Understand the current status of all work orders, materials, and equipment
Drive impactful decisions with real-time operations data. See the status of your work orders, materials, and equipment in one place, and track KPIs while collecting feedback from operators.
Guide assembly and inspection
Error proof operations and accurately track defects in real-time with human and process data.
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Attractive user experiences
Support the frontline workforce for increased productivity
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Edge connectivity
Connect to tools, devices, and sensors for easy data capture
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Agility with no-code editing
Update work instructions on the go without any code
Gain end-to-end traceability and stay on top of the status of your orders
Ensure quality with traceable data. Track quality issues and identify root causes before products reach customers with apps, devices, sensors, and advanced computer vision.
Hit the ground running with configurable manufacturing apps and solutions in the Tulip Library.
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Dynamic Work Instructions
Guide operators through complex workflows.
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Leverage The Tulip App Suite
Build an end-to-end solution for your shop floor.
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Smart Monitoring Dashboard
Connect machines to Tulip and easily track OEE by setting the right configuration.
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Kanban System
Build a simple Kanban system for material replenishment.
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OnShape Connector
Update and pull assembly information and bill of materials from OnShape.
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Work Order Tracking
Track work orders across your facility.
Smart Levels: Four Levels of Smart Factory
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Level One: Available Data
This is likely the current status of most factories. Data is available, but not accessible. Sorting and analyzing data requires manual work and can be highly time-consuming, adding more inefficiencies to the production improvement process than intended or needed.
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Level Two: Accessible Data
At this stage, data is presented in a more digestible form. Data is structurally organized and sorted properly in one location with additional systems that help visualize data and display dashboards. The factory is able to perform proactive analysis, although this may still require some time and effort.
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Level Three: Active Data
Active data means data that can perform proactive analysis using machine learning and artificial intelligence to generate insights without much human supervision. The system can pin key issues and anomalies to predict failures with high accuracy and inform relevant people with valuable insights at the right time.
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Level Four: Action-oriented Data
At this stage, machine learning can generate actionable solutions to the issues that are identified in the earlier stages. The manufacturing machines and devices that are connected to this module or system can then execute those changes with no human intervention. Collecting data, identifying issues, and generating solutions happen in sequence with little to no human input.
Build your smart factory with Tulip today!
See how systems of apps enable agile and connected operations.