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<?xml version="1.0" encoding="utf-8" standalone="yes" ?>
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<title>Andreas Zwanenburg Portfolio</title>
<link>/</link>
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<description>Andreas Zwanenburg Portfolio</description>
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<title>Andreas Zwanenburg Portfolio</title>
<link>/</link>
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<item>
<title></title>
<link>/home-unused/slider/</link>
<pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate>
<guid>/home-unused/slider/</guid>
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<item>
<title>Academic</title>
<link>/home-unused/hero/</link>
<pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate>
<guid>/home-unused/hero/</guid>
<description><p><strong>The Best Way to Create the Website You Want from Markdown (or Jupyter/RStudio)</strong></p>
<p>Build <strong>Anything</strong> with Widgets</p>
<p><span style="text-shadow: none;"><a class="github-button" href="https://github.com/gcushen/hugo-academic" data-icon="octicon-star" data-size="large" data-show-count="true" aria-label="Star this on GitHub">Star</a><script async defer src="https://buttons.github.io/buttons.js"></script></span></p>
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<title>Academic Kickstart</title>
<link>/home-unused/demo/</link>
<pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate>
<guid>/home-unused/demo/</guid>
<description><p>Welcome to the <strong>Academic Kickstart</strong> template!</p>
<p>Follow our
<a href="https://sourcethemes.com/academic/docs/get-started/" target="_blank" rel="noopener">Getting Started</a> and
<a href="https://sourcethemes.com/academic/docs/widgets/" target="_blank" rel="noopener">Page Builder</a> guides to easily personalize the template and then
<a href="https://sourcethemes.com/academic/docs/managing-content/" target="_blank" rel="noopener">add your own content</a>.</p>
<p>For inspiration, check out
<a href="https://sourcethemes.com/academic/docs/install/#demo-content" target="_blank" rel="noopener">the Markdown files</a> which power the
<a href="https://academic-demo.netlify.com/" target="_blank" rel="noopener">personal demo</a>. The easiest way to publish your new site to the internet is with
<a href="https://sourcethemes.com/academic/docs/deployment/" target="_blank" rel="noopener">Netlify</a>.</p>
<ul>
<li>
<a href="https://sourcethemes.com/academic/docs/" target="_blank" rel="noopener">View the documentation</a></li>
<li>
<a href="http://discuss.gohugo.io/" target="_blank" rel="noopener">Ask a question</a></li>
<li>
<a href="https://github.com/gcushen/hugo-academic/issues" target="_blank" rel="noopener">Request a feature or report a bug</a></li>
<li>Updating? View the
<a href="https://sourcethemes.com/academic/docs/update/" target="_blank" rel="noopener">Update Guide</a> and
<a href="https://sourcethemes.com/academic/updates/" target="_blank" rel="noopener">Release Notes</a></li>
<li>Support development of Academic:
<ul>
<li>
<a href="https://paypal.me/cushen" target="_blank" rel="noopener">Donate a coffee</a></li>
<li>
<a href="https://www.patreon.com/cushen" target="_blank" rel="noopener">Become a backer on Patreon</a></li>
<li>
<a href="https://www.redbubble.com/people/neutreno/works/34387919-academic" target="_blank" rel="noopener">Decorate your laptop or journal with an Academic sticker</a></li>
<li>
<a href="https://academic.threadless.com/" target="_blank" rel="noopener">Wear the T-shirt</a></li>
</ul>
</li>
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<div class="alert alert-note">
<div>
<p>This homepage section is an example of adding <a href="https://sourcethemes.com/academic/docs/writing-markdown-latex/">elements</a> to the <a href="https://sourcethemes.com/academic/docs/widgets/"><em>Blank</em> widget</a>.</p>
<p>Backgrounds can be applied to any section. Here, the <em>background</em> option is set give a <em>color gradient</em>.</p>
<p><strong>To remove this section, delete <code>content/home/demo.md</code>.</strong></p>
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<title>Experience</title>
<link>/home-unused/experience/</link>
<pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate>
<guid>/home-unused/experience/</guid>
<description></description>
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<title>Accomplish&shy;ments</title>
<link>/home-unused/accomplishments/</link>
<pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate>
<guid>/home-unused/accomplishments/</guid>
<description></description>
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<item>
<title>Recent Posts</title>
<link>/home-unused/posts/</link>
<pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate>
<guid>/home-unused/posts/</guid>
<description></description>
</item>
<item>
<title>Meet the Team</title>
<link>/home-unused/people/</link>
<pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate>
<guid>/home-unused/people/</guid>
<description></description>
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<title>Recent & Upcoming Talks</title>
<link>/home-unused/talks/</link>
<pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate>
<guid>/home-unused/talks/</guid>
<description></description>
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<item>
<title>Featured Publications</title>
<link>/home-unused/featured/</link>
<pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate>
<guid>/home-unused/featured/</guid>
<description></description>
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<title>Recent Publications</title>
<link>/home-unused/publications/</link>
<pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate>
<guid>/home-unused/publications/</guid>
<description><div class="alert alert-note">
<div>
Quickly discover relevant content by <a href="/publication/">filtering publications</a>.
