Achieving Resilience Through Proactive Supply Chain Risk Management

This project will knit together best-in-class technology to produce a modularized machine learning-enabled software component (Dynamic Risk Mitigation Engine) that integrates supplier, bill-of-material, and event-based risk information to produce recommendations aimed at preventing supply chain disruptions before they happen.

Problem

Supply chain managers need improved visibility into multi-tier supply chains. This applies not only to their Tier 1 suppliers, but to the cascading tiers of supply that extend all the way down to the base materials that go into almost any product, weapon system, vehicle, or piece of equipment. Companies cannot afford to trust that critical parts and materials from an opaque network of subcontractors, distributors, and material-input sources are going to be purchased, shipped, and assembled so that they ‘show up on time.’ They need smarter technology solutions that will alert them to potential part and raw material disruptions long before parts are due on their receiving docks. Moreover, they need a user-friendly solution that considers a vast array of complex variables to produce simple and actionable recommendations that ensure an uninterrupted flow of parts and materials to their receiving docks or assembly lines.

Proposed Solution

The team will design a machine learning architecture for the Dynamic Risk Mitigation Engine (DRME) that integrates live datasets from a variety of sources. It will train the DRME and associated machine learning (ML) algorithms using actual customer supplied datasets. The project will deploy the DRME in a live, operational environment at Rolls Royce as part of the SDXTM visibility and analytics platform for multi-tier supply chains. It will then evaluate pilot performance based on comparison to performance baselines established at the beginning of the pilot period and disseminate results of pilot programs through case studies and document recommendations for future development and enhancements.

Impact

Augmented by the DRME, SDX will be used by Rolls Royce to illuminate hidden layers of its supply chain, quantify cost savings opportunities, identify potential supply disruptions before they happen, and recommend mitigating actions aimed at ensuring the timely purchase and supply of parts and materials across its multi-tier supply chain. When used to its fullest potential, this is the equivalent of X-ray vision into multi-tier supply chains and provides the ability to control, or at least influence, previously opaque interactions between sub-tier suppliers. Ultimately, this project will yield tools that can be used to strengthen and increase the resilience of any supply chain network.