Amin Paknejad
PhD-level Mechanical Engineer, Software Developer, and Technical Instructor focused on integrated industrial systems, engineering methods, and AI-assisted software workflows.
Professional Summary
Engineering methods, manufacturing execution, software automation, and technical instruction.
Highlights of Qualifications
Expert in CATIA V5 and PLM-based engineering methods, with strong experience producing Engineering Masters (EM), Work Instructions (WI), and assembly documentation that connect design intent to shop-floor execution. Combines root-cause analysis and computational tooling to optimize manufacturing and operations.
Methods and Production Documentation
Structured EM/WI assets, MBOM control, and execution-ready assembly guidance.
Computational Acceleration
Python/C# automation for simulation flow, sequencing, and quality improvements.
Cross-Functional Delivery
Alignment across production, quality, procurement, and technical leadership teams.
Contact
Manufacturing Systems
CATIA V5, SolidWorks, PLM (Enovia/SmarTeam), AutoCAD, MBOM control, and tooling methods.
Automation and Software
Python, C#, C/C++, Fortran, SQL, TensorFlow, and parallel processing with MPI/OpenMP.
Engineering Analysis
RCA, CFD (Ansys Fluent), fluid-structure interaction, feasibility and cost-impact analysis.
Work Experience Portfolio
Each role includes implementation highlights and measurable contributions.
Technical Instructor (Industrial Automation and Systems Logic)
- Instruct advanced program logic and Python automation for industrial workflow scenarios.
- Built information management curriculum modeled on PLM/ERP hierarchy and data integrity principles.
- Mentored engineering capstone teams on technical documentation and structured build sequencing.
- Translated high-level engineering concepts into executable, operationally useful instructions.
Intermediate Methods and Mechanical Engineer
- Developed and maintained EM and WI documents for manufacturing process and assembly execution.
- Led root-cause analysis of production non-conformances and deployed corrective actions.
- Managed MBOM and material equipment lists under strict configuration control requirements.
- Performed technical feasibility and make-vs-buy analysis for design change decisions.
- Collaborated with production, quality, and procurement to integrate product updates smoothly.
Mechanical and Manufacturing Design Engineer
- Designed complex structural sub-assemblies with CATIA V5 and SolidWorks.
- Optimized assembly sequencing through simulation, improving performance efficiency by 15%.
- Produced graphic assembly manuals and planning documents for shop-floor teams.
- Authored engineering change requests for tooling and method refinement.
Technical Lead and University Lecturer
- Taught mechanical engineering and computer science with applied computational focus.
- Led training and mentorship programs for junior engineers and co-op students.
- Directed research on fluid-rigid-elastic structure interaction and vibration integrity problems.
- Connected theoretical research with practical engineering implementation.
Industrial Software Developer
- Built industrial software to automate mechanical design and simulation tasks.
- Applied systems logic and QA protocols for reliability in production software contexts.
- Adapted software behavior to evolving project-specific requirements.
Education
Mechanical Engineering - University of Tehran
Advanced fluid-rigid-elastic interaction and numerical strategy development.
Mechanical Engineering - IUT / MUT
Applied engineering analysis and advanced manufacturing disciplines.
Computer Software Engineering - University of Shiraz
Digital systems logic and software-oriented engineering perspective.
Certificates and Credentials
Combining engineering depth, software architecture, and instructional leadership for practical industrial and educational outcomes.
Recent Project Highlights
- Developed Engineering Masters and Work Instructions for transitioning PAKSHAR 3000 from concept to high-volume manufacturing.
- Designed structural bodies and frames in CATIA V5, optimized for digital manufacturing feasibility.
- Improved assembly build sequencing and reduced bottlenecks through mechanical analysis.
- Architected ML-based sorting for industrial inspection workflows using Python and deep learning libraries.
Publications and Research
Selected research in fluid dynamics and numerical simulation with practical engineering impact.
Engineering depth with practical software execution
Open for industrial, educational, and automation collaborations.