Manufacturing Material Consumption Data

This dataset provides granular, transaction-level records of material consumption across manufacturing plants, including details on material types, quantities, costs, waste, and process context. It enables manufacturers to analyze usage trends, optimize procurement, reduce waste, and improve production efficiency through actionable insights.

  • last updated 20 Aug 2025
  • by GoMask
The brief that made it

Monitor material usage trends and identify inefficiencies

Sample rows

preview · 8 of 200 rows · all 21 columns
record_idstringwaste_reasonstringwaste_generatedfloatplant_idstringplant_namestringmaterial_idstringmaterial_namestringmaterial_typestringbatch_numberstringprocess_idstringprocess_namestringconsumption_datedatequantity_consumedfloatunit_of_measurestringoperator_idstringoperator_namestringshiftstringsupplier_idstringsupplier_namestringcost_per_unitfloattotal_costfloat
MC-00001overproduction1500.85PL-101Metro SouthMT-10001Iron OrerawBN-15001PR-20001Foundry2024-06-0374500.5kgOP-350Samuel TorresmorningSUP-10051North Metals2.45182627.225
MC-00002blank0PL-102Evergreen SouthMT-10002Copper Sheetsemi-finishedBN-15002PR-20002Extrusion2024-06-042250.75kgOP-351Linda ParkeveningSUP-10052CopperWorks Inc.5.9513405.9625
MC-00003defect0.01PL-103Highland WorksMT-10003Aluminum IngotrawblankPR-20003Cutting2024-06-0562.5kgOP-352Carlos ReyesnightSUP-10053Alumax82.555159.375
MC-00004blank0PL-104Mountain PeakMT-10004Steel Barsemi-finishedBN-15003PR-20004Tempering2024-06-0645kgOP-353Anna LimorningSUP-10054SteelOne1205400
MC-00005spillage50PL-105Metro CentralMT-10005Plastic HousingfinishedBN-15004PR-20005Packaging2024-06-071200piecesOP-354Ahmed PatelnightSUP-10055Plastix0.851020
MC-00006defect3PL-106Eastern ShoreMT-10006Circuit BoardfinishedBN-15005PR-20006Inspection2024-06-08150piecesOP-355Jamie CheneveningSUP-10056CircuTech4.25637.5
MC-00007blank0PL-107Harbor EastMT-10007Epoxy Resinsemi-finishedblankPR-20007Painting2024-06-091850.25litersOP-356Emily DavismorningSUP-10057ResinPro9.818132.45
MC-00008overproduction2575.6PL-108GreenfieldMT-10008Scrap IronrawblankPR-20008Recycling2024-06-102575.6kgblankblankeveningblankblank0.0377.268

What the 200 rows show

from the 200-row sample

Overproduction (waste reason) stands out: mean waste_generated is 2,034, against 222.6 for the rest.

  • 0.02median waste_generated
  • 3material types
  • 3unit of measures
  • 3shifts
  • 9plant names
  • 14process names
Mean waste_generated by waste_reason104 rows
02,0004,000166.7defect44 rows2,034overproducti…35 rows321.0spillage25 rows
waste_generated195 rows, in bands of 500
075150147810714901,5003,000waste_generated →

Median 0.02, from 0.0 to 2,996.

plant_id200 rows · top 10 of 35 values
  1. PL-21710
  2. PL-2158
  3. PL-2168
  4. PL-1017
  5. PL-1027
  6. PL-2127
  7. PL-2187
  8. PL-1036
  9. PL-1046
  10. PL-1056
21 columns by typefrom the column list below
  • string 16
  • float 4
  • date 1

Columns

21 columns in three groups
blueprint · 21 columns
columntypedescriptionexample
Text 16 columns
record_idstringUnique identifier for each material consumption recorduniqueMC-00001
plant_idstringUnique identifier for the manufacturing plantPL-101
plant_namestringName of the manufacturing plant9 namesMetro South
material_idstringUnique identifier for the materialMT-10001
material_namestringDescriptive name of the materialIron Ore
material_typestringType or category of the material (e.g., raw, semi-finished, finished)raw · semi-finished · finishedraw
batch_numberstringBatch or lot number for traceabilityoptionalBN-15001
process_idstringUnique identifier for the production processPR-20001
process_namestringName or description of the production processFoundry
unit_of_measurestringUnit of measure for the quantity consumed (e.g., kg, liters, pieces)3 measureskg
waste_reasonstringReason for material waste (e.g., defect, spillage, overproduction)3 reasons · optionaloverproduction
operator_idstringIdentifier for the operator responsible for the processoptionalOP-350
operator_namestringName of the operator responsible for the processoptionalSamuel Torres
shiftstringProduction shift during which the material was consumed (e.g., morning, evening, night)morning · evening · night · optionalmorning
supplier_idstringUnique identifier for the material supplieroptionalSUP-10051
supplier_namestringName of the material supplieroptionalNorth Metals
Numbers 4 columns
quantity_consumedfloatAmount of material consumed (in specified units)0 or more74500.5
waste_generatedfloatAmount of material wasted during the process (in specified units)0 or more · optional1500.85
cost_per_unitfloatCost per unit of the material at the time of consumption0 or more · optional2.45
total_costfloatTotal cost of the material consumed (quantity_consumed * cost_per_unit)0 or more · optional182627.225
Dates and times 1 column
consumption_datedateDate when the material was consumed in production2024-06-03

Use it for

  • median waste g…0.02195 rowsmean waste generated …166.7defect2koverpr…321.0spilla…

    A manufacturing dashboard

    Waste_generated by waste_reason and a breakdown of plant_id. Excel, Power BI or Tableau.

  • Why do the 35 overproduction rows have a mean waste_generated of 2,034?

    A root-cause class exercise

    Hand out the rows and one question. The answer is in the data, not in the brief.

  • A software demo

    Believable records with plant_id, plant_name and material_id to fill a screen in front of a buyer.

Not quite right?

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This dataset200 rows21 columns
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blueprint · manufacturing-material-consumption-data

Behind this dataset

Same schema. As many rows as you need.

These 200 rows came out of a blueprint — 21 columns with generation rules behind each one. Open it in Data Factory to retune a column, add your own, wire in foreign keys, and run it at the size you actually need.

Rules it was built with
  • Material types and usage logged
  • Batch and production line tracked
  • Waste and scrap annotated
  • Reorder point flags included
Rows
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Exports
CSV, JSON, JSONL, Parquet, SQL, Excel, TSV, XML
Licence
yours to use, including commercially
API slug
manufacturing-material-consumption-data

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