lnb+MPE9zHPNpNhJ5axjbdyp95yww0YJHQd8VwJcsepJPJPenSYLOSxLE5JJJJPvUW7GfT1rWnQVNcqEP3HOO1d54E1eztY76wu51i8yZZ7cyHbGWKlXBY8A8CuB3A4q9aNhX4B9iAetFXDxqKzGerz33hLUZTaTz2U8oOAHypz/syYA/WoxpXg222yOmnrt5BluFx+RbH6V5M7jcxIHX6UxpFPrx2zx+tcv9nx7j5jv73XI9Pvb+9sPKmWdPstu6kCJTtX5wMYIG0j/PPEXVzLM8kkzs8sjM8jtySzHJ5qxM//ABJrFvW4fpx/FNWUSW5J4qqFJcrXmztx3xQ/wr8jofDBUa3opY8G6UDp1KkD9a9iIBGCPr9K8ChneIoUYqyMHRlOCrDkEEVqr4t8UxFtupykYx84Rvy3Cqnh+Y8+56Ve+GdOuXeWJnt5G6iMAxZ9dn/16hg8MW6Mplu5ZADkqiLGD7E5Jrz5PF3ipMEai5Oejorj9RU//Ca+Khgm8jPsYIh/Ja45YKSK52eswW0FvGscKBEHYZP5k81h+MSw0S4CZJM1uOM9A2a4dPHXihSd0tu/s0MY/wDQQK37Pxxod5ZyW2uI0UkitHLsiZ4pFOeRtyQa1hhmmhXOAdowDn7xJqLG6pp/szSzGHLQ+Y4hZ+C0e47S2Mdvaq+9QTxX0NKWlirin0pKTOSCOaXkda64sQUYP+eaBknpTs4rQBVxUuBtHrUQx1qUnIrGTAfEBzzUe47jUkfAP061DnL4/PvUADNk80wkjoKkIH4fzppAzWkQG44o2ijdjPFIW9jWgFfGOtAYjOO1SYUqf0qLHWvMlEzsX7XUpUYK4yhxk8ggdM1pGRJVDwyg+2cH8jXPAetPV9pz6VjKAjYMk3IJNN39qz1vZRwdpHv1xTvtvIO0e9YODGaKhjjgn8zVmKwuZGyRtU8/NgcVlDVZk5iRAR3YHiopdSv5s77iQDsqEqo7cY/xpKmM3J/7PsR+/m3SdlTGR9QKxbu/efKplYugHTP1qkxeRizMWY9SxJJ/GlK4GK2jTAAVXk1KNuBiotmcZ5FPDe3ArqjGwxzgDBzmjAxmmt83SjPGK6IoYYGDihQaAB+NL6YqxhnP0o6nijO3rSZJ6UAOyec9KQn0/wAaACM5pB3xS5QsPLECk5wTSAnvTtpIJHYUOI7CCne9RZNHmEcY4osI2NF3fapc9Ps7/wDoaVl4GB9BWjob7ruUf9O7/wDoaVlpKpHPoK8+C/fz9Ed9b/dafq/0HlQqn86dE4JIApjcj2qWFQTwMnFaTPPIZdwbA69aiwe9TSD5ye4J96jODWPUQigk4rStE+R2Pp+lZvIwQa0bQ/upCepHftQMpS/eI56mkyKkkHzHPc1Cf89qBGrNj+xLD0+0v/6FNWUCOlasv/IDsP8Ar5k/9CmrJwoOc1y4fZ+rO/HfFD/CvyHdRTflH1pabgDk10HnDlOad0x/+umgA4p316UrDFzn60mCaRzjBH5VYtvmYZGf8KTkkAJkgIQSfYE+9Dwj0YH0IIP612vhPQr59RstTkt9tlGszq8gUCQtG0a7VPPU5/Cr3jDRrqW6F/BbZt1tUWZ4wDhgzklgvPTHOKuFZIZ5zs2mlJNTSphmOe5qHIrvhO+oxMY5FOPIpRggUuM10KQwUVIwwoqMdec4qR8lVPbispSAfEDg45H6VAB87Z9asIMKee1RYOcj1PrU3Aa3WkOMZobOefrSE9u1axYxvv2peKUr0pgyM/WtbiIQaCDQBmht3Irk5SRCB1pOxpymkOB1qHERGQRQMZqTjGaPk5OOfxrNwENxg4FLg0cYpw2mmoIdh23j3pCpOOc0/cOhphbnirUR2FOAOlNBOfbmnZ60mMZNaWAXg9P60vGDSEccUme1WgFA79uaeCMim8UnHOef1pjFcKaMAYpMGgdaCkBOaFwKPLcn5f6mr8eianPEsyx7EYkAygrx69KaLSKRYU9SMYFSTaZd23+sKngnMeSP1qFB0z170mOxYiEeGyASQRz+dTppd1Pho7W4kDdDHG5U/kKgiHXA7fX1r2vR0CaVpKj/AJ8rZj9WjVif1rycRjJUp8qRnLQ8q02wntJmMltLEDE6hpY2XJLKcZI9q52e32AMMgdhz6V7P4o/48rf/r6T/wBFyV5HPgxoSeevHTOK5KOIlKpKT8jtqu+Fp+r/AEG2y+ZEAwwa7Lwf4esr83099E7RxCFYACyKWcNuOR6YHfvXMaUge6tY2AKyXEKYOCDuYCvb44oYUEcUaRovCrGoVR+AqqlZ3sjgZ4jqdiLa+vrdcgQ3M8a7uu1XOOtZ7weX+Neo+OrW1/s6C8EMYuVvIo2lCgO0ZSTKs3XHA715jNliOc1HtWIQQkgY612GkeF4LvQ7jUppplnCXTxRrgIREpI3Z55Iqj4XtYL3VbC2uI1eIrcPIrdDsiYjP44r1iK3t4YVgiijSFVKiNVAQA9RihV2B4U9u3Jz069