00 / Lucas Rosate — Engineering portfolio

Quality engineering through processes, data and industrial systems.

Evidence → Analysis → Implementation → Verification

Four cases show how I mapped a cross-plant workflow, connected more than 80 operational tables, automated material traceability and linked audits to action follow-up across 16 processes.

Examine the cases

Lucas RosateQuality engineering

Selected work

Four industrial problems, their mechanisms and evidence

Each case separates context, implementation choices, technical limits and documented outcomes.

Case 01 / Customer complaints

Customer complaints: a shared investigation workflow

I mapped with the participating teams where inputs, documents and ownership were lost between plants. The redesign connected structured intake, 8D investigation, assigned tasks, due dates and adoption follow-up.

59%reduction in average response time

Structured intake
Required data · documents · source
8D investigation
Containment · cause · evidence
Actions and dates
Owners · Planner · follow-up
Adoption
Guidance · feedback · adjustments
Effectiveness
Outcome · recurrence · learning

Select a stage to explore its role in the flow.

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View the complaints workflow

Case 02 / Traceability automation

Material traceability on demand

I built a VBA routine that reads TXT and web sources, splits content into arrays, applies structuring rules and connects supply and material data to the order book for on-demand updates.

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 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 connected quality, production, maintenance, delivery and material sources in a Qlik associative model. Mapping loads, joins, concatenations, filters and key management retained history while reducing repeated consolidation.

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 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 assigned a specific role to each component: Power Apps guides audit execution; SharePoint retains records and evidence; Power Automate and Planner connect actions, owners and due dates; Qlik Sense supports analysis across 16 processes.

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 processes

↺ Effectiveness and recurrence history informs subsequent audit analysis.

Select a stage to explore its role in the flow.

← Scroll horizontally to explore the diagram →

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.

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

Technical toolkit

Methods and tools connected to the cases

Methods and tools shown in the context where they enter the workflow: investigation, data integration, routine automation and outcome verification.

Quality Engineering

Requirements, risk, cause investigation and criteria for verifying stability, capability and effectiveness.

Continuous Improvement and Processes

Workflow mapping, cause prioritisation and change follow-up through operational adoption.

Industrial Data and Analytics

Source preparation, associative modelling, history and visualisation for relating operational events.

Automation and Applications

Interfaces, routines and integrations that turn operational inputs into traceable records, tasks and outputs.

In development and personal projects

Keep in touch

Professional contact

LinkedIn presents my professional path; GitHub contains my public technical work. To discuss quality, industrial data or automation, use email.