MECHATRONICS ENGINEER | BRIDGING SYSTEMS, SOFTWARE & HARDWARE
Mechanical-design-focused engineer with hands-on experience in static FEA, topology optimisation, ROS2 navigation, and on-site MEP commissioning on the Ontario Line transit project. On track for P.Eng licensure with PEO (Oct 2026).
I'm Abdulrahman Almansy, a BEng (Hons) Mechatronics Engineering graduand at Asia Pacific University (APU) (expected Oct 2026), based in Ontario, Canada. EIT-eligible, on track for P.Eng licensure with PEO upon graduation.
My focus sits at the mechanical end of mechatronics — static FEA, topology optimisation, CAD/CAM, and vibration-aware dynamic analysis — backed by real commissioning experience on the Ontario Line transit project (Connect 6ix, Toronto). I treat every system as an integration problem: structure, motion, control, and software must all speak the same language.
From mesh-convergence studies in SolidWorks Simulation to tuning Nav2 cost-maps in ROS2 and commissioning PLC interlock logic, I apply a failure-first mindset — FMEA and RCA before the first weld, not after the first incident.
Reduced bracket mass by 28% while maintaining FoS > 2.5 via topology optimisation on a 6061-T6 aluminium component under 5 kN loading. Validated with mesh-convergence study (<5% von Mises stress variance). Generated 5-operation CAM toolpaths, cutting machining time by 15%.
Designed a custom 10 m × 8 m warehouse SDF world in Gazebo Harmonic and built the full navigation stack from scratch — SLAM Toolbox → AMCL localisation (500–2000 particles) → NavFn/Dijkstra global planner → DWB controller. Built a Python/tkinter operator GUI with live occupancy-grid map and real-time /odom robot position. Resolved 5 critical failure modes via RCA — including ROS2 Jazzy's TwistStamped cmd_vel type change, AMCL world-to-map frame offset, and Nav2 goal rejection in occupied costmap cells — achieving 92% waypoint success.
Programmed an 8-rung Omron PLC ladder-logic sequence driving double-acting pneumatic cylinders (solenoid valves), relay unit, and a magnetic pick-and-place actuator. Configured totalising timers (TTIM 001 = 20, TTIM 003 = 30, TTIM 005 = 20 units) for sub-cycle synchronisation. Applied FMEA on ladder rungs to eliminate 3 sequence race conditions, achieving ±50 ms timing consistency across 100+ cycle dry-runs with E-stop and interlock logic per safety-circuit standards.
Reduced sensor-to-actuator reaction latency by ~20% across 50 bench-test runs by tuning ultrasonic threshold logic, DC motor PWM response timing, and applying low-pass filtering on range measurements — mirroring real-time control challenges in industrial AGV platforms.
Built an end-to-end rehabilitation platform: an ESP32 glove with 5 flex sensors + MPU6050 IMU detects 5 hand gestures (2 s hold debounce, instant emergency stop) via calibrated per-finger thresholds, driving a 60-LED WS2812B NeoPixel strip. PyQt5 dashboard provides live elbow-angle plotting, circular rep counter, and CSV session logging. Voice control via ElevenLabs TTS + Google SR with fuzzy matching selects from 3 rehabilitation intensity plans with mid-session resume.
Designed a 7-phase explainable fault diagnosis framework for photovoltaic systems, combining XGBoost with Tree SHAP to attribute each prediction to the 5 monitored parameters (I, V, P, G, T) across 4 fault classes — normal, open-circuit, short-circuit, and partial shading. Benchmarks XGBoost against RF, SVM, and CNN with both Tree SHAP & Kernel SHAP — the first cross-architecture SHAP comparison in a unified PV fault pipeline. Targets macro F1 > 0.85. Aligned with UN-SDGs 7, 9 & 13.
Programmed an ABB IRB 120 industrial manipulator in RAPID to pick and place 20 coloured pegs across two pallets, forming target letter patterns. Sequenced MoveL commands with calibrated Offs() 3D offsets (±25 mm to ±150 mm), dual velocity profiles (v1000 / v500), and DO16_GRIPPER_ON Set/Reset for pneumatic gripper control. Diagnosed positioning misalignment and gripper timing errors through iterative coordinate tuning.