</div>
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<title>Popular Topics</title>
<link>/home-unused/tags/</link>
<pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate>
<guid>/home-unused/tags/</guid>
<description></description>
</item>
<item>
<title>Drone piloting</title>
<link>/project/drone-piloting/</link>
<pubDate>Tue, 30 Jan 2024 00:00:00 +0000</pubDate>
<guid>/project/drone-piloting/</guid>
<description><p>In the past years, I&rsquo;ve regularly piloted drones. Since 2022, I own a DJI Mini 2 drone which I fly for hobby photography/videography outdoors and occasionally from a boat at sea. Sometimes I assist friends or family with drone inspections, such as roof assessments, and orthomosaic mapping.</p>
<p>During my Masters, I piloted prototype drones daily for test flights and calibrations. These drones were designed for autonomous flight, and I served as a safety pilot to intervene if needed. Working on the drones, and these piloting experiences deepened my understanding of drone components and sensors and their behaviour.</p>
<p>On special occasions, I piloted other drones, like a DJI Mavic 3 during the Xprize Rainforest Competition in 2023, flying BVLOS in the jungle for close-up images of the vegetation. As of January 2024, my logged flights are:</p>
<ul>
<li>DJI Mini 2: 188 flights, 18h</li>
<li>Parrot bebop 2: 90+ flights, 40+h (autonomous drone prototype)</li>
<li>DJI Mavic 3 pro: 8 flights, 4h (BVLOS)</li>
<li>DJI Tello: 30+ flights, 5+h (autonomous drone prototype)</li>
<li>Eachine Trashcan: 40+ flights, 8+h (FPV practice)</li>
<li>Flyablitiy Helios 2: 1 flight, 10min (tryout/pilot-training)</li>
</ul>
</description>
</item>
<item>
<title>Downscaling autonomous drone navigation</title>
<link>/project/downscaling-autonomous-drone-navigation/</link>
<pubDate>Mon, 22 Jan 2024 00:00:00 +0000</pubDate>
<guid>/project/downscaling-autonomous-drone-navigation/</guid>
<description><p>For the second part of my Thesis project in my Masters, I have researched how autonomous navigation for drones in forest conditions downscales. In this downscaling, the CPU and memory load of the processor, the sensor quality, and flight peformance are considered. With these results, I created a 100-gram drone with full onboard navigation capabilities to fly autonomous in forest conditions.</p>
<p>In order to compare performance in the rainforest with for example processor load, the performance has to be quantified somehow. To make this performance measurable, I created four metrics with formulas. These four metrics are:</p>
<ul>
<li>the miminum findable gap size the drone can find to traverse through</li>
<li>the minimum obstacle size the drone can detect</li>
<li>the maximum obstruction width the local planner can plan around</li>
<li>the reaction time of the perception to map obstacles and detect collisions</li>
</ul>
<p>To benchmark how the performance and processor load change with different configurations for the planning algorithm, I chose to run simulations where the board replays actual logged flight data. The perception and planning algorithm then processes this real forest flight data according to the specifically given setting. This setting then varies to compare different setups.</p>
<p>For the benchmarking, a dataset is created with the 500-gram autonmous drone built for the
<a href="../xprize-rainforest-competition">Xprize Rainforest Competition</a>. The 500-gram drone flew over a trail in a dutch forest fully autonomous, and all data is recorded. From the recorded data, the Drone&rsquo;s localisation data and the depth image are extracted. This extraced data is then injected in ROS where the perception and path planning are running with a specific configuration. In this simulation, loop durations for sup-processes, CPU load, and memory load are measured. To steamline the benchmarking, the simulation process is automated such that a set of pre-defined configurations is simulated back-to-back to run over 100 simulations of a couple hours. In this automated benchmarking, the system performance is logged in ROSbag files and transfered to pickle files.</p>
