IndustrialProcess is a set of JSON data models to communicate industrial process data. It implements the principles of Smart Data Models (associated with FIWARE) and is a part of the domain Smart Manufacturing.

The original motivation comes from the research project ALCHIMIA, where we integrated data for Digital Twins in electric steelmaking. The related processes were the Electric Arc Furnace and Ladle Furnace.

Common data models contribute to semantic interoperability. In principle, these enable an entire suite of applications. In the sections below, you can find:

• Application example: Digital Twin
• The data model
• Generic data monitoring with smart-process-industry-message-debugger

Application example: Digital Twin

For an application example, the data model originates from a Digital Twin for the Electric Arc Furnace (EAF). The EAF is a process for electric steelmaking, melting and refining scrap for subsequent processing to become new steel products again. The EAF is a perfect example for circular economy.

The figure below illustrates how the data model can deliver data to Digital Twins.

To know more about the EAF model and how it relates to the big picture, please see this presentation: https://doi.org/10.5281/zenodo.17734117

The data model

IndustrialProcess contains three data models, each agnostic of the use case:

• MaterialAddition
• ProcessChemicalAnalysis
• ProcessEvent

Below is an example of the MaterialAddition message.

{
  "id": "urn:ngsi-ld:MaterialAddition:PlantZ:UnitProcessX:75545",
  "type": "MaterialAddition",
  "dateObserved": "2025-07-17T14:07:00Z",
  "processName": "unit_process_x",
  "heatNumber": 10001,
  "addedMaterials":
  [
    {
      "code": "scrap_type_3",
      "mass": 40000,
      "category": "scrap",
      "chemicalConcentration":
      [
        {
          "substance": "Fe",
          "percentage": 0.9973
        },
        {
          "substance": "Cu",
          "percentage": 0.0005
        }
      ],
      "specificEnergy": 1.3,
      "source": "my-id-1",
      "origin": "my-id-2",
      "supplier": "ACME",
      "materialPrice": 0.02,
      "storageAvailability": 250000
    }
  ]
}

The data models are available at https://github.com/smart-data-models/dataModel.IndustrialProcess

Generic data monitoring with smart-process-industry-message-debugger

smart-process-industry-message-debugger is a generic data monitoring application built upon the IndustrialProcess data model. It integrates with Apache Kafka and expects to receive messages that contain metadata similar to the IndustrialProcess data model.

The application excels with batch processes now that the software supports the heatNumber field within the data model. Based on this field, it groups the messages into heats. This enables the application developers to easily monitor if and when the data of each heat becomes available.

The software is open source, available at https://github.com/alchimia-project/smart-process-industry-message-debugger

My roles in research and development

My roles in developing these data models in 2024-2025 were:

• The data model
  • Coordination of the development task
  • Creation of JSON schema
  • Creation of JSON examples
  • Submission process to Smart Data Models
• smart-process-industry-message-debugger
  • All development-related tasks

Related items at Kannisto.org