+Rx2qqUIYg13XjWwsbK4sWtIli8+KQyJHwuVbg4riGAL1qqrauBpvEzaNZL/dndj9N0v+NZ4tXOTj6dDXaeGNMstVWG3u1dokinm2oxUlll2DJH1NdQ3g3w6Qdsdwh7FZeR/30prKhPR+rO7HfFD/AAr8jyP7M4Vj6ZqAKSdvXnArotes4rC/1GzhZzFC6hS5BYhkV+uPf0rDjX96CTwDn1rZzRwB9lmH8J/Dn+VJ5Ev9013egeGotYsmu5bmSIGV4kWNAc7cfMST71oy+A7bY/k38vmYO0SRqVLe5BzimpgeYNE4zmp7YEZI7A1bu4tnmoSN0buhPrtOKq2/O9emBn61lKdx2Pa9EXbpGjDrmxtX5/20D/1qbUwTpuqgdTY3YH18pqbpIxpejgf9A+z/AC8ladqh26bqp9LG7P8A5Cas0yTxG4HLYPUn61WaOQ421am5XI9vzqS0ied4YIxvlnkWONeOWY7QK7IYnkViyOzsNSn3Nb2lzOqHDmGJnCn3IFE0UsZdWjZHU4ZWBBBHqDXr3h3Sp9I04W05QzPNJPJ5ZLKN2AFBIHpXHeLNNuoL64u3QGC5YtE6DjJ/hYnvWscZrawXOJR3ztYY7ZOfzq5KiqqbTkMoPFROADyOfzq5aWtxfSRW1rE8szA7UTBOBzkk9qp4hbDKseSrdTgc+3btQDtzkdf0r1Ww0N7fw6bCWCE3rW9wW4Rv3rlmUb8dRkd685v9PubKWSK6heOTGQrgjI6ZX2pquuormWTnJAJ/M03GfqKniJVsHGCfqfWta5h/tS5J0+ylZUhjVlgjJJK5+ZgoraOIiO5hj7uTTeDzz+VbD6Zcqu1rO6Vl6hoZAc9OciqRtxnAXpwRyCD6HNa+3iFzLXGcg8Up5NA6cUhGKskO9BGTzSdKUk/jSsMdjikHFIuaTqTSsA8Kp60gxk4pACOtFOwDsZoIGBnr7UmGPPQelKQcUwAUpOQaQNx70jMcdKBMBkH2p2Oabzj/ACaUUwF20DH4+lDHimoACSeaAHZPenLknNISSfalGeBT6DRp6TAtxf2UTAeW0gD5zjA5+tbXiC6vNVl1OG0lFtbadHs8sNgyMmc8jGM9ua520ma3mimX7yNuHX6dq07qwa+kkvbSVR9oVTLEzFcMoA/h9cUlubIo6TcXs11HZ3ZaRJ1cK0mCVKqW6025gWC4mjU5CSMnpnBxWhBZCwKXd1OpmTIiVclVJGD168e1Zs0peSRyclmZifqc0myhYQfnOK9tsRizsRjGLW3GPTEa8V4tayKpfcgcMNoz2JPWvbLZStvbKeqwxL+SAV83i3+9MZbmN4o/48rf/r6T/wBFyV5FNtMaHvgfQ5r13xR/x5W//X0n/ouSvIpei+mBiuaD95nZU/3Wn6v9DT0BFbUdIXu+o2Y7D/loDXtIrxjw4hbWNEA7X1u3H+y26vZxWl9TgZy3jjB0i3B6HUIB/wCQ5a8rmAEh2DHT0r1Hx4R/ZVmO/wDaEZ/ARS15ZMCzgA85Hv7015gdd4JjJ1qIn+G1uGH1IC/1r1KvMvA246w+R92xmY/99oK9MpLVgef+PioudLJ6/Z5h+BeuBYDf+PFd548Ia+0+M/w2bP8A99SMP6VwR3NJt9D29qtSshnoXgf/AFi/9etx+k6135rgfBH+tX/r1uP/AEetd6aVF6P1OvHfHH/DH8jybxeVGu6mB3Nvn6+Shrm4gnmAuTjI6V0fisq2t6qQP4owfqsarn9K5yEDeAehPXvWjkcR674PCjQrQgYDSXJ/KQr/AEroKw/CSgaBpeO4uT/5MSVuEgAk9ACT+FUmI8Q1DLTXZUcefMfoC54qlEMsTjsfQZ/OrF4SzzvnhpZGGOnLE1Xg3EMew/H2rNvUo9z08YsNOHpaWo/8hrUOtNt0nVz/ANOVyPzQirVunlwW8Y6JDEg+iqBVLXm26Pq5Pe0lX/vobf61SJPGbg4OPwrS8NLnWtG/6/Ijz045rMuANx+v5YGK1vDKg61ooIyPtaN9CAWrMs9jrmPGpA0mE9/tsX5+XJXUCuU8cH/iU24B5N7H/wCi5K1voSeXyZDNkcZrrPASl9ZuGxxHp8p+hMsa/wCNcnKSpAPOa7HwB/yE7/8A68Pf/nslQpDPSq8+8d/8fdlyP+PXp3/1j816DXn3jrH22yz/AM+mSPbzHrTm0JRw+PmGDjFeieAYsW2rS45a4hQN3wqE4/WvOxjdgHNel+A1YaZfMf4r9x0x0ijpJjZ12K8m8SwpDrWpLEFVDIHwCBguoY8D3r1mvKvEys2t6kR08xR+SgVq5CRxgpp7ClGelLxnNe6WN2+v4UhH40pyaUdKAEGc8inFcUbgRwBSnJGe9AxoGeKQjHSlU80EZpgIOcAU5umKQDBo5HvTEMXOfank+lHANGMZNIQAd80cj60mcUZzyKBi7ic5GKcoA5NNwaUdDmmwsPBJxXaaP4H/ALTsLa+k1AwCdd6JHEH4zjklhzXFJImdpPTnufavWZZ57DwWk9qTHLFYQPGw4I3uuT+RNZVG0lYDI/4V06gkaqrHnAa2I/UOf5VLH4EukUEaogfHIEDFf++twP6Vx3/CReJI8hNVvMEk4aQvyf8AezS/8JN4rAVRqtxtxjHy8fjjP60uWfcLnYS+ArmWPP8AaoMvo0J2enXdmuK1TTrjSb6exnZHki2HemdrK67gRmrcfi7xdETjUWYHH+sjjccfUVm3l7e6jcy3d5J5k8pBYgAKABgAAUrST1Y7sltio56nI4+hzXuUf3EP+wv8q8MtR86L/edB+ZxXuorwMV/FEzA8U/8AHlb/APX0n/ouSvIpiAqY7gV694p/48rf/r6T/wBFyV5BJyqgn09K5o/Gztqf7rT9Zfob3hZN+r6NtI3C53HPHCqzGvX68i8JRn+2tIB6+dK34LGzV66K0W5wnHePGP2DTk/vXbH8oz/jXmk2N4I/ya9I8fNi30hR95ridgPUBFH9a80mBDkd+PzPNUwO28AjOpXbHqunsPxMsdek15x4AXdf37k8pZKABxndIP8ACvR6UQPOfHbkapZe2nofrmWSuHJzKzdiTXbeOyH1W2X+5YRj85JGrih/rMe9JvUDv/A5zIv/AF7XP/pQtd+a4HwP/rF/69rn/wBKBXfUqWzO3HfHH/DH8jx/xO2da1jH/Pcrj3AArBgJEgJHQ8VueIudY1nJx/pk4/JiKxoMbvx9v6VqcR6/4Tz/AMI/pOe63B/OeQ1tv9x/91v5Vk+GVC6FpABz+4Lfizs1ak3EUx64jc/oapEnhswBDdeCc/n7022ChZCP4sDHXvT7yGeHeHUqCx+mdx6VDZ5VtpOQ5QfT5qhlHvCDCoM5IVRn8Ky/Ef8AyBdW558gf+hrWqKyPEpI0PVSBk+Ug/OVBTT0EeO3OS/tx09a3PCmG1zRxt/5bSN64xE7ZrFnGGrf8IoTr2lH+79pY/T7O4pDPWq5PxuSNPssf8/ePzjaur7VyHjlttnpyk4BuJG45OQmB/Oq6CR5rLjzOTnHrxXaeA1xqN+w6fYAD9TKhFcVLlnz3zyeK7r4fp+/1ZzniC2X82Y/0qBnoPavO/HJP2+27gWScemZHr0SvN/G5xqSj/pzhPf+89adCUcYAQ/Hr9a9R8Ckto8xOeNQuBz/ALkfSvL0bDn3r1bwWANDhI/juLlv/HsUIbOkryjxAWOsaoQ3W4cY9Np2/wBK9XryXXGH9savx/y+T4/BiKtiRx27nijJzimgEHPalr6KxoLk9P8ACjPvTT60DPP+TSAkGQM0mSegpofGc/8A6qYXOfagRIT3pQxNRFgMc0qOOaYyTnGf/r0BieKUEUhI7DnvQAhBp2eOuB/WkyfTj9aXjv0/OiwhASaXijPPtR0waBoTODikO73NO27iK2tC0n+07swl9kcaea78dNwXH602XYxliz2OT+tetawW/wCEImIVgf7KszgjJH+rzkVwGoalZWTyQ2dlvgQ+WJXDBWYHscf1r0C01jTtZ8MahKcL5enzwXUbclGEJXIz2PUf/WrCqnoyeU8gDnP0/GpdwxUOCDkjg9PpTxjt/WtSeUkyTx2p6ncPeosnIFSoKiW4WL1gu+4tlx0nh45ORvAxXuYPWvENMbF7p+3r9qhH5tXtwHX6n+ea+cxX8URg+KP+PK3/AOvpP/RcleQT/LsOc5HPT0r1/wAUf8eVv/19J/6Lkrx2Q5Cj6CuePxM7qn+7U/V/odN4O/5Duk55x9p/9J5BXrYryfwYAdc04ddqXTflCwr1gVqtzhZxHj/GzRQeMPdn9I684mI84Dtxya9E+IOB/Yh55N4PyEdecyfNIeeegq2gO98AKv2rVDxuFtEM+xkzXodef/D9P3urPjGIrZPTqzH+legVCWoHmHjY51th6WsH4cE965Bc+d+Jrr/GnOt3HoLa2B/75zXHxZWYkgYDDHfvSe4HoXgj/WjjH+jXP/pQtd8a4PwScz5Ixm3ueP8At4Wu8NFLZnbjvjj/AIY/keL6+znU9XwOt/eD/wAisayId276A59q1NZkJ1LV89767I7dZWNZkecue+01rY4T2vw8u3RNGz3s4m/76G7+tXrmQRW9zKRkRwyyEDuFUnFVNDBGjaKD1/s+0/LylNWL/BsdRBOB9kucn0BjaqWwjxjVLx7p34CoJCVAz0qtZjc8QAyfMjUAcEncOKS5CqzKDkbjj6A1PpePtmnr0zd24OO+XFZso9yrC8WM66DqO3OWNuvHoZkzW7WF4scJol76s0KDp1Lil0QjyKfO7n/9ddJ4Ojb+29LfPGLvP08hxXNTt8+D2/Gul8GFjrmnHsY7sfT9y1UM9WrjPHv/AB66Xz/y3m4/4ADXZ1xXjw5i0pf9u4b8QFqnsJHm7Z35r0L4f8/22e+LEfh++rz5878/yr0L4fD5dbPqbEfkJqhDO7rzTxswbVQuPu2sIPXnq39a9LrzHxoQdWud3GyG2VfcFM1oxI5AcSA1634