--- title: "Machine Monitoring Solution Architecture" slug: "machine-monitoring-solution-architecture" status: "update" updated: 2026-08-13T12:40:53Z published: 2026-08-13T12:42:46Z canonical: "support.tulip.co/machine-monitoring-solution-architecture" --- > ## Documentation Index > Fetch the complete documentation index at: https://support.tulip.co/llms.txt > Use this file to discover all available pages before exploring further. # Machine Monitoring Solution Architecture Machine monitoring connects shop floor equipment to Tulip to track real-time machine data, calculate OEE, and build human-machine workflows. As you scale from monitoring a single machine to managing a fleet, **choosing the right architecture pattern is critical** for maintainability, cost-efficiency, and performance. This guide synthesizes best practices from Tulip solution architects and customer implementations to help you design scalable, production-ready machine monitoring solutions. **In this article, you will learn:** - **Key concepts of machine monitoring components** - **Decision tree for selecting the right machine monitoring architecture** Note This article is primarily intended for solution architects, IT/OT engineers, experienced citizen developers, and technical decision-makers evaluating machine monitoring implementations. ## Machine monitoring components To understand architecture patterns, you need to know the core components of Tulip's machine monitoring system: **Machine**: A digital representation of a physical asset. Machines have **attributes** (e.g., spindle speed, temperature) that you update via OPC UA, MQTT, or the [Tulip machine attributes API](/r230/docs/use-the-machine-attributes-api). **Machine Type**: A template that defines states, attributes, and triggers for a category of similar machines (e.g., "CNC Mill" type for 5 different make/models). **Machine Attribute**: A data point from a machine (e.g., "Cycle Time", "Part Count"). Attributes can be read-only (sensor data) or writable (setpoints). **Machine Trigger**: Conditional logic that runs **headless** (without an app running) to update machine state or activity fields based on attribute changes. **Machine Activity Table**: A system table that logs machine state history, part counts, defects, and downtime reasons for OEE calculation. **Important**: This table has no Tulip Table APIs enabling real-time reads & writes. **Station**: A physical or logical location on the shop floor. You can assign machines to stations to enable "at this station" trigger logic. ### Typical enterprise-level machine connectivity architecture The architecture below is the most common for enterprise-level large-scale connectivity. ![MQTT Setup v2.svg](https://cdn.document360.io/7c6ff534-cad3-4fc8-9583-912c4016362f/Images/Documentation/MQTT%20Setup%20v2.svg) This shows how a shop floor machine would be connected to Tulip via an OT gateway with an MQTT broker, and optionally a DataOps platform. ## Select the right architecture ![Designing Machine Monitoring Solution.png](https://cdn.document360.io/7c6ff534-cad3-4fc8-9583-912c4016362f/Images/Documentation/Designing%20Machine%20Monitoring%20Solution(1).png) For more information, see: - [Headless vs. app-based architecture](/r230/docs/machine-monitoring-headless-vs-app-based-architecture) - [Machine monitoring app-based architecture patterns](/r230/docs/machine-monitoring-app-based-architecture-patterns) ## Related resources Use the links below to find relevant resources for your machine monitoring solutions. ### Knowledge Base - [Machine Monitoring](/r230/docs/machine-monitoring) - Foundational concepts and setup guide - [How to Add and Configure Machines](/r230/docs/add-and-configure-machines) - Step-by-step machine configuration - [Machine Monitoring Architecture](/r230/docs/machine-monitoring-architecture) - Network topology and IT infrastructure - [Build Your First MQTT Data Source](/r230/docs/build-your-first-mqtt-connector) - Connector setup guide - [Using Machine Data in Analytics](/r230/docs/machine-data-analysis) - Create OEE dashboards - [Automations](/r230/docs/automations-1) - Automation capabilities ### Tulip Library - [Machine Monitoring Dashboard App](https://library.tulip.co/apps/machine-monitoring-dashboard) - Pre-built dashboard template - [Machine Monitoring Terminal App](https://library.tulip.co/apps/machine-monitoring-terminal) - Operator terminal with OEE tracking - [Composable MES: Production Management Suite](https://library.tulip.co/suites/production-management) - End-to-end production apps ### Tulip University - [Machine Monitoring Fundamentals](https://university.tulip.co/learn/courses/33/machine-monitoring-in-tulip) - [How to Connect Machines to an OPC UA Server](https://university.tulip.co/learn/courses/29/how-to-connect-machines-to-an-opc-ua-server) ### API documentation - [Use the machine attributes API](/r230/docs/use-the-machine-attributes-api) - Write machine attribute values - [Table API guide](/r230/docs/table-api-guide) - Read and write Tulip Tables --- Did you find what you were looking for? You can also head to [community.tulip.co](https://community.tulip.co/?utm_source=intercom&utm_medium=article-link&utm_campaign=all) to post your question or see if others have solved a similar topic! **OEE (Overall Equipment Effectiveness)** A key performance indicator (KPI) that measures manufacturing productivity by calculating the percentage of planned production time that is truly productive. **OEE** combines three factors: **Availability** (uptime), **Performance** (speed), and **Quality** (good parts produced). **Formula:** OEE = Availability × Performance × Quality **Scale:** Expressed as a percentage, where 100% represents perfect production (manufacturing only good parts, as fast as possible, with no downtime). **OPC-UA** **OPC Unified Architecture** is a cross-platform, open-source, IEC62541 standard for data exchange from sensors to cloud applications developed by the OPC Foundation. **MQTT (Message Queuing Telemetry Transport)** A lightweight publish/subscribe messaging protocol designed for constrained devices and low-bandwidth, high-latency networks, widely used in IIoT applications. **DataOps platforms** DataOps refers to integrated software solutions that streamline the collection, transformation, contextualization, and delivery of industrial data across operational technology (OT) and information technology (IT) systems. Key characteristics: - Edge-to-cloud data pipeline management: Orchestrate data flow from factory floor devices to enterprise systems and cloud platforms - Protocol translation: Convert between industrial protocols (Modbus, OPC-UA, Ethernet/IP) and modern IT standards (REST APIs, MQTT) - Real-time data processing: Apply filtering, aggregation, and transformation at the edge to reduce bandwidth and latency - Contextualization: Add metadata and business context to raw sensor data for meaningful analysis