{
  "format": "dataset-manifest/1",
  "slug": "3d-printing-preparation-software",
  "version": 3,
  "seed": "3d-printing-preparation-software:1",
  "spec": {
    "format": "dataset/1",
    "slug": "3d-printing-preparation-software",
    "name": "3D Printing Operations Data",
    "tagline": "Operations data from 3D printers, including types, filaments, slicing settings, and job histories.",
    "description": "Printers churn out 3D models, utilizing various filaments and optimized slicing settings to transform digital designs into tangible objects. Each printer type is unique, equipped with specific nozzle configurations and firmware that contribute to the quality and precision of the print jobs. Filaments of differing properties fuel these machines, varying from common thermoplastics to niche materials that yield special characteristics in the final product. Users manage multiple workspaces to oversee the production process, tracking the history of jobs completed and materials consumed.\n\nA row in the printers table represents a different 3D printer, detailing its model, type, and specifications, while the filaments table lists the various materials available for printing. The slicing_settings table captures the parameters for how designs are translated into instructions for the printer, including layer height, speed, and temperature settings. Jobs are recorded in the jobs table, documenting individual printing tasks along with their outcomes, and the relationships between different jobs and workspaces are established in the workspace_jobs table. Each workspace serves as a hub for the jobs executed, linking individual print tasks to the specific environment in which they were conducted.\n\nThis dataset allows users to explore questions like: How do different slicing settings affect print quality? What is the efficiency of various filament types in relation to specific printer models? How do job success rates vary across different workspaces? It is particularly useful for practicing data analysis in the realm of IoT and manufacturing, enabling users to draw insights from the intricacies of 3D printing operations. The data is synthetic, representing a simulated environment to provide a safe space for experimentation and skill development.",
    "domain": "iot",
    "shape": "multi-tenant",
    "useCases": [
      "orm-seeding",
      "api-mocking"
    ],
    "keywords": [
      "3D printing",
      "filament",
      "printer settings",
      "job history",
      "workspace management",
      "slicing",
      "firmware",
      "nozzle specifics"
    ],
    "locale": "en",
    "license": "CC0-1.0",
    "version": 1,
    "tables": {
      "printers": {
        "description": "This table lists different 3D printers, each identified by a unique ID. Each printer has specific attributes such as type, manufacturer, and firmware version.",
        "rows": 100,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each printer."
          },
          "printer_type": {
            "kind": "enum",
            "values": [
              "FDM",
              "SLA",
              "SLS"
            ],
            "description": "Type of 3D printer.",
            "weights": [
              8,
              2,
              1
            ]
          },
          "manufacturer": {
            "kind": "words",
            "min": 1,
            "max": 2,
            "description": "Name of the printer's manufacturer.",
            "pool": [
              "MakerBot",
              "Ultimaker",
              "Prusa",
              "Creality",
              "Anycubic",
              "Raise3D",
              "Formlabs",
              "FlashForge",
              "Monoprice",
              "LulzBot",
              "XYZprinting",
              "Sculpto",
              "Zortrax",
              "Dremel",
              "Snapmaker",
              "BCN3D",
              "Artillery",
              "Elegoo",
              "Wanhao",
              "Tiertime"
            ]
          },
          "firmware_version": {
            "kind": "words",
            "min": 1,
            "max": 3,
            "description": "Version of the printer's firmware.",
            "pool": [
              "1.0.0",
              "2.1.3",
              "3.2.1",
              "4.0.0",
              "5.1.2",
              "6.3.4",
              "7.2.0",
              "8.1.1",
              "9.0.5",
              "10.2.0",
              "11.1.4",
              "12.0.0",
              "13.3.2",
              "14.2.1",
              "15.0.1",
              "16.4.3",
              "17.1.0",
              "18.0.0",
              "19.2.1",
              "20.3.5"
            ]
          }
        }
      },
      "filaments": {
        "description": "This table contains various filament types used in 3D printing, linked to printers. Each filament has properties like material type and diameter.",
        "rows": 150,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each filament."
          },
          "material_type": {
            "kind": "enum",
            "values": [
              "PLA",
              "ABS",
              "PETG",
              "TPU"
            ],
            "description": "Type of filament material.",
            "weights": [
              5,
              3,
              2,
              1
            ]
          },
          "diameter": {
            "kind": "decimal",
            "min": 1.5,
            "max": 3,
            "scale": 1,
            "description": "Diameter of the filament in mm."
          },
          "printer_id": {
            "kind": "fk",
            "ref": "printers.id",
            "description": "ID of the printer using this filament."
          }
        }
      },
      "slicing_settings": {
        "description": "This table holds settings for slicing 3D models, which determine print quality and performance. Each setting is associated with a specific printer and filament.",
        "rows": 120,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each slicing setting."
          },
          "layer_height": {
            "kind": "decimal",
            "min": 0.1,
            "max": 1,
            "scale": 2,
            "description": "Layer height in mm for slicing."
          },
          "print_speed": {
            "kind": "int",
            "min": 20,
            "max": 200,
            "description": "Speed of the printer in mm/s."