<p>These pickle files contain data that is directly imported in Python. In a Python script, the data is processed and visualised. In the visualisations, the loop durations or load is plotted in time graphs and statitically shown in boxplots. These visualisations not only show the average value, but also the variation in the measurement. For every simulation, the four perfromance metrics are calculated by the measured data and configuration settings. The figure below shows an example of the measured CPU load when varying the resolution of the obstacle map (voxel-grid). In this example, a 0.05m voxelgrid reffers to a mapping where obstacles are mapped in cubes of 5x5x5cm. The smaller the cubes, the more accurate obstacles are represented, and the smaller gaps can be found by the planner to plan a path through.
<img src="cpu_load_voxel_size.png" alt="Caption"></p>
<p>The benchmarking over 100 configurations of the planner on exactly the same scenario, the results show that configurations related to the perception (depth-image resultion/rate, voxel-grid resolution) have the biggest impact on reducing the CPU load and performance. In the research, tradeoffs are visualised how different configurations with different CPU loads and performance relate to eachother. These tradeoffs can then be used to choose what performance are required or most important, and which are less important for a certain task. With this knowlegde, a system can be configured to use a low CPU load where the performances are known upfront.</p>
<p>With these results, a Tello drone with full onboad autonomy is created, shown at the top of this page. This
<a href="https://store.dji.com/nl/product/tello?vid=38421" target="_blank" rel="noopener">Tello</a> drone can navigate through 1.0m gaps, has a 300ms reaction time, detects obstacles of 2cm and bigger, and plans around obstacles upto 3.6m width. Onboard the Tello drone, a new lightweight type of camera is used wich is quite novel in this field, the
<a href="https://www.arducam.com/time-of-flight-camera-raspberry-pi/" target="_blank" rel="noopener">Arducam TOF</a> depth camera. To process all autonomy, a
<a href="https://www.raspberrypi.com/products/raspberry-pi-zero-2-w/" target="_blank" rel="noopener">Raspberry Pi Zero 2w</a> is used. In total the system weighs 110 grams including battery, and can fly for 4 minutes. In publications, I have not found drones that compute onboard autonomous path planning on this small size and flight time.</p>
<p>The two images below show Rviz with the depth image from the TOF camera, the mapping of obstacles in the blocks, and the path planning in 3D around the obstacles</p>
<p><img src="tello_path_planning.png" alt="Caption">
<img src="tello_path_planning_2.png" alt="Caption"></p>
</description>
</item>
<item>
<title>Sailing</title>
<link>/project/sailing/</link>
<pubDate>Mon, 22 Jan 2024 00:00:00 +0000</pubDate>
<guid>/project/sailing/</guid>
<description><p>WRITE TEXT HERE</p>
<h2 id="navigation">Navigation</h2>
<p>WRITE TEXT HERE
<img src="routing.jpeg" alt="Caption"></p>
<h2 id="dufour-40">Dufour 40</h2>
<p>WRITE TEXT HERE
<img src="dolphin_drone.jpeg" alt="Caption">
<img src="dolphin_VUR_downwind.jpeg" alt="Caption"></p>
<h2 id="swann-45">Swann 45</h2>
<p>WRITE TEXT HERE
<img src="kforce_3boats.jpeg" alt="Caption"></p>
<h2 id="splash-and-optimist">Splash and Optimist</h2>
<p>WRITE TEXT HERE
<img src="splash_andreas.jpeg" alt="Caption">
<img src="splash_more_boats.jpeg" alt="Caption">
<img src="splash_breskens.jpg" alt="Caption"></p>
<h2 id="coaching">Coaching</h2>
<p>WRITE TEXT HERE
<img src="coaching.jpeg" alt="Caption"></p>
</description>
</item>
<item>
<title>Study Robotics</title>