M/wCQDZnGMy3J/wDIhryVCplGRn5hn6Zr17wjgaBp2BgbrrH0+0SUIGb9eQ67Ir6tqZAPy3U6nHr5jGvXjXjeoyE3+oMeS91O35uatko5ZiaQbvSkUtjmnEnoDxivoLmo47fxqFnPag5zVmCzWQNKzgLGpc59qVwIEjLDJOBnvUTsAzAcgdDTsyXB2oMKD1zjite00O4lTfgBM43MDk8dge1S5DSMBnwTSo+a3rjRigYHacHrj9ayLi2aE5XOAeaSY7D0cHA6U8/WqgY8FckjnFWOoyKu5LJMjGPypMjvUYcdKYxIzk07gT8UuRjGaqB8Dk0byDwc0rgXVyMY/Gug0O5ERuI1+VpojGGzg4PUAiuVSVucflVuG6KHIJDY4wcflSbNEW57i6SB9NurYjy5Q6vhjkZzkYGOa19FlltLDWEaMiG8jWLDZGRtIOPzqGPV/NVRIkbMoGCQc5qteajLKMbsD0GMU7jM6Xy8kDBK8cc8ioSCAOaGcEmmFiev4UIholU46mpVbriqe8g1YicHNZyZBr6KN+q6QPXULRSPUGQV7fXiWhMianpDnjbqNqc88ASLXtorwcQr1LiZgeKP+PK3/wCvtP8A0XJXjsygbcHsK9i8Un/Q7UetyD+Ub14zKw3KfQfnWEFab+R3VP8AdafrL9DrvA6sdbtSei29yfrmMivV68q8CShtXiXH3rW42/gK9Wq7e8cJwHxCYFtFXPKi6Yj2bYM/pXnv35B27/lzXefEAZvdNGelqxx/20avPzxLj/a/rWlmB6b4DCH+2SvpYj8T5tdxXCfD0jZrY777L8sS13dTFCPKvGTA67qC/wB2K1X0/wCWSmuSj5mTP9/jvnmul8Xt/wAVDqhz/DbD8oVrm4n2yDI4zScSj0XwWcz5xjNtccen79a7yuB8EHdIp9bW4/8AR6133SppLR+p2Y744/4Y/keJathr3UyOrXly35yMazoScyZ7KRj61b1F8z3ZB/5eJiT6guTVW3IO/A5IOa25XY4T3DSAF0rRwOg0+zH4eStGrHZpert3FhdkfXymxUmnp5dhp0f9y0tk/wC+YlFQa0HbStVVBl3tJkUccllx3oUdBHit0OScnBOfz5q5owU3+lKT96+tVPbgyCq19BNBIY5lIb0PceoqzoZB1XRRjrqNkPTgyqKyaGe3Cub8ZsF0SUEZMlxCi9sHDHP6V0lcx42YLpEOec30I9cny5KLaAeUShi59eldb4KCnWLQD70cN056f3Cv9a5OQ8k+/vXW+BMHWc9CLGc4/wCBIP8APFMZ6hXCePW+bSF7bLs/rGK7yvPvHzkXGmr28iQ/iz4/pViRwpK7xnsa9B+H5ymuEdN1l/KWvPMBmJxXo3w/UC21dh/FPAv4qrH+tQkNnbV5b4yy2tX2eix2wH/fpTXqVeUeL2J13UgeB+4A/CFBVtCOagUCTk55GM17B4SGPD+lfS5P53Ehrx6PJl9ga9h8I8eHtK+lz/6UyUIGb1eMaiGF9egHpPL6f3zXsxrxW6LtcTsW5aSRj7kueapiRzRb0FNO78/5UoY/h2pcg19AWKoz9auDcIWX1BB+hqop54HNW84jHrWbGi3o1kJp0BA2KylyQDjPSt7Xbm4aU2GmukQtoFaU/dJZx0B69MVz+lX5tp3jJO2bbgcDlee9aWpae99L9ss5VMkkaCdSSnKqFBzUs1iZGmXl6blIZ5JJYrhjCwdi21ucFc1NqEIXdGedp/SrNrpzWri4unjBiy0aI4JLYx2qreyiQzOOd2SM9aEwMyC1MjSBcHClsZxxUfzDdgcHsPerOnXUcMk5lBAMLKpwc5J9Kr5UH1HrV3IkOjgyNxP4cUqWryFskY/Wp4gCvB/lWro2l3Wq3YtbYJv2PIzSEhVUdyR/hUTnyx5mQYbWXPXgfhSfYjk4Yfzr2Wz8H+H4YIVubUTTqo8yQyygM3fAUgY/CrDeFPC7DB02Ie4eQf1ryXmtPsM8R+yMpwSM9aVbORmyuf0r2j/hDfC3OLLGfSVz/Ooz4K8NnpHcKf8AYlH9Vqf7Uh2K5jz/AEHwxqOsR3EsE0UQgkEbCbd8xIz/AAg/yrN1bTprO8uLKYr5tu21mXO1sjcCM+or2rTtMsdLhaC0RlRm3uXbczNjGSay9U8JaPqt1JeStPHPIF3mJl2sVUKCQR/WiOZe9rsPnPGDZz9VI+hyKBa3HPPT616s3gDSW/5fbz2/1eB+QH86QeANP5/0+59v3afrk1ssygJyueTG3n3MMHj8M01I5lcnBGM884r1WT4fQn/V6pID/wBNLdT/AOgsK5fxD4fk0KWCNphNFcIzRyYCElT8wK//AF6f1yM3ZMhmDDdeQAdxDq24MOCDnIxXoGgePLT7JJFrEkn2iM/uXSMuZkx0YoMZrzWVVyT2pIZQpIJ4/Ch01J3YjuH8Q32t38yyti2jWZ7aPaBtUuoBOOc4965eTSNWZgRbccf8tYf/AIqomMseHillQsMboXZGwecEqc4pj3F8Fz9tvf8AwIl/xrCWHmpOUGvmehCtQlRjTqp6X2a6+qZvaX/bek3Fvd29qhliDqFZ4tpDLtIOGrqB4y8S4wdFts+ouFx+W6vMTdalji/vf/AiX/GgXWp97++/8CJf8aFRq+X4/wCYXwXaX3r/ACOv1m51zW7kXM9qkRSJYY0jkjKhQWbOS3vWKuk6kH3GDjP/AD0i6f8AfVZ0V3fFsNe3vH/TxJ0/OrH2q5PS9vP+/wDJ/jV+xreX4/5hfBdp/ev8jr/D+o6hoUl2f7PM8VysW8LNEjqY92MEnHeumHjA7cnSbjd/d8+3/nmvKTNfcYvbzH/XeQ/1p3nXvX7bef8Af+T/ABprDV/L8f8AML4LtL71/kberLqmp391fG12Gd8hPNiO1QAAM7qoppuobgWt8D/rpEf5NVLzr0f8vt5j/rvJ/jR594el5ef9/wCT/Gj6rX7r8f8AML4LtL71/kdroGo2mgCOW/EioY5YAIwrnc8nmDocYwDW/P468NhGWNrp5GUhR5JUAlcjJY/0rylpbpsCS4nkXIOJZWcA+oDGmkscc/0rSlg3FWluY4qrCrNOCaSSWvkT3DsxY5yWZmPbljntTLcP8/OOMfXNMw2OTmlDEcA4/StXhuhzWPYLDxR4ca0shJfRxyiCJHR1cFWVQDnAx+tM1nxBo7aXqItb6F7gwkRKu45fIPHGK8gZWJ+tOCsv3fvVKw1kHKWr26nuHDTOWYAYzg4q94fGdV0MYwf7RtW59pFNZADHJbr+dXrK5NnNa3KDL288c6jOMlGDCsZ0HbQD3OuU8ckHSrWPOGe+jIPssclUF+Illxv02cHHO2YHn2+UfzrE8ReKY9ajtoordoY4HaTMjhmdiNvQDHrWSpytsSco/wAz5Hqf5+9df4FKrrR3uo32UyqCcZbchwOeuAa49sA8VItzNE0ckR2vGwZTzwRTVGT6FHvtea+PZ1bUreFSCYrSPfg5wxeQ4/lSxfEC/a1MMlkouTEYxcK+RvxjeUxXITzSzyySyszySMWZmJJJPvWnsJCsRoTnP6V6N8P2X7Nq8eeVuIJD9HRh/SvNSzK3TvVu01PU7FneyupbdpABJ5ZA3AdM0fV5BY91ryDxQ5k1rVTnpOU/75+X+lVx4s8V42/2lLx32R5P44rMuLqa5kd5nLySMXdmySzMck1X1eQJDYMLJ+v9a9f8JHPh/Sj6i6/9KZK8ejOxiTzkGt7TPFGs6Zbra20kRgUsyRyxhghYliAeuMn1pexlcD1922qx9AT+QrxC5lBmk2cruYLng43Gtubxr4iniliJtUEqMhaOMhgGGOCTXNliSTnOSaTpSCxjbiBSbyDTC+eBSbvUV7ZRaQ5qyCNuDVJXxjFTo5bvUNDQksZPIyD2IJGKmhv7mBkYltyjCkE8j0IpCwPHemFcnmosVzElxqk0rchj2+cgj9KbHOJMgnk9uePzpojQ56VHJGQdydRz6cUg5hJlZWDgVFu3c1cjZJFKtjP9PxqlLDLGzMAcA8HrxSZLdyddyR+Yc/hz3xW94Z1s6Tem78rzQYWjkQsQWUnPB6fpXPeevkFCDvx7cnimQTPHu9wR3+tc8/eTiyT6Fs9Qsr63t7mGaMrMoYDeu5W7qR1yPpVrcvqPzFfPEc77twZh/ukj+VTNfXy523NwE7KJHA/Q14csC09GM+gsg0ua+fV1fVBgLd3II7+YamGu64nK6jeYI5Blc8e2TUfU5rqB75RxXg48S+IwQy6tfA9Mee+38s4/Sph4t8Vjganc8f7QP/oVH1SYWPcqK8RTxl4pX72ozHH94Kc/kKcvjbxUOTqDEc/wRnHHuP60/qkwPbK87+I27zdFwekdyCPqyc/pXNr468U8D7av+80UR/mtZuo67f6nIsl9N5sirtQ4AAHXoOK3pYeUJXZLM2YkEg1AADzTnkDMT1zQMEV6cUTcsQ3Cr8jn5T0PpViWNiAVwVPORg+tZLAHr0q7Zz4AiZvl6LxWyRaHrEWIUKWYnhVGST9BVtdOvCu77PKPqhFdRolrYWlhc6rONz5aK3QgZLD+7n1rHv8AXNYgm8p4I4yxDqPvExkkYppGnKYU8E0Lcqw9cgj+dQhivINdNdFL2yhuQmA7MpXrtZcg81zzxgNj3xWqQrDo5Gx1/On72zUQG04p6k1qokMlyCKb0oPt3/GkYdMGr5QAbjT8YGetR54yacp460coAznHHbrSgHr1oyPT+VXLW3a4kihXG6R1Uf8AAjRylorAv0x/T370ZKnkfzrqb2DSNFSKC4kWWZwX2qgJz05wf61m3FpbToz2wO4gyBOBhTz/AJ5ocSrGSGBq9YabqepypDZQs5Ztpc5EacZyzYxVvQPDl9rF0hKMtjHIFuZuAAByVXPU16hp0Wj6UYtKtGAkcSTbchnIHUuR+lc82ombR45c2tzZ3Fxa3K7Z4XKSLyeR3HtUO010HjJVHiPUgOAUtScdyYVJrHji