Open-source repositories for manufacturing teams, from the MES connector to maintenance and analytics.
Pick your assistant, copy the prompt and paste it into Claude, ChatGPT, Gemini or Grok.
Claude
Read https://automotivecloudwatch.com/repositories/manufacturing.md and map it to my team. Ask me up to four short questions first: my team, my program and its stage, what we already run, and any hard constraints. Then give me one written assessment: a short summary, three maps (already running, not running yet, still done by hand), the top 10 repositories rated for impact and effort, a setup check, and a 30-day plan that starts with the one repository to try today.ChatGPT
Open https://automotivecloudwatch.com/repositories/manufacturing.md with your browsing tool and read all of it, then map it to my team. Ask me up to four short questions first: my team, my program and its stage, what we already run, and any hard constraints. Then give me one written assessment: a short summary, three maps (already running, not running yet, still done by hand), the top 10 repositories rated for impact and effort, a setup check, and a 30-day plan that starts with the one repository to try today. If browsing is off or the link will not open, tell me and I will paste the file.Gemini
Read https://automotivecloudwatch.com/repositories/manufacturing.md and map it to my team. If you cannot open the link, tell me and I will paste the file. Ask me up to four short questions first: my team, my program and its stage, what we already run, and any hard constraints. Then give me one written assessment: a short summary, three maps (already running, not running yet, still done by hand), the top 10 repositories rated for impact and effort, a setup check, and a 30-day plan that starts with the one repository to try today.Grok
Fetch and read https://automotivecloudwatch.com/repositories/manufacturing.md, then map it to my team. If you cannot open the link, say so and I will paste the file. Ask me up to four short questions first: my team, my program and its stage, what we already run, and any hard constraints. Then give me one written assessment: a short summary, three maps (already running, not running yet, still done by hand), the top 10 repositories rated for impact and effort, a setup check, and a 30-day plan that starts with the one repository to try today.You get a written assessment of your team: a short summary, three maps of what you run, what you lack and what you still do by hand, the top 10 repositories rated for impact and effort, a setup check and a 30-day plan.
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Plain text for an assistant: /repositories/manufacturing.md /repositories/manufacturing.json
Edition 1, checked 2026-10-19
Somewhere in most plants, an engineer is quietly rebuilding something that already exists as open source. Sometimes it is a connector between the PLC layer and the MES. Sometimes it is a time series anomaly check, a vision inspection pipeline or a scheduling model in a spreadsheet. The work is real and it is usually good, and it is rarely the best use of that engineer's year.
Open source on the plant floor carries its own questions about validation, change control and who supports it at three in the morning. The library does not answer those for you. It does make sure your team is asking them about the right projects.
Edition 1, checked 2026-10-19, lists 41 repositories across 8 teams. By level that is 13 Start here, 22 Practitioner, 6 Deep end.
Manufacturing Execution and Integration has the most entries, 6; 7 teams have the fewest, 5 each. 15 entries carry a license flag (weak or strong copyleft, a non-standard license or no license detected), so read the license before you plan around them. Last activity runs from 2026-07-06 to 2026-10-19, as checked on 2026-10-19.
This is the first edition, so nothing has moved yet.
Manufacturing Execution and Integration 6 Industrial IoT and Edge 5 Controls and Automation 5 Digital Twin and Simulation 5 Quality and Vision Inspection 5 Maintenance and Reliability 5 Planning, Scheduling and Optimization 5 Industrial Data and Analytics 5
Own the MES layer and the ISA-95 integration between shop floor and enterprise systems, using OPC UA, MQTT, Sparkplug and a Unified Namespace.
6 repositories
An open C implementation of OPC UA client and server, including PubSub, that compiles down to embedded targets.
Use it when you need to put an OPC UA server on a machine controller or gateway without a commercial SDK.
The OPC Foundation's official .NET reference stack for OPC UA clients, servers and PubSub.
It is the reference to test against when interoperability questions come up, and it is the natural choice for Windows and .NET based plant software.
