Case Study · Downstream Refining

$46M an MRO-Betriebskapital in sieben Raffinerien freigegeben

An AI-native MRO intelligence layer deployed across seven SAP-isolated refineries in 11 weeks, releasing $46M in working capital, cutting emergency procurement by 44%, and eliminating PSM substitution failures.

7 Refineries ~$285M MRO Inventory 11 Weeks to Go-Live SAP ERP
Downstream refinery MRO working capital released through AI-native spare parts intelligence across seven sites
~$46M in MRO working capital released across all seven refineries
44%Emergency procurement costs reduced within 12 months across all 7 sites
NullPSM substitution failures on safety-critical, pressure-rated process equipment at 12 months
11 WksFrom first data connection to four modules live across all seven refineries
Über den Kunden

One of the largest independent downstream refining companies in the United States, operating seven complex refineries across the Mid-Continent, Southwest, Rocky Mountain, and Pacific Northwest regions.

Combined crude processing capacity exceeds 650,000 barrels per stream day. Asset classes under management include fluid catalytic crackers, delayed coking units, centrifugal compressors, and heat exchangers, with a large rotating equipment population subject to OSHA Process Safety Management and API inspection obligations. For operators running multi-site refinery networks, how spare parts inventory is managed across distributed oil and gas sites determines whether emergency freight becomes the default procurement channel.

At deployment, combined MRO inventory was valued at approximately $285M across seven site storerooms and a central distribution facility. The organisation ran SAP as its primary ERP with separate site-level CMMS instances, resulting in no consolidated visibility or demand intelligence at enterprise level. Each refinery planned and procured independently, with no mechanism to surface surplus stock at peer sites before raising an external purchase order.

"The audit we ran before deployment kept pointing to the same conclusion: we didn't have a parts shortage across our network, we had a visibility shortage. Virtually every emergency freight event involved a part that was physically somewhere in our system. MRO360 made the network visible in a way our own SAP instances simply could not." (VP Supply Chain & Reliability)

Die Herausforderungen

Wie das Unternehmen die Nachricht veröffentlichte ~$46M in working capital by fixing the gaps below.

  • Seven isolated SAP instances with no consolidated MRO visibility or shared demand intelligence across refineries.
  • OSHA PSM and API compliance risk from site-level substitution decisions, with no enterprise-wide certification verification or audit trail.
  • Specialty component lead times of 16-24 weeks against reorder points set at SAP go-live and never systematically updated.
  • 17 avoidable emergency procurement events in 12 months caused by no cross-refinery inventory visibility, each carrying 50-80% freight premiums.
  • Turnaround gap analysis performed manually 3-4 weeks before mobilization, too late for normal procurement on any long-lead parts identified.

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Was Sie lernen werden

In der vollständigen Fallstudie

  • How MRO360 connected seven isolated SAP instances in 11 weeks, with no ERP replacement and no parallel migration.
  • Wie PSM-weighted criticality assessment across regulated refinery process units flagged 100% of safety-critical SKUs for certified-substitute-only resolution.
  • How dynamic reorder points replaced static 4-6 year-old SAP configurations simultaneously across all sites, eliminating both overstock and dangerous stock exposure on the same part numbers.
  • How cross-enterprise transfer intelligence reduced avoidable emergency procurement from 17 events to near zero, and increased inter-refinery transfers from 4 to 19 per month.
  • How AI turnaround demand forecasting confirmed every critical spare needed for a planned refinery shutdown was available six weeks before mobilization, with zero emergency procurement in the first post-deployment cycle.
  • How the model compounds accuracy over time: correlated failure pattern recognition, OEM lead time calibration, and turnaround forecast refinement with every operational cycle.
Für wen dies gedacht ist

Entwickelt für Teams, die für Wartung, Reparatur und Überholung (MRO) sowie für die Zuverlässigkeit zuständig sind

VP Supply Chain & Reliability

Accountable for network-wide emergency spend, turnaround readiness, and inventory performance across multiple refinery sites.

MRO & Procurement Managers

Responsible for spare parts availability, stocking policy, and spend control across a multi-site SAP environment.

Maintenance & Turnaround Planners

Managing work order backlogs of 1,500-3,500 items per site and confirming parts availability before every planned shutdown.

ERP & Operations Leaders

Deploying an intelligence layer above existing SAP instances without replacement, migration, or IT disruption.

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