8zAUEnI4HU54oUU1cSIduR/Wm7ecZrqDodrY20Vzf3EaM/WGTaSCR25z+lZtzaWMyO9lLGzKOUUg8/h/hWygrGtkZgwBjPSjcPyqIhlJzTt2eKpQRLQ5mU9smjimYJ5P4UnOTyaHEkd0PrS7fmzj0puCTuoJbOOv6UcgDupOaM4Oe2aXBxk9aaff1pcgEmc03bSLx3/rTxt9T+lLkEYYIAxjmg5pCVFMMg7UuZASqetP3sOnFQB/SnAqep5ovcCzG5GSTyfWphIpH+TVMEgjFPLEUWAshxnrUoAeqGeRU8cnIpOIDZFaN96elWI5FlXaeuORSjbID/8ArquqvHJkdM8/yrOSAe0CknipI7VGBGORUilXJG7nHsK3vD+hXWsTTJFJHGkIRpXkyeGJA2gfSuSpLlVwMNbTHCo5z/dVj09wKWS3UABgwJ9QR/Ovdbaxs7aCK3jhi8uNAgyinPHJPHelNjp5PNpbH6wx/wCFeXLGrsB4GbbP3Rk+nIp4tPlORz78V7qdK0hs5sLPnr+4jGfyFRNoehNktplkSe5hTP8AKo+uJ9Bnh32JRj5ufT/9VBtc8ZH8q9uPh7w6VKnTLXH+ym0/mpz+tMPhrwyRj+y7b8AwP55o+uRC54ibQ9ARn6imfY2HUj2HNe2t4V8MMADp0YH+y8g/rUX/AAh/hY5H2HGRjiWQ/wAzTWMgB4ubUjoc+1RyW8gGT+vFe0t4M8MEEC1cZ7rKQR+OK898VaTDo9+1pAztC8CXEW8gsAxZSCfwrqpYiNR2RLOObIJHp+FG844p75JNNVcnGK7UiRvJHHNSJkEHpjn8aUKQen/1qcRwa1Rojr7KSS/0kwIds0B3RgEfMV5HX1rNmj1a5lJmgmeUAID5ZAwPTtWNa3lzaSZjdlGeQpIzjmthvEVywAA2tjgrg8/iKs1T0LUrGytI7V9qnLMwzk5Y57VhyPuc49eO9SvdXFzkzOzk92x/hUBXnpVxJYh5+tOT3pD0x0NC5A5PP51siGS5HSkbpxSYz0pODxWghAQeDTlx61GeDS5pgS5y3Hb+tbOhyxQajZSyDcokwR15ZSoIzWKpA571ZhmaMhlOCpznjg9e9Sy0aV/cRC51pLq2WSWeSQ28j5JRWJIKkn/OKj0CH/iaWkkpJs1cC63E7TGw2kcVYt9St32faoVdsFfMwCcdMYNJLfW0cbR2cQjRieRweeDSY7neax4h0rRLSGHSxaPLISEjhKbIht++4Tv0rnfBDzXWuXc0j5ZLWWV8kksXcLxn61xzbclv4ieTXW/D/B1i9YnBFg6gdM5lQ/0rncVGLsZlXxlj/hItRIx/q7TPT/niorN0qVYb60kdSyJKjFRjnByBV3xawbxDq+MfetwfqsKLWLHI0bBgcEHI78jmtY/Cho3NUurC8udabUc+b5QWwQlyFIXaCoUgenWsPTVCX0Kh8I+5ZfptJrSaTT7+KMXB8udSP3mMk9uSKTGlW6sIAWl6MzZLY68E8VstjUz71UWeQx/cz8vTjFVRz9ammOWYn1JHfiowD/nmmiWOJ45pijB9c0tKq9SaDMcMigrn8aKaRzuz2xigB3K9abvJByO9G/IPFOCgjmgBV6HNJgUuMd6MrQBzp6Zzn3oHSp2iwPUVD0PFeWpkXEGQaXqetLxSHg1pGQJky5p54PqaIxuUk8YpMrnr3/8Ar1umUKOcZp/IppINIDitCizE4UfMcfrVgbWGQazixJ9qlSUiokgHvG6kuufr0ra0HV9S0qVpoJio+USIQCrrnoc1nwsH6gYPWoJ32MwQ/KeDjmuKtHnVmI9vg8U+GpokkOoQRllBZJCQykjocirC69oDKHGo2uw5AbfgZ/GvA95AwB7/ANe9P+0TFdn8GchcY/lXkywUe4Hvf9t6FhT/AGjaAMcLmVRk+2alGpaWQCL6056fv4/8a+ffNJGMfz4+lOWV1x1/X+tZ/UrdRn0Mt1aP924gb/dlQ/yNP8yM/wAaf99L/jXzu1xJwVZgR3U/4Upu7jB/ePzjOGI/lR9T8wsfRG9P7y/mKUEGvnZdQvVGFnmHoRI4/rThquqAEC8uRk84lf8AxpfU5dx2PogHNeU/EJw2sRqOsVjCrdD1ZmxXJf2xqpwPtt1n181sjtUMt1NcMXmkaRyOXYkk49a6aGHdOV27kMquctUsETyOiIpZ2OFUAkkmo8Ddmt3wxIv9q2ZZQRGZW5AIJ8tuOa9FAkTyaNpthFFLql0VkkGfLQ4C/kM1FNpulvF51hKXT+Ibt2Prn/CptRfSrptc+2pKt+JZhacuVAydoGOPzFUNIidbiRUJ2NE2/HI45FaGhQliCEqR/SkRF7Cr1+By+MY4z0qir7R61ogbJQCv09KR3xwOtN3luaYx5HfNaxRAhY/nTlyabUiDt261skA4Fh9KTkn3/OlJ5+lHHBqgGjOeadxkUbgTR0OaAHdKAcUmCw54o6DmkNEoY4pdz/561GO1PB4yaLDuLuzz