IBM/AssetOpsBench

Health v2 · maintenance only

Flags: no_releases

Adoption not part of the score

2237 stars · 319 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

AssetOpsBench is an open-source benchmark and framework from IBM for building, orchestrating, and evaluating domain-specific AI agents for Industry 4.0 asset operations and maintenance. It ships 460+ scenarios across 9 asset classes, five specialist agents (IoT, FMSR, TSFM, Work Order, etc.), and multi-agent orchestration blueprints (MetaAgent, AgentHive) built over the Model Context Protocol.

Use cases

• benchmark LLM agents on industrial asset maintenance tasks
• build domain-specific AI agents for predictive maintenance
• evaluate multi-agent orchestration for IoT and work order management
• run condition-based maintenance scenarios for HVAC and industrial equipment
• prototype MCP-based agent servers for Industry 4.0 workflows
• compare foundation models on time-series forecasting for asset operations

When to choose

• you need a standardized benchmark for industrial AI agents
• you are building multi-agent systems over MCP for asset operations
• you want ready-made scenarios and datasets for predictive maintenance research
• you need orchestration blueprints for domain-specific agents

When to avoid

• you need a production CMMS or EAM system rather than a research benchmark
• your domain is unrelated to industrial asset operations
• you want a no-code agent builder with a polished UI

Facets

framework · maturity active

agent-framework benchmarking mcp machine-learning llm-inference rag artificial-intelligence iot large-language-models python windows industry-4-0 predictive-maintenance time-series-forecasting condition-based-maintenance multi-agent-orchestration hvac-maintenance asset-operations benchmark-dataset ai-agents industrial-automation linux macos docker

Member repositories

For agents

markdown · JSON · MCP: product_card(name="IBM/AssetOpsBench")