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Overview

This repository contains a Streamlit prototype that demonstrates how the TLS facility concept team might explore flow, waste, and improvement ideas in one place. The refreshed dashboard keeps a running history of every calculation or observation so data can be revisited during daily huddles or leadership reviews.

The app bundles four lightweight tools:

  • Takt time planner – Capture named scenarios, compare takt time versus cycle time, and review historical calculations on an interactive chart.
  • Waste observation log – Record detailed gemba notes (area, shift, counts) and instantly see aggregated charts with the latest entries.
  • Kaizen planner – Build an improvement backlog with due dates, status tracking, and leverage scoring cues to highlight quick wins.
  • AR HUD concepts – Explore heads-up display overlays for Flow Driver shuttles, PPO installs, and FQA final assurance to brief experience designers.

Use the dashboard as a starting point for discussions about your own production system and as a sandbox for future TLS experiments.

Plan the next iteration

Review the project roadmap for a curated list of high-value improvements to implement next—covering data persistence, deeper analytics, AR prototyping support, operational readiness, and research activities. Update it as milestones are completed so the team stays aligned on what to push to the repository next.

Getting started

  1. Install dependencies
    pip install -r requirements.txt
  2. Launch the Streamlit dashboard
    streamlit run app.py
  3. Open the URL printed in the terminal (typically http://localhost:8501) to explore the TLS concept modules.

Explore the design blueprint

The docs/ directory contains the UI/UX architecture that guides the Streamlit implementation. Use it as a reference when extending the dashboard or collaborating with designers:

Feel free to fork this repository and adapt the calculators, data models, or styling to suit your team's workflows. Contributions that add additional documentation artefacts (wireframes, research insights, deployment runbooks) are welcome.

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