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Product Literature

Product Literature

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Hamiltonian’s Kãsei is a light-weight data integration platform providing advanced, AI-assisted Data Governance capabilities. Kãsei seamlessly integrates with all Enterprise Software, Analytics and Cloud Applications. 

DATASHEET

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BROCHURE

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Hamiltonian’s MRO Optimizer uses AI and Maching Learning algorithms to analyze the MRO parts ordering rules, decreases MRO spend and reduces stockouts.

DATASHEET

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BROCHURE

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Customer Success Stories

Customer Success Stories

01

Kãsei

A Fortune 500 paint manufacturer is taking control of their master data and getting more out of Oracle E-Business Suite with the help of Hamiltonian Systems.

02

Kãsei

Hamiltonian Systems helps a global Steel manufacturer with application data collection, data governance, data quality and data integration using pre-built data templates for Oracle Supply Chain.

YouTube Channel

YouTube Channel

Kasei - Training Material
Optimizing MRO Inventory without Min Max or Guesswork   v1.1
55:53

Optimizing MRO Inventory without Min Max or Guesswork v1.1

A major objective of most manufacturing companies’ digital initiatives is increasing operating margins. Cost reduction through production process efficiency improvements, effective asset management, and sourcing optimization for direct and indirect items are some of the primary ways that organizations are successfully improving their profitability and competitiveness. Unlike for direct items, demand and usage for indirect items (also referred to as Maintenance, Repair and Operations, or MRO) varies depending on equipment failures and unpredictable factors. Forecasting the equipment failure and the need for required spare items is difficult. Companies tend to overstock repair parts, but still face stockout situations. Overstocking increases expense budget, hurting the bottom-line results; running out of an MRO item can cause downtime. Hamiltonian’s MRO Optimizer analyzes the Min/Max ordering and other planning rules, and then adjusts the necessary parameters to suggest the appropriate quantity for safety stock and replenishment. Finding the magic number for every part is the key to optimize MRO purchases. The safety stock levels and the quantities of purchase derived by replenishment methods are based on certain assumptions and individuals’ subjective decisions. The forecasts which drive the ordering rules originally start with assumptions for initial inventory levels. Subsequent ongoing replenishment should be based on: Actual consumption Equipment Reliability and Usage Preventive and Predictive Maintenance work orders Asset Criticality Material lead time Future Cognitive Maintenance MRO Optimizer has built-in, rule-based algorithms and machine learning to optimize the replenishment of every item, helping users maintain desired plant service levels while reducing stockouts. This business process automation improves maintenance efficiency and reduces the subjectivity of MRO inventory replenishment decisions.
Webinar
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