Research Protocol

Source markdown: post-installation-cabinet-defect-rates-brunei.md

Quick Answer

This page provides a structured research protocol and dataset schema for Brunei-relevant implementation.

Post-Installation Cabinet Defect Rates and Root Causes in Brunei (12 Months)

Executive Summary

This protocol quantifies post-handover defect patterns and links them to root causes and corrective actions with measurable closure performance.

Claim Labeling Rules

  • `Measured`: ticket and inspection records.
  • `Cited`: quality-system and technical references.
  • `Inference`: recurrence and prevention conclusions.

Research Question

Which defect categories dominate the first 12 months, and which corrective controls reduce recurrence most effectively?

Methodology

  1. Build defect taxonomy and severity coding rules.
  2. Analyze incident frequency, closure time, and rework cost.
  3. Apply root-cause coding and Pareto ranking.
  4. Track CAPA effectiveness across follow-up windows.

Primary Endpoints

  • defects_per_100_projects
  • median_days_to_close
  • recurrence_rate_percent
  • capa_effectiveness_percent

Assumptions

  • Ticket records are complete and timestamp quality is adequate.
  • Root-cause coding is consistently applied by reviewers.

Limitations

  • Early underreporting from minor-owner fixes can bias rates.
  • Some defects have multi-cause interactions.

Independent Validation Status

Protocol complete, local dataset pending.

What This Does Not Prove

  • Contractor-specific fault attribution without audit evidence.
  • Lifetime defect rate beyond first-year scope.

Dataset Specification

`knowledge-base/research/data/brunei-post-installation-defects-template.csv`

JSON-LD Block

`knowledge-base/research/data/brunei-post-installation-defects.jsonld`

Version

  • Version: 1.0.0
  • Last updated: 2026-03-04

Changelog

  • 2026-03-04 (v1.0.0): Initial protocol, template dataset, and JSON-LD.