✳ PROCESS · DEVELOPMENT · MANUFACTURING
I work at the intersection of manufacturing quality, practical engineering and process improvement—with hands-on experience in automotive aluminium die casting and a growing focus on process and development engineering.
QUALITY ASSURANCE
Automotive aluminium HPDC internship
ENGINEERING DEGREES
M.Sc. ITTM + B.Tech. Automobile
LEAN SIX SIGMA
CSSC Green Belt · 2026
SELECTED CASE STUDIES
Industry · Student · Educational
01 / THE JOURNEY
A foundation in automotive engineering, shaped by production-floor experience and technology-management studies.
Lovely Professional University
Built fundamentals in vehicle systems, manufacturing, engineering design and CAD/CAE. Took part in Formula Student fabrication and vehicle electronics activities.
Precise Engineering Company · Nashik
Six-week summer training covering production workflows, inventory, documentation and basic quality activities.
Precise Engineering Company · Automotive aluminium HPDC
Worked on incoming, in-process and outgoing inspections, 3D measurement, nonconformity records, X-ray/leak-testing exposure and 8D/root-cause support in an IATF 16949:2016 quality-system environment.
FHM Berlin
Studied technology transfer, innovation, sustainability and project management. Master's thesis explored green technology transfer between Germany and India.
CSSC Green Belt · SAP Learning · Siemens SCE · Semiconductor Fabrication 101
Strengthened structured problem-solving, quality systems, PLC concepts and introductory semiconductor-fabrication knowledge, supported by explicitly labeled educational data simulations.
02 / SELECTED WORK
A transparent mix of internship practice, student engineering and independently modeled learning projects.
CASE STUDY 01 INTERNSHIP / TECHNICAL REPORT
Examining the manufacturing logic behind an automotive water-pump housing—from die geometry and gating to cast-defect mechanisms and part inspection.
Automotive aluminium HPDC formed the industrial setting for my quality-assurance internship. The water-pump housing was analyzed through a separate internship engineering report.
Reviewed die geometry, gating and venting, process parameters and casting-defect mechanisms; examined NX 6 outputs and Excel-based manufacturing calculations.
Performed dimensional and visual checks on automotive components, recorded nonconformities and supported inspection improvements, using hand gauges and a 3D measuring microscope.
The visual above is an original schematic for explanation, not a reproduction of an employer drawing or a claim of independent die design.
CASE STUDY 02 ACADEMIC / STUDENT TEAM
Formula Student brought fabrication, mechanical assembly and vehicle electronics together in one hands-on team environment.
Participated in student workshop CNC machining, welding, soldering, fabrication and race-car component fit-up and assembly.
Worked on the CAN-based dashboard, wiring harnesses, microcontroller activities and telemetry/data logging within the student team.
Academic and student-team use of Vector CANoe/CANalyzer and MATLAB/Simulink Vehicle Network Toolbox.
Team project: activities reflect participation, not sole ownership of the complete vehicle.
CASE STUDY 03 PERSONAL EDUCATIONAL SIMULATION
A DMAIC dimensional-rejection exercise with 300 synthetic CNC-spacer inspection observations, stratification and a modeled what-if correction.
Relative reduction in modeled rejections if the hypothetical centering adjustment worked as assumed.
Synthetic data · improvement not physically implemented or independently measured.
Framed a dimensional rejection problem and assessed 300 synthetic observations: 26 modeled baseline rejects (8.67%).
Stratified observations by machine, tool age and shift; explored root-cause hypotheses and modeled a centering adjustment without real production intervention.
Proposed gauge verification, a real-world pilot, dimensional monitoring and escalation checks that would be needed before claiming actual process gains.
Disclosure: Fully synthetic learning simulation. The 4.00% result and 53.85% reduction are hypothetical calculations, not measured employer outcomes.
CASE STUDY 04 INDEPENDENT EDUCATIONAL SIMULATION
An introductory lot-monitoring and excursion-investigation exercise using Python/Excel, simulated defect records, DPPM and statistical process monitoring.
Built a reproducible learning package with 36 synthetic inspection lots representing 1.8 million simulated devices. Calculated DPPM and baseline p-chart limits.
Flagged six scripted excursion lots and organized defect categories, possible causes and structured containment and verification steps.
The figures, alerts, defect patterns and investigation outcomes are educational scenarios; no semiconductor production data or fab testing was involved.
The grid is a simplified illustration of the simulated monitoring exercise, not real-time fab data.
03 / CAPABILITIES
Skills are grouped by how I developed them—industrial practice, academic/team application, and formal learning.
Incoming, in-process and final inspection; drawing interpretation and tolerances; 3D measuring microscope, hand gauges, traceable documentation and inspection routines.
Manufacturing and defect analysis, 5 Whys, complaint follow-up, Lean Six Sigma DMAIC and structured process reasoning—applied in internship work and educational projects.
Formula Student mechanical assembly and workshop fabrication, vehicle wiring and CAN communications; CAD, simulation and programming through academic work.
Excel analysis and reporting, SAP/ERP fundamentals, introductory Python, Siemens TIA Portal knowledge badges and semiconductor-process learning.
CREDENTIALS / SELECTED
English Fluent German B1 · B2 in preparation Hindi & Marathi
04 / CONTACT
// OPEN TO THE NEXT CHALLENGE
I’m interested in early-career roles spanning process engineering, development, manufacturing, testing and quality—across Germany and beyond.
CONNECT ON LINKEDIN ↗riteshd3436@gmail.com