<link>/project/study-robotics/</link>
<pubDate>Mon, 22 Jan 2024 00:00:00 +0000</pubDate>
<guid>/project/study-robotics/</guid>
<description><p>WRITE TEXT HERE</p>
</description>
</item>
<item>
<title>3D printing</title>
<link>/project/3d-printing/</link>
<pubDate>Fri, 10 Nov 2023 00:00:00 +0000</pubDate>
<guid>/project/3d-printing/</guid>
<description><p>Since the start of my HBO Mechatronics studies, my interest in 3D printing has grown, leading to significant learning experiences. Over the past 7 years, I&rsquo;ve delved into various aspects, such as optimizing material-print settings and mastering 3D design in Solidworks for lightweight, strong, and durable prints.</p>
<p>Throughout my HBO study projects, I designed numerous parts and small-scale machines in Solidworks, translating these designs into 3D-printed realities. During my first internship, I revived an old and mallfunctioning Ultimaker Original, one of the pioneers in consumer 3D printers, from 2011. Over time, I enhanced its capabilities by modifying electronics, creating a new hotend and adding a heated bed. The printer is shown in the image at the top of this page.</p>
<p>After five years, I decided to upgrade to the Creality Ender 3 S1 for a quieter and more precise printing experience. This printer automates many calibrations and fine-tuning processes, minimizing the need for manual adjustments and ensuring smoother prints, especially with its acceleration sensor for automatic tuning and reduced vibrations at high speeds.</p>
<p>Throughout my 3D printing journey, printing on avarage roughly two parts per week, I have actively engaged in designing, printing, and refining. This hands-on approach has provided valuable insights into material properties and additive manufacturing processes. I now have a comprehensive understanding of selecting materials based on factors like durability, sun exposure, chemical requirements, and brittleness. Additionally, for the part design, the layer-by-layer printing process has taught me to consider factors such as layer orientation for strength, the necessity of support structures, and the precision required for achieving strength, lightweightness, and speed.</p>
</description>
</item>
<item>
<title>ROS</title>
<link>/project/ros/</link>
<pubDate>Fri, 10 Nov 2023 00:00:00 +0000</pubDate>
<guid>/project/ros/</guid>
<description><p>WRITE TEXT HERE
&hellip;..
&hellip;..</p>
<ul>
<li>ROS for autonomous drone navigation in rainforest</li>
<li>ROS for mechatronics study rover</li>
<li>ROS in simulation for sensor fusion</li>
<li>ROSBAG for advanced replay with simulated overlay (comparing benchmarking results)</li>
<li>RVIZ for practical visualisation</li>
</ul>
</description>
</item>
<item>
<title>Autonomous drone navigation rainforest</title>
<link>/project/xprize-rainforest-competition/</link>
<pubDate>Mon, 08 May 2023 00:00:00 +0000</pubDate>
<guid>/project/xprize-rainforest-competition/</guid>
<description><p>For the beginning of my Thesis project, I created an autonomus 500-gram drone that could navigate in the rainforest. By only utilising onboard sensors and processor, the drone performed obstacle mapping and path-planning in complex and dense forest scenarios. This drone was for the
<a href="https://www.xprize.org/prizes/rainforest" target="_blank" rel="noopener">Xprize Rainforest competition</a> in which TUDelft collaborated with ETH Zurich and Aarhus University under the name
<a href="https://biodivx.org/" target="_blank" rel="noopener">ETH BiodiviX</a>.</p>
<p>In the competition, teams had to measure biodiversity of a specific rainforest area and create a report with the findings. Measuring biodiversity had to be done remotely, so only robots could enter the competition area. Whitin 24h, these robots had to collect the data. The BiodiviX team had 1 rover and 5 drones in total for the measurements. Thereafter, in the following 24h, the report had to be generated.
