This section explores how workflow management applies to physical robotics operations - focusing on the real challenges organizations face when coordinating robot systems with human teams.
Industrial and commercial robots operate using proprietary control systems and communication protocols. Connecting these systems to broader business workflows requires middleware, protocol translation, and careful architecture planning.
Industrial standard used by major robot manufacturers (ABB, KUKA, FANUC, Siemens). Provides secure, reliable machine-to-machine communication with built-in data modeling and service-oriented architecture.
Open-source robotics middleware widely used in research and development. ROS2 uses DDS (Data Distribution Service) for real-time communication between nodes. Common in academic settings and newer collaborative robots.
Lightweight publish-subscribe protocol designed for IoT devices. Used for robot telemetry and event-driven communication. Lower bandwidth requirements than OPC UA.
Many robot manufacturers use proprietary communication methods requiring vendor-specific SDKs or edge devices for translation to standard protocols.
Robot systems typically require network segregation between operational technology (OT) and information technology (IT) networks. Integration points usually occur through:
When connecting robots to external systems:
Modern industrial environments increasingly combine automated and manual work. Managing these mixed workflows requires coordination between robot control systems and human task management.
Assembly operations - Robots handle heavy lifting and precise positioning while humans manage delicate components requiring dexterity.
Quality inspection - Automated measurement systems perform initial checks, routing exceptions to human inspectors for review.
Maintenance workflows - Diagnostic routines generate data that maintenance teams use for troubleshooting and repair.
Industrial robot deployments must follow relevant safety standards:
Documentation and audit trails help demonstrate compliance during safety assessments.
When planning robot-workflow integration:
Robotics workflow management applies across various sectors:
Automotive assembly, electronics production, material handling, CNC coordination, quality inspection systems
Autonomous mobile robots (AMRs), automated guided vehicles (AGVs), picking and packing systems, inventory management
Laboratory automation, pharmacy dispensing, sample tracking, diagnostic equipment coordination
Packaging lines, batch processing, cleanroom operations, quality control systems
Protocol complexity - Translating between industrial protocols and business systems requires specialized middleware and expertise.
Network security - Maintaining proper OT/IT segregation while enabling data flow.
Latency sensitivity - Real-time robot control versus asynchronous workflow updates require different architectural approaches.
Legacy systems - Older robot controllers may lack modern connectivity options.
Vendor lock-in - Proprietary systems can limit integration flexibility.
Organizations managing robot fleets face challenges in:
This section includes vendor-specific documentation exploring workflow management considerations for different robot platforms:
Note: These resources explore potential integration patterns and workflow management challenges. Specific implementation details depend on individual organizational requirements, robot configurations, and network architecture.
Information currency: This documentation provides general information about robotics workflow integration concepts and challenges. The robotics industry evolves rapidly, with frequent changes in:
Verification required: Before making any technical or business decisions:
No guarantees: This documentation does not constitute:
Contact Tallyfy support to discuss your specific robotics integration requirements and current capabilities.
Robotics > KUKA Robotics integration
Robotics > Universal Robots integration
Robotics > Unitree Robotics integration
Robotics > AppTronik Apollo integration