The source of the Sparkplug specification and its compatibility test kit, which define topic structure, payloads and state handling for industrial MQTT.
Read it before building a Unified Namespace on MQTT, since Sparkplug is a widely used contract between devices, brokers and SCADA, and the specification is still maintained.
A small, widely deployed open MQTT broker and client library from the Eclipse Foundation.
It is the simplest broker to stand up for a pilot line or test bench before choosing a clustered broker for production.
An open platform from UMH that packages connectivity, a Unified Namespace and data storage into a deployable stack for factories.
Study it as a working example of how a Unified Namespace architecture is assembled from open components.
An open MES and production management system covering orders, technologies, material flow and shop floor tracking for small and mid-size plants.
Use it to see the data model of a working MES and to prototype order and routing flows before selecting a commercial system.
Own edge gateways and connectivity that collect data from PLCs, sensors and machines and move it to plant and cloud systems.
5 repositories
A flow-based, browser-edited programming tool for wiring together devices, protocols and services, widely used on industrial edge gateways.
It is the fastest way to prototype a machine data integration, and many industrial edge products ship it built in.
An Apache library that gives one API for talking to PLCs over protocols such as S7, Modbus, EtherNet/IP, ADS and OPC UA.
Reach for it when you need to read data from a mixed fleet of controllers without writing a driver for each protocol.
An industrial protocol gateway from EMQ that converts device protocols into MQTT for edge and cloud systems.
Evaluate it for lightweight edge connectivity, noting that the open edition includes only a subset of drivers such as Modbus and MQTT.
The core services of EdgeX Foundry, a vendor-neutral Linux Foundation edge platform built from microservices.
Look at it when you need a reference architecture for device services, data normalization and edge rules in one framework.
A plugin-driven agent for collecting and shipping metrics, with inputs for OPC UA, Modbus, MQTT and many other sources.
It is a low-effort way to get machine and infrastructure data into a time series database without custom collectors.
Own PLC and motion control logic, IEC 61131-3 and IEC 61499 programming and the open runtimes and engineering tools that execute it.
5 repositories
Version 4 of the OpenPLC runtime, which executes IEC 61131-3 programs on standard hardware and is managed from the OpenPLC Editor.
Use it for training, test benches and low-risk control tasks, and note that it replaces the archived OpenPLC_v3 repository.
An open IEC 61131-3 integrated development environment with a code generator and runtime for programming controllers.
It is the most complete open environment for learning structured text, ladder and function block programming end to end.
The Eclipse 4diac engineering environment for building distributed control applications with IEC 61499 function blocks.
Use it to explore IEC 61499, the event-driven and hardware-independent model behind several software-defined automation efforts.
The 4diac runtime that executes IEC 61499 applications on embedded devices and PCs.
Pair it with 4diac IDE to deploy and test distributed control logic across several devices.
A long-running open CNC and motion controller for mills, lathes, robots and other machines, running on real-time Linux.
It is a working reference for real-time motion control, trajectory planning and hardware abstraction in machine tools.
Own the digital representations of assets and processes, including Asset Administration Shells, twin platforms and physical system models.
5 repositories
Eclipse BaSyx server components in Java for hosting Asset Administration Shells, submodels and registries.
Use it to stand up AAS infrastructure for a pilot, since the AAS is the Industrie 4.0 and Catena-X standard for describing assets.
A Python SDK for creating, reading and serializing Asset Administration Shell models.
Reach for it to script AAS generation from engineering data or to validate shells received from suppliers.
A desktop viewer and editor for AASX packages, the file format of the Asset Administration Shell.
It is the easiest way to open and inspect a digital nameplate or AAS package, and it replaces the archived admin-shell-io version.
An Eclipse framework for managing digital twins of devices as live state with APIs, search and change notifications.
Consider it when you need a scalable backend that keeps a current state of many assets and exposes it to applications.
An open environment for modeling and simulating physical systems in the Modelica language, with FMI export.
