00 / Lucas Rosate — Engineering portfolio

Engineering for industrial problems.

Evidence → Analysis → Action → Verification

Quality, process and materials guide the investigation. Data and digital systems expand its reach. These projects document my contribution, the technical decisions and the operational results.

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Lucas Rosate
Lucas RosateQuality engineering

Selected projects

Engineering, data and automation projects

Four case studies document the problem, implementation and available evidence.

Case 01 / Customer complaints

Customer complaints: a shared investigation workflow

I coordinated the redesign with the participating teams: we mapped bottlenecks, structured inputs and monitored adoption of the 8D standard.

59%reduction in average response time
01Input 02E-mail 03Document 04Plant 05Actions 06Status

Disconnected channels and control points

View the complaints workflow

Case 02 / Traceability automation

Material traceability on demand

I automated extraction and integration of supply, material and order-book data. The routine enabled on-demand updates across shifts.

3–4 h → <1 minper execution
TXT + WEB: Supply and raw material sources → VBA: Repeatable extraction → Structure: Split · arrays · processing rules → Integration: Connection to the order book and supply context → Operations: On-demand updates · different shifts01TXT + WEBSupply and rawmaterial sources02VBARepeatableextraction03StructureSplit · arrays ·processing rules04IntegrationConnection to theorder book andsupply context05OperationsOn-demand updates· differentshifts
  1. TXT + WEB

    Supply and raw material sources

  2. VBA

    Repeatable extraction

  3. Structure

    Split · arrays · processing rules

  4. Integration

    Connection to the order book and supply context

  5. Operations

    On-demand updates · different shifts

Select a stage to explore its role in the flow.

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View the VBA automation

Case 03 / Operational intelligence

Operational intelligence across departments

I modelled quality, production, maintenance, delivery and material data in Qlik Sense, reducing repeated consolidation and retaining history for analysis.

80+tables in the associative data model
Industrial sources: Quality · production · maintenance · delivery · materials → Supporting routines: Python · VBA · SQL — extraction and integration → Qlik Load Script: Mapping · joins · concatenation · filters · history → Associative model: Controlled keys · relationships across 80+ tables → Analytical use: Dimensions · measures · decisions in contextQualityProductionMaintenanceDeliveryMaterials02Supporting routinesPython · VBA · SQL03Qlik Load ScriptMapping · joins ·filters · history04Associative modelControlled keys · 80+tables05Analytical useDimensions · measures ·decisions
  1. Industrial sources

    Quality · production · maintenance · delivery · materials

  2. Supporting routines

    Python · VBA · SQL — extraction and integration

  3. Qlik Load Script

    Mapping · joins · concatenation · filters · history

  4. Associative model

    Controlled keys · relationships across 80+ tables

  5. Analytical use

    Dimensions · measures · decisions in context

Select a stage to explore its role in the flow.

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View the Qlik Sense case

Case 04 / Audits and actions

SISVE: from audit to effectiveness assessment

I developed SISVE with Power Apps, SharePoint and automations to connect audits, actions and effectiveness assessment. Qlik Sense brings process analysis together.

16industrial processes in scope
Audit: Power Apps — structured execution → Record: SharePoint — evidence and history → Deviation: Traceable corrective action starts → Task: Planner — owners and due dates → Actions: Power Automate — notifications and integration → Assessment: Effectiveness and recurrence after action → Integrated view: Qlik Sense — analysis across 16 processes01AuditPower Apps — structuredexecution02RecordSharePoint — evidence andhistory03DeviationTraceable corrective actionstarts04TaskPlanner — owners and due dates05ActionsPower Automate — notificationsand integration06AssessmentEffectiveness and recurrenceafter actionIntegrated view — Qlik Sense — analysis across 16 processes
  1. Audit

    Power Apps — structured execution

  2. Record

    SharePoint — evidence and history

  3. Deviation

    Traceable corrective action starts

  4. Task

    Planner — owners and due dates

  5. Actions

    Power Automate — notifications and integration

  6. Assessment

    Effectiveness and recurrence after action

  7. Integrated view

    Qlik Sense — analysis across 16 processes

↺ Effectiveness and recurrence history informs subsequent audit analysis.

Select a stage to explore its role in the flow.

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View the SISVE system

Technical depth

SPC, product risk and action effectiveness

Applications of statistical analysis, Core Tools and nonconformity investigation.

Quality Engineering / SPC

A favorable Cpk does not settle the question.

Signal: apparently acceptable capability. Evidence to examine: changes in variation over time. Decision: establish process stability before interpreting capability.

I first verify whether variation remains under control over time.

Stability, capability and decision in statistical process control UCL MEAN LCL VARIATION OVER TIME

Product / process

Turn a requirement into a validation criterion.

Documented work includes experimental tests, specifications and process follow-up. APQP and PPAP participation covered specific stages, rather than ownership of the complete frameworks.

Technical requirement → test → comparison with the criterion → decision

Investigation / decision

Containing an effect does not eliminate its cause.

An occurrence requires containment; recurrence requires investigating the mechanism. Methods, owners and tests need to connect to the hypothesis being assessed.

Occurrence → hypothesis → test → action assessment

Customer Quality / decision

Response time and effectiveness answer different questions.

Response time tracks the flow of complaint handling. Effectiveness assessment examines the outcome of the action. The customer complaint case keeps these two interpretations separate.

Response → action → effectiveness → recurrence

Oracle SQL / IBM Cognos

Historical queries with Oracle SQL and IBM Cognos

Custom views, historical queries and reports were structured while respecting the performance, access and stability constraints of the existing infrastructure.

Oracle: Source and history → SQL: Adjusted view → Cognos: Analysis and access01OracleSource and history02SQLAdjusted view03CognosAnalysis and access
  1. Oracle

    Source and history

  2. SQL

    Adjusted view

  3. Cognos

    Analysis and access

Select a stage to explore its role in the flow.

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Technical toolkit

Methods and tools applied in industry

Select a method or tool to inspect its application context.

01

Quality Engineering

Requirements, prevention, investigation and effectiveness assessment.

02

Continuous Improvement and Processes

Methods for reading flow, prioritising causes and sustaining change.

03

Industrial Data and Analytics

Modelling, integration and visualisation for interpreting operations.

04

Automation and Applications

Process-adjacent solutions that reduce manual effort and improve traceability.

05

In development and personal projects

Technical exploration; not presented as consolidated professional experience.

Keep in touch

Professional contact

View my career on LinkedIn, explore projects on GitHub or contact me by email.