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Selected Projects / Case Snapshots

Anonymized engineering case snapshots from MedTech manufacturing and R&D, focused on artifacts, execution, and verification evidence.

Details are NDA-safe. The emphasis is on what was built, how it was validated, and what evidence made decisions defensible.

Case A — Equipment qualification close-out in Swiss MedTech manufacturing

Problem

  • Qualification package incomplete and inconsistent across suppliers.
  • Missing component specifications and as-built electrical/pneumatic schematics.
  • Work instructions too thin or not tied to acceptance checks.

Approach

  • Created qualification protocols and reports aligned to IQ/OQ needs.
  • Executed stability testing where required for process evidence.
  • Authored CSV plan and report for software-backed workflows.
  • Produced as-built electrical/pneumatic schematics and component specs.
  • Reworked work instructions with step checks and data capture.

Result

  • Clear visibility of gaps and closure evidence.
  • Faster qualification close-out with fewer QA loops.
  • Improved audit readiness for equipment release.

Case B — R&D electromechanical test stand prototype

Problem

  • R&D needed a stand to explore manufacturing parameters for a new product.
  • Integration complexity across microcontroller, stepper drivers, motion, and repeatability.

Approach

  • Designed fixture and motion stack with repeatability targets.
  • Integrated microcontroller firmware, stepper drivers, and sensors.
  • Implemented logging with configuration IDs and timestamps.
  • Ran a quick GR&R to isolate dominant variation sources.
  • Tuned motion profiles and fixtures for stability.

Result

  • Working repeatable test stand enabling broader parameter testing.
  • Parameter studies supported by traceable data.

Case C — Connected HW/SW system: CSV to CSA transition driver

Problem

  • Embedded + cloud + iOS/Android ecosystem with frequent changes.
  • Small embedded library updates triggered full-system re-validation.
  • Submission-driven evidence expectations required defensible scope control.

Approach

  • Authored system specs and intended-use boundaries.
  • CSV plan and risk-based test strategy defining reduced scope.
  • Test execution, reporting, and traceability matrix.
  • SDK/component validation support to isolate changes.
  • Change-impact rules to limit re-validation blast radius.

Result

  • Clear scope for what must be re-validated per change.
  • Evidence package prepared for submission-driven evidence expectations.

Case D — R&D electromechanical test stand prototype (integration hell → repeatability)

Problem

  • Integration across motion, sensors, and embedded control kept failing.
  • Measurements were not repeatable enough for parameter studies.

Approach

  • Built a minimal electromechanical stack with controlled IO and logging.
  • Tightened fixtures and ran a quick GR&R to isolate variation.

Result

  • Repeatable measurements for R&D iterations.
  • Clear path to scale-up fixtures and evidence capture.

Case E — Legacy platform change with IEC 62304 evidence + cybersecurity test planning (anonymized)

Problem

  • Legacy firmware/library change triggered broad re-validation.
  • Cybersecurity testing was not mapped to evidence expectations.

Approach

  • Defined change scope and the IEC 62304 evidence delta.
  • Built a cybersecurity test plan aligned to submission-driven evidence expectations.

Result

  • Re-validation scope limited to impacted components.
  • Evidence package ready for audit/submission context.

Case F — Field retrofit sprint for a cover-staining line (anonymized)

Problem

  • EOL main controller forced a platform change.
  • Field issues showed up after a safety subsystem integration change.
  • Process module variability drove occasional cover glass defects.

Approach

  • Root-cause analysis across field logs, mechanics, and integration logic.
  • Retrofit plan with verification steps and acceptance criteria.
  • Prototype improvements to the process module with targeted tests.
  • Evidence updates for change control and re-validation.

Result

  • Stabilized field behavior with a documented retrofit path.
  • Clearer verification evidence for QA close-out.

Case G — Cryosurgery device connector redesign (anonymized)

Problem

  • Single connector had to combine EEPROM, pneumatics, and power interfaces.
  • Connector robustness and material compatibility were limiting reliability.

Approach

  • Redesigned connector architecture with clearer interface separation.
  • Mapped EEPROM handling and pinout compatibility for legacy systems.
  • Explored materials and coating trials (e.g., parylene) for durability.
  • Built prototypes and verification checks for fit and sealing.

Result

  • More robust connector concept ready for transfer.
  • Evidence pack for future validation and manufacturing handover.

More projects

Further anonymized projects from production equipment, R&D test rigs and verification automation.

Qualification of two new cleanroom production machines

Problem
Two machines needed release with clear acceptance criteria and evidence for DQ/IQ/OQ/PQ.
Approach
Qualification plan and DQ/IQ/OQ/PQ protocols, FAT/SAT and cleanroom execution support, part corrections during qualification, tests across all product combinations, PQ with stability testing.
Outcome
Both machines qualified within two months, with fewer deviations and a clean QA evidence package.

Pulling machine prototype for materials testing

Problem
R&D needed a rapid prototype to de-risk a process and generate repeatable measurements.
Approach
Rig designed and built with Arduino control, stepper motor, linear stage, IR lamp, and pneumatics.
Outcome
Reliable test data and a clear path to industrialization.

Collaborative robotics for verification automation

Problem
Manual verification steps were slow, variable, and difficult to scale.
Approach
Fixtures and sequences for an Omron cobot workflow with test automation and evidence capture.
Outcome
Improved repeatability and throughput with cleaner verification records.

Engineering Work (Hands-on)

Hands-on execution for field issues, retrofit work and verification rigs. NDA-safe, evidence-ready.

Field issue / retrofit sprint

Problem: Field issues demand fast root-cause analysis, an equipment retrofit, and verification evidence.

See retrofit project snapshot

Typical signals

  • Service events, scrap, or alarms with unclear failure mode
  • EOL components forcing a retrofit under time pressure

What we deliver

  • Root-cause analysis, design fix, and verification plan
  • Retrofit change package with updated evidence

Sensors & measurement systems

Problem: Sensor integration behaves differently in the field than in the lab.

See Omron D6F case

Typical signals

  • Offsets drift after installation or across temperature
  • Redundancy logic trips without a clear failure mode

What we deliver

  • Integration + calibration logic with failure-mode checks
  • Verification plan and evidence updates for QA

Mechanical/mechatronics prototyping

Problem: A fixture or verification rig prototype has to work quickly.

See prototyping service

Typical signals

  • No test setup to validate the design
  • R&D needs data before design freeze

What we deliver

  • Rapid fixture/rig prototype with controlled IO + logging
  • Path to industrialization with documentation notes

Manufacturing equipment robustness

Problem: Production equipment instability hurts throughput and quality.

See equipment qualification support

Typical signals

  • Downtime, scrap, or yield drift under normal conditions
  • Process window not tied to evidence

What we deliver

  • Stabilization plan with root-cause and retrofit actions
  • Manufacturing engineering changes with QA-friendly evidence

Embedded change impact (IEC 62304-aware)

Problem: Small embedded changes trigger large re-validation scope.

See IEC 62304 migration insight

Typical signals

  • Firmware/library updates ripple into safety evidence
  • Embedded change impact is unclear across components

What we deliver

  • Change impact assessment and IEC 62304 evidence mapping
  • Test strategy aligned to submission-driven evidence

Test method + repeatability (GR&R/MSA)

Problem: Test method is not repeatable on real hardware.

See GR&R/MSA insight

Typical signals

  • GR&R/MSA fails due to fixture variability
  • Manual measurements drift between operators

What we deliver

  • Test method definition with acceptance criteria
  • Repeatability improvements and verification rig tuning

If late requirements, cybersecurity, and testability are inflating scope, see verification-driven engineering in MedTech.