Use it to build physics-based models of machines and processes, under the OSMC public license, which allows GPL or EPL style use.
Own automated visual inspection, from image processing and defect detection models to labeling the data those models need.
5 repositories
The standard open computer vision library for image processing, camera calibration and classic machine vision.
Most inspection pipelines still rely on it for preprocessing, measurement and calibration around any learned model.
An Intel-led library of visual anomaly detection models that learn from good parts only.
It suits defect inspection where bad samples are rare, which is the usual situation on a production line.
The library behind the recent YOLO object detection and segmentation models, with training and export tools.
Use it for fast detection prototypes, and check the AGPL license or buy a commercial license before shipping it in a product.
An open data labeling tool for images, video, text and time series with configurable annotation interfaces.
Labeled defect data is usually the bottleneck in vision inspection, and this is a practical way to organize that work in house.
A Python toolkit of reusable building blocks for detection results, such as tracking, zone counting and annotation.
It saves time when turning raw model detections into line metrics like counts, dwell time and zone violations.
Own predictive maintenance and asset health, including time series anomaly detection, forecasting and the maintenance work order system.
5 repositories
A Python library that offers dozens of outlier and anomaly detection algorithms behind one consistent API.
Use it to benchmark several anomaly detectors on sensor data quickly before committing to one.
A library for computing the matrix profile, which finds repeated patterns and anomalies in long time series.
It is a strong, explainable choice for spotting unusual cycles in vibration, current or pressure signals without labeled failures.
A Python package that automatically extracts and filters hundreds of features from time series.
Use it to turn raw machine signals into features for remaining useful life or fault classification models.
A Python library for forecasting and anomaly detection on time series, from classical models to deep learning.
It gives one interface for comparing many forecasting and detection methods on equipment and process data.
Atlas CMMS, an open maintenance management system for work orders, preventive maintenance, assets and spare parts.
It is useful to see how condition alerts can turn into scheduled work, or to run maintenance for a smaller site.
Own production planning, scheduling and resource optimization, from mathematical solvers to the ERP and MRP data they act on.
5 repositories
Google's optimization suite with constraint programming, routing, linear and mixed integer solvers.
Its CP-SAT solver is a strong default for job shop scheduling, sequencing and line balancing problems.
A Java and Kotlin planning engine, continued from OptaPlanner, for scheduling and resource allocation with constraint scoring.
Use it when planners need explainable schedules built from business rules such as shifts, skills and maintenance windows.
A Python modeling language for linear, mixed integer and nonlinear optimization that works with many solvers.
Reach for it when you need to express a custom production planning model clearly and swap solvers underneath.
A high-performance open solver for linear, mixed integer and quadratic programming.
It is a capable free solver to pair with Pyomo or other modeling tools before paying for a commercial solver.
An open ERP system with manufacturing modules for bills of materials, work orders, production planning and inventory.
Study it to understand the ERP and MRP data that scheduling and MES systems depend on, or to run planning at a small manufacturer.
Own historians, time series databases, stream analytics and dashboards that turn plant data into decisions.
5 repositories
An Apache time series database designed for industrial IoT, with a tree-shaped data model for devices and measurements.
Consider it as an open historian alternative when you have very many sensors and need high write rates and compression.
A PostgreSQL extension that adds time series storage, compression and continuous aggregates.
It lets plant data live next to relational context in SQL, and note that some features fall under the Timescale License rather than Apache-2.0.
A column-oriented time series database with SQL, built for fast ingestion and queries.
Evaluate it when query speed over high-frequency sensor data is the main requirement.
An Apache toolbox for industrial IoT that connects to machine protocols, processes data streams and builds dashboards without much code.
It suits plant teams who want self-service stream analytics on shop floor data without a large data engineering group.
A widely used dashboard and observability tool that visualizes data from time series databases, SQL and many other sources.
It is the usual front end for plant KPIs and machine monitoring built on open historians.
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The other libraries: Automotive Robotics and Physical AI All repositories