Module Type Package (MTP) Plug-and-Produce Automation Orchestrator using CrewAI
Process plants struggle with modular reconfiguration when integrating multi-vendor equipment without standardized Module Type Package (MTP) definitions. Build a plug-and-produce orchestrator using CrewAI to parse module descriptors, validate OPC UA interface mappings, and automate orchestration across process units.
What you are building
Build a CrewAI multi-agent team to parse MTP manifest files and orchestrate automated plug-and-produce connections between process modules.
How work is evaluated
Evaluates MTP manifest mapping completeness and generated Process Orchestration Layer bindings.
Datasets
Public datasets, plus the private datasets you have access to.
How submissions are scored
Validation Error Test
Ensures zero validation errors for compliant MTP inputs.
This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.
bound_services_ratio
Ratio of correctly bound MTP services to requested services. • target: 1 • range: 0-1
This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.
Learning goals
Define CrewAI agents (MTP Parser Agent, OPC UA Binding Agent, Operations Manager)
Automate manifest validation for VDI/VDE/NAMUR 2658 Module Type Package standards
Synthesize Process Orchestration Layer (POL) configuration outputs automatically
Resources
Sample MTP manifest files (VDI/VDE/NAMUR 2658 compliant) for dosing, mixing, and heating modular process units.
Challenge setup
Evaluates MTP manifest mapping completeness and generated Process Orchestration Layer bindings.
Challenge input
JSON containing module_id, mtp_version, services_provided
CrewAI
Offers structured multi-agent role play and tool execution.
Evaluated output
JSON with pol_bound_nodes, state_machine_status, and validation_errors
- Ensures zero validation errors for compliant MTP inputs.
- Ratio of correctly bound MTP services to requested services. • target: 1 • range: 0-1
- Benchmark: Modular Process Automation Benchmark
- Bound Services Ratio target: 1
- 1 public reference case
- Python execution harness
- Python sandbox (unavailable on Versalist)
Shows the first task, up to three tools, and up to three evidence items.
View technical recipe
Configured tools
- CrewAI · Required
- crewAI · Optional
Evaluation contract
- Validation Error Test · Weight 1
- bound_services_ratio · Weight 1
Metrics
- bound_services_ratio · Target 1
Benchmarks
- Modular Process Automation Benchmark
- general
Reference cases
- 1 public reference case
Workflow tasks
- Task 1
Input: JSON containing module_id, mtp_version, services_provided
Output: JSON with pol_bound_nodes, state_machine_status, and validation_errors
Execution harness: Python
Evaluation tools
- CrewAI · Agent Collaboration Framework
Recipe freeze marker
No recipe freeze time is recorded.