I help MedTech manufacturing teams qualify equipment, run FAT/SAT/commissioning, build test stands/fixtures, and solve hands-on manufacturing engineering issues (equipment retrofit, root-cause analysis, verification rig build) — delivering audit-ready, submission-driven evidence and repeatable results.
MedTech / Biotech manufacturing • cleanroom equipment • test & assembly machines
References available upon request • NDA-friendly anonymized samples
Short, execution-focused manufacturing engineering fixes for regulated manufacturing and connected systems.
Result: Clear close-out path with audit-ready evidence.
Result: FAT/SAT runs with clean acceptance evidence and controlled punch-list closure.
Result: Stabilized equipment with documented root cause and fixes.
Result: Repeatable measurements + audit-ready evidence.
Result: Risk-based CSV/CSA scope with traceability and test coverage.
Result: IEC 62304 evidence set + submission-driven cybersecurity test plan.
Hands-on execution for field issues, retrofit work, and verification rigs — NDA-safe, evidence-ready.
Problem: Field issues demand fast root-cause analysis, an equipment retrofit, and verification evidence.
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Problem: Sensor integration behaves differently in the field than in the lab.
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Problem: A fixture or verification rig prototype has to work quickly.
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Problem: Production equipment instability hurts throughput and quality.
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Problem: Small embedded changes trigger large re-validation scope.
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Problem: Test method is not repeatable on real hardware.
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If late requirements, cybersecurity, and testability are inflating scope, see verification-driven engineering in MedTech.
Three focused offers with a clear front door: Qualification + FAT/SAT first, supported by engineering and CSV/CSA.
Primary track
Audit-ready protocols, execution support, and evidence packs to release equipment confidently.
Secondary track
Rapid prototyping of electromechanical test solutions designed to scale.
PLC/SPS integration via partner network when required.
Specialist track
Risk-based CSV/CSA for software and connected systems that support product development and regulated manufacturing. Focused on intended use, data integrity, and audit-ready evidence — without document-heavy overhead.
Aligned with FDA CSA guidance and GAMP 5 (2nd edition) context.
If late requirement shifts are inflating scope, this explains the pattern and how to avoid it: Verification-driven engineering in MedTech .
Four steps that keep scope tight and make QA/Engineering happy.
Lock requirements, constraints and acceptance criteria.
Risk-based scope, test strategy and documentation map.
Protocols, evidence, deviations and reports.
Clean package + recommendations for requalification/maintenance.
Predictable scope & transparent change control.
Every project is scoped individually. Most clients start with either a short fixed-scope package or a time-based engagement for execution support.
How you avoid surprises: We agree on scope, deliverables and acceptance criteria upfront. Any change is handled as a clear change request.
Low-risk first steps that clarify scope and produce tangible outputs.
Short, focused engagement to assess validation gaps and define a practical, risk-based path forward (typically 1–2 working days).
Rapid review of URS/specs + available vendor docs; you get a prioritized gap list and a recommended path to DQ/IQ/OQ/PQ (scope by criticality).
Acceptance criteria + checklist aligned to your URS and risks; includes a punch-list template to drive clean close-out with the vendor.
Engineering sketch of a practical fixture/test stand: requirements, architecture outline, key components, and a rough BOM — designed to scale toward industrialization/qualification.
Criticality map + validation approach for a system with data flows and dependencies; you get a clear testing/evidence path (CSV now, CSA where appropriate).
Concise, anonymized case studies focused on engineering outcomes.
Problem: Two machines needed release with clear acceptance criteria and evidence for DQ/IQ/OQ.
What I did: Built the qualification plan, wrote DQ/IQ/OQ protocols, and supported FAT/SAT and cleanroom execution.
Outcome: Faster release with fewer deviations and a clean QA evidence package.
Problem: R&D needed a rapid prototype to de-risk a process and generate repeatable measurements.
What I did: Designed and built the rig with Arduino control, stepper motor, linear stage, IR lamp, and pneumatics.
Outcome: Reliable test data and a clear path to industrialization.
Problem: Manual verification steps were slow, variable, and difficult to scale.
What I did: Defined fixtures and sequences for an Omron cobot workflow with test automation and evidence capture.
Outcome: Improved repeatability and throughput with cleaner verification records.
Problem: A connected hardware add-on plus multiple software services (incl. cloud/data flows) had to be validated in a US-bound / FDA context. The system had many dependencies and frequent changes, requiring repeated validation cycles.
Approach: Risk-based CSV delivery (scope by criticality), traceability across HW/SW, test scripts and evidence capture for key workflows and data integrity, dependency mapping, structured change impact assessments and re-validation. Over time, transitioned the validation approach toward CSA to keep pace with changes while preserving audit-ready evidence.
Result: Audit-ready validation evidence across integrated components, faster iteration cycles, and clearer change control for a complex connected system.
Practical, engineering-first notes for MedTech manufacturing teams focused on evidence, scope, and execution.
Senior-engineer playbook with scope boundaries, evidence checklist, and cybersecurity workstream.
Why production installs failed: turbulence, placement bias, scaling, and redundancy logic.
How to keep installation and operational evidence clean, traceable, and audit-ready.
Define measurable criteria and use a punch-list workflow that closes gaps before qualification.
Risk-based assurance that reduces low-value testing without reducing evidence quality.
Common gaps in drawings, specs, and work instructions — and how to close them fast.
Practical boundaries and evidence planning for connected devices, cloud, and mobile apps.
Engineering choices that make test data trustworthy in real projects.
Anonymized, NDA-safe examples focused on problem, approach, and result.
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Short, no fluff.
Boutique engineering studio. I deliver projects hands-on and scale with a trusted network of specialist engineers (mechanical, embedded, PCB, machining) when needed. PLC/SPS integration via partner network when required.
Equipment qualification (DQ/IQ/OQ/PQ) • FAT/SAT support • Commissioning support • Verification (GR&R/MSA) • Test stands/fixtures & jigs • Automation • Robotics (cobots) • Prototypes • Productivity improvements
MedTech / biotech manufacturing • regulated • cleanroom / production
ISO 13485 • ISO 14971 • IEC 60601 • IEC 62304 • ISO 11608 • ISO 14644 • ISO 12100 • ISO 13849-1 • IEC 60204-1 • 21 CFR Part 11 • EU GMP Annex 11 • GAMP 5 • MDR • IVDR
Fastest via email or phone. I reply within 24 hours.
Email
info@techkrates.com
Phone
+41 783 20 66 33
WhatsApp
Chat on WhatsApp
LinkedIn
linkedin.com/company/techkrates
