Manufacturing Plant Supply Chain Bottlenecks

This dataset provides detailed records of supply chain bottlenecks within manufacturing plants, including workflow stages, root causes, impact severity, recurrence, and resolution actions. It enables operational managers to visualize interruptions, analyze trends, and optimize throughput by identifying and resolving recurring issues. The data supports efficiency improvement, risk mitigation, and strategic decision-making in manufacturing operations.

  • last updated 28 Oct 2025
  • by GoMask
The brief that made it

Identifying and resolving recurring supply chain bottlenecks

Sample rows

preview · 8 of 96 rows · all 27 columns
bottleneck_idstringworkflow_stagestringduration_hoursfloatrecurrence_flagbooleanplant_location_streetstringplant_idstringplant_namestringplant_location_citystringplant_location_statestringplant_location_postal_codestringplant_location_countrystringbottleneck_typestringdate_detecteddatedate_resolveddateroot_cause_categorystringimpact_severityintegeraffected_product_idstringaffected_product_namestringresolution_actionstringresolved_bystringrecurrence_countintegerthroughput_loss_unitsfloatfinancial_impact_usdfloatmanager_idstringmanager_namestringbottleneck_descriptionstringroot_cause_detailsstring
BNK_100001production5false1200 Industrial BlvdPLT_A01Central ManufacturingClevelandOH44115USAequipment-failure2024-03-042024-03-04equipment-maintenance3PRD_001HVAC CompressorEmergency repair and revised maintenance schedule.MGR_10102309200.75MGR_101Laura SimmonsUnexpected breakdown of assembly line conveyor halted operations for 5 hours.Conveyor motor had not received scheduled maintenance.
BNK_100002procurement36true88 Lakeview DrPLT_A02Lakeview AssemblyBuffaloNY14206USAmaterial-shortage2024-02-282024-03-01supplier-issue4PRD_002Window FrameExpedited alternate supplier delivery.MGR_102289037270MGR_102Daniel OrtizShortage of aluminum sheets delayed start of production.Supplier shipment delayed due to severe weather.
BNK_100003quality-control47false3548 Route 20PLT_A03Midwest FabricationAuroraIL60505USAquality-issue2024-02-152024-02-17process-design2PRD_003Steel BracketCalibration protocol updated.MGR_10301506400MGR_103Priya DesaiHigh defect rate detected in batch, requiring reinspection and rework.Insufficient calibration on testing equipment.
BNK_100004packaging12true401 Pioneer RdPLT_A04Pioneer PlasticsGreensboroNC27407USAlabor-shortage2024-01-232024-01-24workforce2PRD_004Plastic CasingTemporary staffing agency contracted.MGR_104331010980MGR_104Michael ChuInsufficient shift coverage caused backlog in packaging department.Multiple employees out sick during flu season.
BNK_100005shipping26false200 Atlantic AvePLT_A05Atlantic ComponentsBostonMA02110USAlogistics-issue2024-03-112024-03-12external-factor3PRD_005Control PanelAlternate carrier engaged for urgent shipments.MGR_10501207800MGR_105Sophie HernandezCarrier truck breakdown delayed outbound shipments.Third-party logistics provider reported vehicle failure.
BNK_100006inventory18false1200 Industrial BlvdPLT_A01Central ManufacturingClevelandOH44115USAprocess-delay2024-01-122024-01-13process-design1PRD_006Circuit BoardConducted staff training.MGR_1010602200MGR_101Laura SimmonsInventory reconciliation took longer due to software update.New inventory system required additional training.
BNK_100007production4.5false6200 Smith StPLT_A06Southern MetalsHoustonTX77020USAequipment-failure2024-03-152024-03-15equipment-maintenance2PRD_007Metal SheetSeal replaced and fluid refilled.MGR_1060954200MGR_106Linda FosterHydraulic press malfunction interrupted production.Hydraulic fluid leak detected.
BNK_100008packaging36true950 Mountain AvePLT_A07Mountain View ElectronicsDenverCO80207USAlabor-shortage2023-12-222023-12-24workforce3PRD_008Smart SensorOvertime shifts scheduled.MGR_10722109800MGR_107George HoltzHigh absenteeism during holiday season affected packaging.Multiple staff on leave simultaneously.

What the 96 rows show

from the 96-row sample

Procurement (workflow stage) stands out: mean duration_hours is 29.1, against 14.7 for the rest.

