Case Studies
Solar Turbines Uses aPriori Manufacturing Cost Models to Facilitate Fact-Based Supplier Negotiation
Overview
Analytics & Modeling - Predictive Analytics Application Infrastructure & Middleware - Data Exchange & Integration Functional Applications - Manufacturing Execution Systems (MES) | |
Equipment & Machinery | |
Procurement Quality Assurance | |
Predictive Maintenance | |
Data Science Services System Integration | |
Operational Impact
Solar Turbines uses aPriori to conduct batch analyses, generating price points for different batch sizes depending on production volume. This information allows Solar Turbines to compare tiered pricing (based on volume discounts) to operational requirements like desired inventory levels. | |
In one representative case, Solar Turbines used aPriori to generate a manufacturing cost model for welding a component. The model suggested a welding time of 17.5 hours (including both cycle time and set up time). Their supplier, however, offered a bid of 48 hours for the same component. Leveraging their detailed manufacturing cost model, Solar Turbines’ team was able to initiate a productive conversation on this divergence. The supplier re-examined the actual manufacturing process and pinpointed hours of unnecessary weld-grinding time that was driving the difference with aPriori’s manufacturing cost model. This time was eliminated, and the price for the part was ultimately reduced. | |
In another illustrative fact-based negotiation, Solar Turbines used aPriori to model manufacturing costs for a part with a cost structure heavily driven by materials (30% of the total part cost). Working with the supplier, they determined that excess cost was rooted in supply chain waste: the supplier was paying 50% more for materials than the price available to Solar Turbines. Simply by identifying a more cost-effective materials source, per unit costs could be reduced. | |
Quantitative Benefit
The price for the part was ultimately reduced by about $450 per unit. | |
Per unit costs could be reduced by 15%. | |