Quality Monthly Report Generator

Problem

Quality monthly reports often rely on manual Excel cleanup, metric calculation, charting, and PDCA writing. When data is spread across multiple sheets or monthly files, gaps, inconsistent definitions, and weak trend analysis are common. This capability is for engineers who need to turn structured quality or test data into a reviewable, deliverable report.

How It Works

• Data intake: accepts multi-sheet Excel files, multiple monthly files, JSON, or manual input, and detects data types such as test cases, defects, work summaries, and PDCA.
• Metric calculation: uses parse_excel.py and metrics_calculator.py to parse, consolidate, compute single-month metrics, and compare multi-month trends to reduce manual error.
• Outline confirmation: generates a report outline first, covering sections, data sources, key metrics, and chart plans, before producing full content.
• Visual delivery: outputs one HTML file with Mermaid charts rendered as SVG, viewable in a browser and printable to PDF.

Boundaries

It works best when monthly quality data exists or can be mapped to a consistent format. It is not a substitute for missing raw data. Confirm the outline before final report generation; if fields do not match data_format.md, normalize or fill gaps first. First run may install pandas, openpyxl, and mermaid-cli, which can take a few minutes.