+ddf8P0hfV7tj99LFyg9QXUGuRyoHt+Fdl8O2iGo6mCCXNmhQgZG0SDd/SsKnwszMbxMAuva1jnNyx9+VBrHBzkH8PrWv4ldX13V3GcG4YAkEA7eO9Y2V7Y61UdkUmO3kYAoLmmnke9JgkVqi7isTRnjpTG6UDP+eaoTY4cmnZ2nk8U0A44peO4zSIHEqetNPXOaCR0FKuCaBCqwHOKcSCQRSNjNNII6UDHEjpQabz1xQNxpjMYM445I96cVVgSvX+tLxikXgmvEMyAg5o61JJ144H51GAc9a2gNFlFO3rwaQgZ4xSx/cIHWhFJYLjLE4x6mupFpDeR9Pzp5Tpk9anBFvlmGWwcLx+tV8TzsSAcE5+ma0T0NLCiPIPNOEZONvI70htrhF+YEE9jwcU1JHjPPTPINQ5CaNBlMVtv/AL3H4U22iSUDvkgAYznNR3N9DJBFDEp3AhnY8DGDwP8A9VafhpA97pqnjdfwDn0LVy1XyxciCyPD2s/eXSrwrjO5YmPH+famDQ9TyVGnXhLZGPIkJHbjAr3H/wCvS14csc29gPDZNB1K3CyS2N1hug8qQkfhiom0y6xu+yXAX/rk5/mK92IzQFHpU/XH2GeCf2e46wTjuQY2/wAKhazLEr5cn02MD/KvoEqD1AP1ANNMcR6oh+qqf5in9cfYLngH2GLaciQHtwetMFioB5J9MK3Br382tmetvAT6mKM/0pn2DTicmztSfUwxk/yqlju6C54D9kAyTx9cik8jaCeor3p9I0WTPmadZN9YI8/niuG17wRdCS9u9MkgW2VJJ/IkLK67VLFUOMY9Oa6aWLjN8ojzlo89P/r0+1uJLKdJlHK565GMjGRUi4zz/jzQ8asOnFeol3KRvO2j6r/pDO6S7V37eCccZIxio/PsLRJI7Xn5cM7HqT9f8KwQHQjaSB7Ej+VMcyscE5BrVJFE88rTfKeVzn8aj8tNnJwR365pY12jn/GmzOvQfQ1okiWRrnkZoOf/AK/HFIpHalyO9axRIbqeD71GcdaeMEYrWwD8dx+dN3HJ9sU7pgDp1+lRlhuosBJlcj1qQYNVxgH3qXHTPX2pMCQ8DIpm71oPP0pDg8UgHA1taFcaNbXiyapH5kGAFGCwB9wOaxlXilBwelJoR6y+s/Dt4o1c2BRcFVaycbc/WOrkGs+CLTD21xp8JYbcwx7CR1x8q14/njGOMUzC56Vzuiu7A9bmk+H17cNNO+nPK5LM0hZQzHuegzWRrtr4Bjs7l7V7RLry/wB0LV97Fu3yZIrz07SuCARSAdlA/l7U1Tt1YDsgdf8A61MZyKPmzRjca2QwA3ZP6UDOGzT8ClABBzVDGjpSDqaXpxSY596BMcAe1Ayp6UoyMnNPAGCfbpQSREEnvT+MUnVsU7HOKBjDk8jpTlIx1pSQOMYpAVFMZktG4PA4pgV89K0SBiocDmvBiQVH6cjpVcn0q44G1vpVWuiAIsQdK1LBE3u+wOVUnHBNZURPAzWxpvC3DDqMDPt1rqNImaFkubrYi5aSQhVJ4yT0zXWSWemeHtPjuL5hJdS4YRqATkdlzXO6b/x/2×7/AGmP/wBCq341JbULHJJ/0KPqeOZW7UrmpYtdZ0rUpvKe3McjHEfmhSGPPpVbVdOSLMqDClvmHoSKxNP4vbL/AK7x/wA66zWv+PSb6Kf/AB6s2xM5A4B/Gt3RbuO1mtp2wRBcRSkcDhD0rCPU05CRnk96wkrqxmz2X/hYnh4Ha0N4T3MaIyj8SRUyeP8Awqw+aS6Q+jwjP5hsV4xGzbsZOKXJ8wfSuB4OmI9rHjnwuSAZ5hkZy0LAfnUo8a+FCcfbG/78yH+QrxHc27qe9PyQBj1rJ4SPRjPch4r8LkA/2jEARn5lkB/HIp48T+GWGRqdv+JP+FeFbm9TT1Zti89TUPBruB7uuvaC0YlGoW3lliquXwpI6jJGKX+3vD3H/E0suTjmZRz+JrwVri4MflmRtm8Hb2zj0pqM3TPFT9R8wPoEavorDI1CzOfSZCfyzXGeIfHT20l7ZWNpDOhjeHz3kYAF1I3AAYIrzQk/NSBmKkE11UMGoy5m7iIhI4bJ5NTpKTwRVbuKtxquxjjkAV7sFc0SuOU7u1DFVBJH49a1LGGBozuRTksDnnjPvVbUIYY9wRAowxwM4z+NbqCL5UZjy4HHf8KjBznNMbrQKfKjOSHZGadnPGaZ/wDXpR0H0FUQO56Z6Uqk5popy9TVoZLnOB601gB7mkFI1IQuTwD3qRTwM1EOgqQUgHk8UgGTxx9P/r0en1xThwVP1pAOB6j0pc+34009R7mlPGcUAOGfWkx70ooPQUgF5AA9aXJHuKjPX8RUygYoAacGlUEcCmr/ABfWl/ipAPA7mlLgCo8ndStTAcADzQQOtMWn0CEGcEdqUHGc0UnegA+lPU4YE0zuKKAHM3U0gyeRTDnFPBOBQB//2Q==” alt=”” class=”wp-image-136″ >