The semi-finals of this competition took place in June 2023 in the rainforest of Singapore. Our team was successfull with the data collection and report and advanced to the competition finals, which will be in Amazon rainforest in the summer of 2024. In the video below, you find an intresting aftermovie of what our team preformed in Singapore.</p>
<div style="position: relative; padding-bottom: 56.25%; height: 0; overflow: hidden;">
<iframe src="https://www.youtube.com/embed/0gJPW-Bgh6A" style="position: absolute; top: 0; left: 0; width: 100%; height: 100%; border:0;" allowfullscreen title="YouTube Video"></iframe>
</div>
<p>To create a drone that could navigate autonomously in the rainforest, I had to study what the best method would be, I had to design a drone system, build a drone system, program the drone, and testfly the drone. For the design of the drone, I took Parrot Bebop 2 drone for which I designed a module on top to create the autonomy. This module on top contained an Odroid XU4 processor board, a Realsense Depth camera, and additional flightsystems for the mission such as communication and GPS.</p>
<p>For the autonomous navigation I used the
<a href="https://github.com/ZJU-FAST-Lab/ego-planner" target="_blank" rel="noopener">EGO-planner</a> as basis. This algorithm has a perception process that maps the detected obstacles in the environment and a jerk-optimised path-planner to generate smooth paths towards the goal, shown in the image below. This path planner was in 2023 the state-of-the-art algorithm to run real-time on a small processor board which also robustly find paths in dense and complex environments.</p>
<p><img src="EGO-planner.jpeg" alt="Caption"></p>
<p>The planner was adapted to work in the ROS architecture of my system and adapted to communicate with the Bebop 2 drone via the Parrot SDK. Other sensor and software modules are added to the system to run the outdoor mission, such as a 4G module, RC receiver and a GPS module. The 4G module enabled remote supervision of the drone with telemetry, video streaming, adapting the mission, and control from the groundstation (the laptop). The GPS module enabled GPS waypoint missions with the EGO-planner.</p>
<p><img src="mechanical_system_components.jpg" alt="Caption"></p>
</description>
</item>
<item>
<title>Industrial robot cell</title>
<link>/project/industrial-robot-cell/</link>
<pubDate>Sat, 03 Jul 2021 00:00:00 +0000</pubDate>
<guid>/project/industrial-robot-cell/</guid>
<description><p>During my HBO Mechatronics graduation internship, I contributed to
<a href="https://www.vanweeswaalwijk.nl/" target="_blank" rel="noopener">Machinefabriek Van Wees Waalwijk</a>, a company specializing in industrial automations. In this internship, I design a stacking carrousel system to feed trays of strawberries into a process utilizing a 6-axis robotic arm in an industrial bakery.</p>
<p>Following the internship, I continued my collaboration with the company during the summer break and for four additional months in the subsequent year. In this extended period, I served as an engineer, actively involved in machine designs and assemblies. Additionally, I visited the company&rsquo;s clients, where I analysd existing machine processes. My role included conducting objective assessments of machine performance, identifying bottlenecks, and proposing optimization strategies for both the machine design and the customer&rsquo;s processes.</p>
<h1 id="internship">Internship</h1>
<p>During the internship project, I was tasked with designing a carousel system for trays of strawberries to seamlessly integrate into an existing robot cell featuring a UR10 6-axis robot within an industrial bakery. The goal was to facilitate the efficient picking of strawberries by the robot arm from a stack of trays inserted by an employee.