Designed and simulated a complete regenerative braking system for a 1500 kg EV in MATLAB/Simulink. The DC motor model (0.8 Nm/A torque constant, 8:1 gear ratio) operates as a generator during a 6-second braking event, decelerating the vehicle from 80 km/h to 15 km/h. Peak negative motor torque of −200 Nm drives 212.5 A into a 400 V battery pack, recovering 115 Wh at 82.7 kW peak. Overall system efficiency held at 85%, with regeneration approaching 100% efficiency during steady deceleration — equivalent to ~25% city range extension.
Photovoltaic arrays lose yield — and can become a fire risk — when open-circuit, short-circuit, or partial-shading faults go undetected. Machine-learning classifiers can spot these faults, but most act as black boxes: an operator sees a label, not a reason, which makes the output hard to trust or act on.
My FYP builds a 7-phase explainable fault diagnosis framework that pairs XGBoost with Tree SHAP, attributing every prediction to the five monitored parameters — current (I), voltage (V), power (P), irradiance (G), and module temperature (T).
How my work across the BEng (Hons) Mechatronics Engineering programme — coursework projects, the FYP, and my industry internship — shows each of APU's twelve programme learning outcomes (PLOs). Each card gives the official outcome, then my evidence for it.
Ability to gain and apply principles of Mathematics, Science and Engineering to the solutions of complex engineering problems.
Applied solid mechanics to a 6061-T6 bracket under 5 kN load, electric machine and power-electronics theory to a regenerative braking model, and PV electrical behaviour to fault diagnosis.
Ability to undertake complex engineering problem analysis and apply engineering principles to solve them.
Used root-cause analysis to resolve 5 critical failure modes in a ROS2 navigation stack, and applied FMEA to remove 3 race conditions from PLC ladder logic.
Ability to select and use suitable tools and techniques for complex engineering problems.
Chose and used SolidWorks Simulation and CAM, ROS2 with Gazebo, MATLAB/Simulink, Omron PLC ladder logic, ABB RAPID, and Python ML libraries, with Git for version control.
Ability to investigate complex engineering problems using research techniques.
Validated FEA with a mesh-convergence study (under 5% stress variance), ran 50 bench tests to tune a real-time controller, and found a research gap for my FYP through a literature review.
Ability to design innovative solutions for complex engineering problems.
Cut bracket mass by 28% through topology optimisation while keeping FoS above 2.5, designed a gesture-controlled rehabilitation system, and built a 7-phase explainable fault-diagnosis framework.
Ability to communicate effectively and professionally on complex engineering activities.
Tracked 40+ RFIs and kept revision-controlled drawing registers on site, and presented work through technical reports, posters, video presentations, and documented GitHub repositories.
Ability to comprehend and demonstrate good practices of engineering in sustainable development and environmental considerations for the solutions of complex engineering problems.
Modelled EV energy recovery of 115 Wh per braking event, lightweighted components to save material, and aligned my FYP with UN SDGs 7, 9, and 13.
Ability to engage in professional engineering practice for safety, health, social, cultural and legal responsibilities in developing solutions for complex engineering problems.
Checked mechanical installations on a public transit project against CSA and project standards, built E-stop and interlock safety logic, and designed assistive technology for rehabilitation patients.
Ability to execute the responsibilities of an Engineer professionally and ethically.
Reported 12+ site-to-drawing discrepancies rather than letting them pass, followed CSA and ASME standards, reported results honestly against targets, and credited all sources.
Ability to function effectively as a team leader or a member in a team within multi-disciplinary settings.
Coordinated with mechanical, electrical, and structural disciplines on site, delivered group projects in CAD/CAM, ROS, and design, and led my FYP from scope to delivery.
Ability to recognize the need for, and be able to engage in independent and life-long learning towards continuous professional development.
Taught myself ROS2 Jazzy's API changes, explainable AI, and SHAP beyond the curriculum, and am working toward EIT status and P.Eng licensure with PEO.
Ability to demonstrate entrepreneurship skills, engineering project management and economic decision making in multi-disciplinary environments.
Maintained equipment schedules and material cost data feeding procurement, cut machining time by 15% with optimised CAM toolpaths, and designed my FYP as a software-only tool that adds no hardware cost.
An honest look at where I stand as an engineer after four years of study and industry experience.
Whether you have a project in mind, want to discuss engineering challenges, or are looking for a driven mechatronics intern — I'd love to hear from you. Let's build something remarkable.
Thanks for reaching out — I'll get back to you soon.