NotebookPipeline
Shift OEE reports on autopilot
Build the OEE analysis once in a collaborative notebook, then schedule it as a pipeline so the end-of-shift report lands with plant managers every day.
Talk to your shop floor data, build operator dashboards, track OEE and automate shift reporting — all from one platform connected to the lines, machines and systems your plant already runs on.
See how it worksAsk your machine events, OEE and downtime in plain language
From notebook to live dashboard for plant managers and line leads
Schedule shift reports, OEE rollups and downtime alerts
From asking a question to shipping an operator dashboard, MINEO covers the full journey — connected to the lines and systems your plant already runs on.
Connect any datasource — machine events, OEE, downtime logs, MES, ERP — and start asking questions in natural language. Threads auto-generates SQL, runs code, and delivers answers with interactive charts and tables. Build custom AI assistants with the model of your choice.
Threads · Plant analysis { "tool": "maximo-mcp", "action": "create_task", "summary": "Open a maintenance work order for line 07" }
via maximo-mcp · just now
More than Jupyter. MINEO Notebooks combine code, AI assistant cells, interactive widgets and visual tools in one collaborative environment. Perfect for production engineers, quality and maintenance teams — write Python, explore line data, and deploy as live apps from the same notebook.
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Compare OEE and downtime across lines and shifts.
df = mineo.query("SELECT line, AVG(oee) FROM machine_events GROUP BY line")
px.bar(df, x="line", y="oee", title="Shift OEE")
Key insight: North America drives 43% of total revenue. APAC showed the strongest growth at +23% QoQ, driven by expansion in Japan and Australia.
df.sort_values("revenue", ascending=False).head()
| Region | Revenue | Growth |
|---|---|---|
| North America | $1.8M | +12% |
| Europe | $1.1M | +8% |
| APAC | $820K | +23% |
| LATAM | $480K | -3% |
Turn notebooks into always-on dashboards and interactive applications for operators, plant managers, quality and maintenance. Deploy with Streamlit, Gradio, Dash and 6+ more frameworks. Custom domains, white-label branding and embeddable visualizations — ready for the line and the control room.
Mineo · Plant dashboard Last updated: 2 minutes ago
OEE
84%
+3% vs Q3
Throughput
12.4K
+6% vs Q3
Downtime
42 min
-8% vs Q3
| Customer | Region | Revenue | Status |
|---|---|---|---|
| Acme Corp | NA | $245K | Active |
| TechFlow GmbH | EU | $182K | Active |
| Sakura Ltd | APAC | $156K | Pending |
| DataBr SA | LATAM | $98K | Active |
A complete Linux development environment accessible from your browser. Install any package, any tool — Claude Code, Codex, Gemini CLI. Build your predictive maintenance and quality models with the libraries you trust, connect to your plant datasources and collaborate with your team. No local setup required.
VS Code — Dev Environment Explorer
import streamlit as st
from mineo import DataSource
import plotly.express as px
st.set_page_config(layout="wide")
st.title("Plant Dashboard")
ds = DataSource("plant_db")
df = ds.query("SELECT * FROM machine_events")
# Layout
col1, col2 = st.columns(2)
col1.metric("OEE", f"{df.oee.mean():.1%}")
col2.metric("Downtime", f"{df.downtime_min.sum():,} min")
# Charts
fig = px.bar(df, x="shift", y="oee", color="line")
st.plotly_chart(fig, use_container_width=True)
mineo-dev@workspace:~/project$
Successfully installed plotly-5.22 scikit-learn-1.5
Your app is live at https://plant-dashboard.mineo.app
✓ Deployed successfully
Chain notebooks into production workflows. Schedule recurring runs with cron, trigger via REST API, and monitor execution in real time. From shift rollups to downtime alerts — build reliable workflows without infrastructure overhead.
/ Projects / plants / Daily shift rollup Elements
Resource Config
Scheduling
API
The biggest unlocks come when MINEO's building blocks share the same logic — the same notebook becomes a shift pipeline, an operator dashboard, or an answer in a Threads conversation.
Build the OEE analysis once in a collaborative notebook, then schedule it as a pipeline so the end-of-shift report lands with plant managers every day.
Engineers query line performance conversationally with Threads while operators see the same numbers in an always-on Live App dashboard on the floor.
Prototype the maintenance model in a Cloud Dev Environment, refine it in a notebook with the team, and ship it as a Live App for the maintenance crew without rewriting.
Use MINEO to talk to your shop floor, build operator dashboards, track OEE and automate shift reporting — all from the same workspace.