Given the industrial food environment, the design was subject to strict cleaning requirements. Every detail, including edges, corners, holes, and other openings, was carefully designed to optimize the cleaning process.</p>
<p>Additionally, the PLC in the system needed to seamlessly interface with the PLC of the robot arm. Consequently, a PLC program with this communication capability was designed and programmed for this task.</p>
<p>A rendering of the carrousel&rsquo;s Solidworks design is shown in the image below.</p>
<p><img src="aardbeien_carrousel.png" alt="Caption"></p>
<h1 id="machine-design-assembly-and-optimalisation">Machine design, assembly and optimalisation</h1>
<p>After the internship, Van Wees offered me a summer side job, and the following year, I continued my involvement with the company for an additional four months after completing my study program in the spring. During this period, I engaged in various projects, doing various tasks including robot programming, optimization, field analysis, mechanical assembly, and electrical assembly.</p>
<p>For programming robots within multi-station robot cells, featuring UR10 collaborative and Epson Scara LS6 robots, I focused on enhancing efficiency. This involved analyzing task execution orders, optimizing robot motions, and implementing additional logic to make the systems more adaptive to dynamic situations.</p>
<p>For deployed production machines operating in the field for several years, I did an objective alalysis and adviced both Van Wees and the customer. My approach involved studying the product and the customer&rsquo;s process, logging machine production data, and conducting a thorough analysis of the results how downtime can be decreased and production optimised.</p>
<p>Contributing to the production of Van Wees machines, I found great satisfaction in both mechanical and electrical assembly tasks. In mechanical assembly, I followed design schematics to assemble parts, while in electrical assembly, I installed numerous sensors on robot cells. This included adjusting cable ducts to the correct size, wiring sensors to can-bus hubs, and connecting can-bus hubs to the PLC. I particularly enjoyed installing and wiring the electronic components at the workshop.</p>
</description>
</item>
<item>
<title>Carbon cure computer</title>
<link>/project/carbon-cure-computer/</link>
<pubDate>Mon, 16 Nov 2020 00:00:00 +0000</pubDate>
<guid>/project/carbon-cure-computer/</guid>
<description><p>I constructed a control system for a companion, designed to monitor and control the curing process involved in creating carbon products or conducting repairs. The compact control system is compactly housed in a Peli Case, as shown in the image above.</p>
<p>While featuring a minimal physical interface, the system offers extensive monitoring, configuration, and control capabilities wirelessly through an application accessible on a phone, tablet, or PC. The primary objective of this control system is to measure and control the vacuum and temperature. To achieve this, the system incorporates a vacuum and thermocouple sensor, and has two relays to control a regular vacuum pump and a heating element within a 2x2kW limit.</p>
<p>To ensure safety, the system incorporates protective features against overcurrent and overheating. Additionally, it provides warning/error signals in the event of unintended behavior, such as a leaking vacuum or a malfunctioning heating element.</p>
<p><img src="cure_computer.jpeg" alt="Caption"></p>
</description>
</item>
<item>
<title>Study Mechatronics</title>
<link>/project/study-mechatronics/</link>
<pubDate>Mon, 01 Jun 2020 00:00:00 +0000</pubDate>
<guid>/project/study-mechatronics/</guid>
<description><p>WRITE TEXT HERE</p>
</description>
</item>
<item>
<title>Carbon workshop</title>
<link>/project/carbon-workshop/</link>
<pubDate>Wed, 04 Jul 2018 00:00:00 +0000</pubDate>
<guid>/project/carbon-workshop/</guid>
<description><p>around 2015-2018 I helped at
<a href="https://www.meeusencomposites.nl/" target="_blank" rel="noopener">Meeusen Composites</a> to build and repair carbon, mainly for racing sailboats. In the carbon workshop I helped with various tasks such as:</p>
<ul>
<li>Building moulds for carbon parts with the CNC router</li>
<li>Sanding/waxing moulds in preperation of the manufacturing process</li>
<li>Cut fibers to size according to laminate plan</li>
<li>Build carbon products with wet layup</li>
<li>Build carbon products with prepreg fibers (layup and vacuum)</li>
<li>Build carbon products with vacuum injection (dry layup, epoxy impregnated via bleeder layer and vacuum) (shown in image)</li>
<li>Prepare broken parts for repair (sanding, milling, etc)</li>
<li>Shaping Naca profiles with moulds, fill primer, and lots of sanding</li>
</ul>
<p>Also, I built a control system for an autoclave which could measure 3x product vacuum, 1x tank pressure, 3x product temperature and could control the tank preasure, tank temperature, and product vacuum. This control system had beside the physical interface at the autoclave also a webpage interface to supervise and log the process, and if nessesery adapt or stop the process.</p>
</description>
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