Best Practices for PCB and Stencil Registration

To ensure consistent and accurate registration between PCBs and stencils, consider the following best practices:

  1. Designing for manufacturability: When designing PCBs, follow guidelines for minimum feature sizes, clearances, and soldermask openings to ensure compatibility with the registration systems used in manufacturing.

  2. Placement of registration marks: Position fiducial marks and other registration features in a consistent and symmetric manner across the PCB and stencil. This helps to minimize the impact of any distortions or variations in the manufacturing process.

  3. Material selection: Choose materials for PCBs and stencils that are dimensionally stable and resistant to warping or deformation. This helps to maintain accurate registration throughout the manufacturing process.

  4. Process control: Implement strict process controls and regular calibration of assembly equipment to ensure consistent and accurate registration. This may include regular cleaning and maintenance of machine vision systems, as well as monitoring of environmental factors such as temperature and humidity.

  5. Quality assurance: Perform regular inspections and audits of assembLED PCBs to verify the accuracy of registration and identify any issues or defects. This can help to catch problems early in the manufacturing process and prevent costly rework or scrap.

Table: Comparison of 2D and 3D Machine Vision Systems

Feature 2D Machine Vision 3D Machine Vision
Image Capture Single camera Multiple cameras or specialized 3D imaging
Depth Information No Yes
Suitable Applications Flat PCBs and stencils PCBs with significant height variations or solder joint inspection
Complexity Lower Higher
Cost Lower Higher

Frequently Asked Questions (FAQ)

  1. What is the purpose of PCB registration?
  2. PCB registration ensures that the various layers of a PCB align precisely with each other, resulting in a functional and reliable end product. It is particularly important when using stencils for solder paste application, as misalignment can lead to poor solder joints and component placement issues.

  3. What are the different types of registration marks used in PCB manufacturing?

  4. The different types of registration marks include fiducial marks (global and local), PCB panel fiducial marks, and stencil fiducial marks. These marks serve as reference points for automated assembly equipment, allowing for precise alignment of the PCB and stencil during the manufacturing process.

  5. How do machine vision systems help in achieving accurate PCB registration?

  6. Machine vision systems use cameras and image processing algorithms to detect and align the registration marks on the PCB and stencil. They provide the necessary information to motion control systems, which adjust the position and orientation of the PCB or stencil to achieve accurate alignment.

  7. What is the difference between 2D and 3D machine vision systems in PCB assembly?

  8. 2D machine vision systems use a single camera to capture a two-dimensional image of the registration marks and are suitable for most PCB assembly applications where the PCB and stencil are relatively flat. 3D systems use multiple cameras or specialized 3D imaging techniques to capture depth information and are useful for aligning components with significant height variations or for inspecting solder joint quality after reflow.

  9. What are some best practices for ensuring accurate PCB and stencil registration?

  10. Best practices include designing for manufacturability, proper placement of registration marks, material selection, process control, and quality assurance. By following these guidelines, manufacturers can ensure consistent and accurate registration throughout the PCB assembly process.

Conclusion

PCB registration is a critical aspect of electronic device manufacturing, ensuring that the various layers of a PCB align precisely with each other and with the stencil used for solder paste application. By understanding the different types of registration marks, methods for achieving accurate alignment, and best practices for ensuring consistent results, manufacturers can produce high-quality, reliable PCBs that meet the demanding requirements of modern electronic devices.

As technology continues to advance, the importance of accurate PCB registration will only continue to grow. By staying up-to-date with the latest techniques and best practices, manufacturers can position themselves to meet the challenges of an ever-evolving industry and deliver products that exceed customer expectations.

CATEGORIES:

Uncategorized

Tags:

No responses yet

Leave a Reply

Your email address will not be published. Required fields are marked *

Latest Comments

No comments to show.