bottleneck-analysis

Draw your factory. Press play. Watch the bottleneck appear. A free, zero-install digital twin studio for production lines — runs entirely in your browser.

Bottleneck-analysis tool for a serial production line: load your measured cycle times, validate the model against real output, and quantify the ROI of fixing the constraint.

LLM capacity-planning copilot for chip validation labs in Python: NL query -> SimPy discrete-event simulation -> sensitivity diagnosis; Anthropic API with deterministic fallback, FastAPI service, Monte-Carlo bottleneck analysis, Docker + GitHub Actions CI; 27/27 pytest passing; synthetic-data limits disclosed.

PuffLine Planner：电子烟产线仿真与人力规划工具。支持烟弹/烟油/尼古丁袋产线仿真、瓶颈与 WIP 分析、人力需求预估、排班成本与智能优化，面向 IE 工程师、产线经理、HRBP 与供应链从业者。Production line simulation & manpower planning for e-cigarette, e-liquid and nicotine pouch manufacturing — SimPy + Python + Tkinter。

Discrete-event simulation of multi-stage operational workflows using SimPy. Identify bottleneck nodes, model queue buildup, and test capacity changes before they hit production.

Customer-support operations control tower: process mining, SLA bottleneck detection, and capacity forecasting on 250K+ workflow events across 50K cases. Airflow + dbt + DuckDB + Pandas + 6-page Streamlit dashboard.

An advanced Python profiling and performance analysis toolkit that unifies timing, resource monitoring, line-by-line profiling, flame graphs, call graphs, memory leak detection, async/thread analysis, live dashboards, and intelligent optimization suggestions in one extensible platform.

Dependency-light OEE and bottleneck analysis for manufacturing event logs.

Análise de processos produtivos com Python, métricas de fluxo, exceções e identificação de gargalos.

A.F.O artifact for bridge-sensitive bottleneck attribution and control in hierarchical LLM memory paths (gem5-based reproducibility bundle).

Interactive browser simulator for exploring how AI capability growth becomes real-economy output, or fails under physical and institutional bottlenecks.

Evidence-bound workflow diagnostics and certified lower-bound reporting for long-running AI agent pipelines. Improve agent workflow throughput without changing the model.