Experience
Sr. Process Engineer @ Murata
Vantaa, Finland (Sep 2022 – Present)
Process owner, silicon–glass fusion area
I own the silicon–glass fusion area in wafer manufacturing: process optimization, yield improvement, qualification of new equipment, automation, and cost reduction. The role runs the full loop — from a hypothesis and a designed experiment to a validated, documented change released into production under the Engineering Change Notice (ECN) procedure.
Core Responsibilities:
- Process ownership: silicon–glass fusion, structural integrity, and the post-fusion workflows.
- Statistical qualifications: qualifying new equipment and process changes with designed experiments (DOE), process capability studies (Cp/Cpk), measurement system analysis (MSA, Gage R&R), and hypothesis testing — with acceptance criteria and sample sizes fixed before the first run, not fitted afterwards.
- Development projects from idea to production: experiment design, execution, data analysis, documentation, and formal approval through the ECN procedure (planning, validation, safe launch, reporting).
- Root-cause investigations: leading the cross-functional team (CFT) on critical process problems, using FTA and 8D.
- Process control: SPC and continuous improvement to reduce variation and keep the process centered.
- Commercial side: purchases and supplier quality projects, financial assessments, and ROI analyses.
Automation & Data Systems:
- Machine automation project lead: leading the project that brings production equipment into an automated operational workflow — machine-level data collection combined with automated process steps, so the system enforces the correct sequence and flags out-of-spec conditions instead of relying on someone remembering to check. Mistake-proofing built into the process, not bolted on as a checklist.
- AI in production: process controls built on AI for predictive maintenance and smarter production workflows, running on live process data.
- Visualization: built Power BI and JMP dashboards for day-to-day process analysis.
- Mentorship: mentoring engineers in Python, machine learning, and deep-learning initiatives.
My Impact:
- Yield leadership: when I started in 2022, overall yield was 96% and falling. We have improved it every year since, and it now stands above 98.5%. Along the way, scrap costs dropped 40% in a single year. The next target is 99%.
- Qualified, not guessed: every new tool and process change in my area goes in with a statistical qualification behind it, which is what makes the yield gains hold instead of drifting back.
Manufacturing Processes
- Thermal glass-silicon fusion
- Edge grinding
- Edge profilometry
- Grinding
- Washing
- Etching processes
- Thermal relaxation processes
- Polishing processes
- Metrology tools
Data & AI Work
- Predictive maintenance on the glass-silicon fusion process
- Data-driven grinding process control
- Machine automation system with automated data collection and operational workflows
- Power BI and JMP dashboards for process analysis
- Mentoring engineers in Python and machine learning
Thesis Worker @ Aalto University
Espoo, Finland (2021)
- Investigated the degradation of lithium-ion battery materials (NMC811 and graphite) for second-life applications.
- Conducted extensive material characterization and data analysis as part of a Business Finland commission.
Process Operator @ Okmetic
Vantaa, Finland (2012 – 2017, summer jobs during studies)
- Started in semiconductor manufacturing in a cleanroom environment, specializing in Double-Sided Polishing (DSP) of wafers.
- Operated precision equipment, performed maintenance, troubleshooting, and quality control.
- Utilized data to monitor processes and ensure quality standards were met.
- Expanded role to include Single-Sided Polishing (Okamoto XLSSP) and wafer sorting, contributing to process development and loss minimization.