Quality as a way to investigate.
Nonconformities, root-cause analysis, technical documentation and corrective actions established the foundation: observe, gather evidence and verify effectiveness.
Professional portfolio / 2026
Lucas Rosate
Quality Engineering · Continuous Improvement · Industrial Digital Transformation
I am a metallurgical engineer working at the intersection of quality, industrial processes, product performance and technology. My experience combines technical investigations, continuous improvement, data analytics and digital solutions for industrial environments.
I start with the evidence. From there, I define the method, select the tools and set the criteria used to verify effectiveness.
00 / Starting point
Quality taught me to investigate. Product development broadened how I read risk. Data and automation gave scale to analysis and recurring industrial routines.
I turn complex industrial problems into robust processes, better decisions and sustainable results.
01 / Career path
From nonconformity investigations to integrated operational systems.
Five movements show how quality, product, data, automation and technical coordination became one coherent engineering practice.
Data and automation grew out of operational needs.
VBA tools, Business Intelligence and Python routines reduced manual preparation, supported comparisons and made operational information more available.
Product development broadened the analytical frame.
R&D, testing and specifications broadened my view of the product lifecycle. In APQP and PPAP, I contributed to selected framework stages and specific layers of the documentation rather than leading the full process.
Applications began to support the entire workflow.
Power Platform, SharePoint and Qlik Sense connected records, ownership, deadlines, evidence and follow-up in one workflow, from initial record to verification.
Technical coordination across functions.
The scope grew to include cross-functional investigations, technical communication with customers, implementation follow-up and an integrated view of quality, production, maintenance and improvement.
02 / Selected projects
Three central cases and one complementary system.
The three main cases examine data architecture, workflow redesign and operational automation. The complementary system documents a different application architecture.
Case 01 / Operational intelligence
A connected view of the operation.
I structured a platform to reduce the effort spent preparing information and increase the time available for interpretation, risk analysis and decision-making.
80+tables in the associative data model
Open the case
01Industrial sourcesquality · production · maintenance
02Support routinesPython · SQL · VBA
03Qlik Load Scriptjoins · mapping · history
04Associative modelkeys · dimensions · measures
05Analytical userelationships · reading · decisions
Case 02 / Customer Quality
Mapping, 8D and governance in the complaint workflow.
Working with the participating teams, I mapped bottlenecks, structured inputs, introduced an 8D-based standard and monitored adoption after the new workflow was introduced.
59%reduction in average lead time
Read the process
01Input
02E-mail
03Document
04Plant
05Actions
06Status
Disconnected channels and control points
Case 03 / Traceability
On-demand updates across shifts.
A routine dependent on one person became a repeatable extraction, transformation and integration process for supply, raw-material and order-book information.
4 h → <1 minper execution
See the automation
01TXT + Websources
02VBAextraction
03Structuresplit · rules
04Integrationorder book
05Operationson demand
Complementary project / SISVE
From item-level inspection to historical analysis in Qlik Sense.
SISVE records every inspected item, routes nonconformities and follows action plans through the auditor's decision. Qlik Sense consolidates historical performance and recurrence patterns.
16industrial processes in scope
Explore the system
SISVEauditable workflow across 16 processes
01 · AuditComplete recordEvery inspected item is recorded.Power Apps
02 · SISVEConsolidation and routingShows the item, reason, owner and management follow-up.SharePoint · Automate
03 · Area ownerAction planA due date is set and evidence is attached.Planner · SharePoint
04 · AuditorApprove or rejectRejection requires a new plan and new evidence.recorded decision
Rejectedreturns to the action plan before the due date
05 · Qlik SenseHistorical evolutionAudits, repeat findings, recurrence, performance and status.consolidated analysis
03 / Technical depth
Stability, product risk and action effectiveness.
Methods and systems appear with their application context, without turning the portfolio into a catalogue of acronyms.
Quality Engineering / SPC
Stability comes before capability.
Monitoring performance means reading the specification alongside variation, trends, recurrence and the ability to sustain performance over time.
I first verify whether variation remains under control over time.
Product / Core Tools
Requirements, risk and performance in one line of thought.
Work in product development, testing, FMEA and control plans, with participation in selected APQP stages and specific layers of PPAP documentation.
APQPPPAPFMEAControl Plan
Technical coordination
Investigations that cross functions.
Methods, criteria, ownership, due dates, stakeholder integration and implementation follow-up.
technical coordinationcross-functional work
Customer interface
Technical clarity in critical situations.
Clear communication about the analysis, next steps, deadlines and the criteria used to verify effectiveness.
Customer Quality8Dactions
Oracle SQL / IBM Cognos
Technical value also exists in legacy environments.
Custom views, historical queries and reports were structured while respecting the performance, access and stability constraints of the existing infrastructure.
04 / Technical toolkit
Methods and tools organised by the role they play.
The disciplines remain distinct. Select an item to see a concrete application and the sequence in which it enters the work.
Quality Engineering
Requirements, prevention, investigation and effectiveness assessment.
Continuous Improvement and Processes
Methods for reading flow, prioritising causes and sustaining change.
Industrial Data and Analytics
Modelling, integration and visualisation for interpreting operations.
Automation and Applications
Process-adjacent solutions that reduce manual effort and improve traceability.
In development and personal projects
Technical exploration; not presented as consolidated professional experience.
05 / Keep in touch
If a project sparked an idea, let’s continue the conversation.
On LinkedIn, I share my professional path and experience. On GitHub, I keep projects and technical explorations. For a direct conversation, send me an email.