  • 39%recurrence_flag = true
  • 14.0median duration_hours
  • 3plant location countries
  • 6root cause categories
  • 7bottleneck types
  • 21plant location states
Mean duration_hours by workflow_stage96 rows
0204029.1proc…11 ro…10.3prod…21 ro…10.7pack…18 ro…19.2ship…13 ro…16.9inve…16 ro…20.0qual…16 ro…2.5other1 rows
duration_hours96 rows, in bands of 5
0153011221716163140602550duration_hours →

Median 14.0, from 2.0 to 48.0.

plant_location_street96 rows · top 10 of 37 values
  1. 1200 Industrial Blvd5
  2. 88 Lakeview Dr5
  3. 3548 Route 205
  4. 401 Pioneer Rd5
  5. 200 Atlantic Ave5
  6. 6200 Smith St5
  7. 950 Mountain Ave5
  8. 4650 Desert Rd5
  9. 1001 Northway St4
  10. 700 Pacific St4
27 columns by typefrom the column list below
  • string 19
  • integer 2
  • float 3
  • date 2
  • boolean 1

Columns

27 columns in four groups
blueprint · 27 columns
columntypedescriptionexample
Text 19 columns
bottleneck_idstringUnique identifier for each supply chain bottleneck recorduniqueBNK_100001
plant_idstringUnique identifier for the manufacturing plant where the bottleneck occurredPLT_A01
plant_namestringName of the manufacturing plantCentral Manufacturing
plant_location_streetstringStreet address of the manufacturing plantoptional1200 Industrial Blvd
plant_location_citystringCity where the manufacturing plant is locatedoptionalCleveland
plant_location_statestringState or province of the manufacturing plantoptionalOH
plant_location_postal_codestringPostal code of the manufacturing plantoptional44115
plant_location_countrystringCountry where the manufacturing plant is located3 countries · optionalUSA
workflow_stagestringStage of the supply chain workflow where the bottleneck occurred (e.g., procurement, production, packaging, shipping)7 valuesproduction
bottleneck_typestringType of bottleneck encountered (e.g., material shortage, equipment failure, labor shortage, process delay)7 valuesequipment-failure
bottleneck_descriptionstringDetailed description of the bottleneck and its impact on operationsUnexpected breakdown of a…
root_cause_categorystringHigh-level category of the root cause (e.g., supplier issue, equipment maintenance, workforce, process design)7 values · optionalequipment-maintenance
root_cause_detailsstringDetailed explanation of the root cause analysisoptionalDie alignment issue.
affected_product_idstringIdentifier for the product(s) affected by the bottleneckoptionalPRD_001
affected_product_namestringName of the product affected by the bottleneckoptionalHVAC Compressor
resolution_actionstringDescription of the action(s) taken to resolve the bottleneckoptionalMaterial recipe updated.
resolved_bystringName or identifier of the person/team responsible for resolving the bottleneckoptionalMGR_101
manager_idstringIdentifier for the operational manager responsible for this workflowoptionalMGR_101
manager_namestringName of the operational manageroptionalLaura Simmons
Numbers 5 columns
duration_hoursfloatTotal duration of the bottleneck in hours0 or more · optional5
impact_severityintegerSeverity of the bottleneck's impact on plant operations (1=Low, 2=Moderate, 3=High, 4=Critical)1 to 43
recurrence_countintegerNumber of times this bottleneck has occurred in the past 12 months0 or more · optional0
throughput_loss_unitsfloatEstimated loss in throughput (units not produced or shipped) due to the bottleneck0 or more · optional230
financial_impact_usdfloatEstimated financial impact of the bottleneck in USD0 or more · optional9200.75
Dates and times 2 columns
date_detecteddateDate when the bottleneck was first detected2024-03-04
date_resolveddateDate when the bottleneck was resolved (if applicable)optional2024-03-04
True or false 1 column
recurrence_flagbooleanIndicates if this bottleneck is a recurring issuefalse

Use it for

  • recurrence flag39%37 of 96 rowsmean duration hours b…29.1proc…10.3prod…10.7pack…19.2ship…

    A manufacturing dashboard

    The recurrence_flag rate, duration_hours by workflow_stage and a breakdown of plant_location_street. Excel, Power BI or Tableau.

  • Why do the 11 procurement rows have a mean duration_hours of 29.1?

    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 bottlenecks with plant_id, plant_name and plant_location_street to fill a screen in front of a buyer.

Not quite right?

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This dataset96 rows27 columns
Yours1,000 rows27 columnsplant_location_street: UK only

blueprint · manufacturing-plant-supply-chain-bottlenecks

Behind this dataset

Same schema. As many rows as you need.

These 96 rows came out of a blueprint — 27 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
  • Each bottleneck event must be timestamped with both detection and resolution dates.
  • Log impacted production lines and associated inventory SKUs for every bottleneck.
  • Include categorical root cause codes (e.g., vendor delay, equipment malfunction, process misalignment).
  • Quantify estimated production loss (units) per bottleneck.
  • Associate each event with a mitigation action and its completion status.
Rows
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Exports
CSV, JSON, JSONL, Parquet, SQL, Excel, TSV, XML
Licence
yours to use, including commercially
API slug
manufacturing-plant-supply-chain-bottlenecks

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