          },
          "filament_id": {
            "kind": "fk",
            "ref": "filaments.id",
            "description": "ID of the filament used for slicing."
          },
          "printer_id": {
            "kind": "fk",
            "ref": "printers.id",
            "description": "ID of the printer using these settings."
          }
        }
      },
      "jobs": {
        "description": "This table tracks individual 3D printing jobs, linking each job to the specific printer, filament, and slicing settings used.",
        "rows": 300,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each job."
          },
          "status": {
            "kind": "enum",
            "values": [
              "pending",
              "in_progress",
              "completed",
              "failed"
            ],
            "description": "Current status of the printing job.",
            "weights": [
              1,
              3,
              5,
              1
            ]
          },
          "start_time": {
            "kind": "datetime",
            "from": "2023-01-01",
            "to": "2023-12-31",
            "description": "Start time of the printing job.",
            "dayProfile": "business"
          },
          "end_time": {
            "kind": "datetime",
            "after": "start_time",
            "withinDays": 30,
            "description": "End time of the printing job."
          },
          "slicing_id": {
            "kind": "fk",
            "ref": "slicing_settings.id",
            "description": "ID of the slicing settings used for this job."
          }
        }
      },
      "workspaces": {
        "description": "This table represents different user workspaces, where various jobs and materials are managed. Each workspace can have multiple jobs associated with it.",
        "rows": 50,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each workspace."
          },
          "name": {
            "kind": "words",
            "min": 1,
            "max": 3,
            "description": "Name of the workspace.",
            "pool": [
              "Workshop",
              "Studio",
              "Lab",
              "DesignSpace",
              "PrintHub",
              "CreationStation",
              "InnovationLab",
              "PrototypeArea",
              "MakerSpace",
              "CraftRoom",
              "TechZone",
              "FabricationBay",
              "ModelingRoom",
              "AssemblyArea",
              "ResearchLab",
              "DevelopmentZone",
              "PrintRoom",
              "ExperimentSpace",
              "CollaborationHub",
              "EngineeringSuite"
            ]
          },
          "owner": {
            "kind": "fullName",
            "description": "Name of the owner of the workspace."
          }
        }
      },
      "workspace_jobs": {
        "description": "This associative table links workspaces to the jobs they manage, allowing for tracking of job history within specific work environments.",
        "rows": 300,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each workspace-job link."
          },
          "workspace_id": {
            "kind": "fk",
            "ref": "workspaces.id",
            "description": "ID of the workspace managing the job."
          },
          "job_id": {
            "kind": "fk",
            "ref": "jobs.id",
            "description": "ID of the job associated with the workspace."
          }
        }
      }
    },
    "structure": "multi-table",
    "traits": [
      "high-cardinality",
      "timestamped",
      "categorical"
    ],
    "analysisQuestions": [
      "What are the most common filament types used in printing jobs?",
      "How do different slicing settings affect job success rates?",
      "Which printers have the highest job completion rates?",
      "What trends can be observed in workspace job management over time?"
    ],
    "suggestedQueries": [
      {
        "title": "Get all jobs for a specific printer",
        "sql": "SELECT * FROM jobs WHERE jobs.printer_id = 1;",
        "dialect": "postgres"
      },
      {
        "title": "Count jobs by status",
        "sql": "SELECT status, COUNT(*) FROM jobs GROUP BY status;",
        "dialect": "postgres"
      },
      {
        "title": "Average print speed by filament type",
        "sql": "SELECT filaments.material_type, AVG(slicing_settings.print_speed) FROM slicing_settings JOIN filaments ON slicing_settings.filament_id = filaments.id GROUP BY filaments.material_type;",
        "dialect": "postgres"
      },
      {
        "title": "Find the latest job for each printer",
        "sql": "SELECT printer_id, MAX(end_time) FROM jobs GROUP BY printer_id;",
        "dialect": "postgres"
      }
    ],
    "usageScenarios": [
      {
        "title": "3D Printing Developers",
        "body": "Developers working on 3D printing applications can utilize this dataset to simulate and test their software against various printer configurations, ensuring compatibility and performance across different machines and filament types."
      },
      {
        "title": "Data Analysts in Manufacturing",
        "body": "Data analysts can leverage this dataset to derive insights about printing efficiency, material usage trends, and job performance metrics, aiding in the optimization of production processes and resource allocation."
      },
      {
        "title": "Educational Institutions",
        "body": "Educational institutions can use this dataset to teach students about data management and analysis in the context of IoT devices, specifically focusing on 3D printing technology and its operational metrics."
      },
      {
        "title": "API Developers",
        "body": "API developers can mock their services using this dataset, creating realistic endpoints for job management, workspace tracking, and filament inventory, helping to streamline the development process."
      }
    ]
  },
  "counts": {
    "printers": 100,
    "filaments": 150,
    "slicing_settings": 120,
    "jobs": 300,
    "workspaces": 50,
    "workspace_jobs": 300
  },
  "stats": {
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