Cummins Power Generation BU launched Frontier program which will allow a common, global order-management system that will enable its customers to receive the right product at the right price at the right time.

Road congestion and strained transportation networks are persistent concerns associated with the rapid urbanization of developing and developed economies. A 2015 study1 reported that travel delays due to traffic congestion led to the waste of 3.1 billion gallons of fuel and a loss of nearly 7 billion extra hours to travelers during rush hour traffic, with a nationwide cost of around $160 billion, or $960 per commuter. Alleviating traffic congestion, in addition to improving safety, is leading public and private organizations to explore new mobility paradigms such as ride-share autonomous vehicles. GOAL The goal of the Connected Vehicle Urban Traffic Management (CVUTM) testbed is to create a smart road traffic ecosystem featuring connected vehicles using vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) technologies, sensor fusion, industrial IoT platforms, cloud infrastructure, and edge analytics. This testbed will serve to preempt road congestion, automatically detect unusual eventson the road, and enable cooperative movement of traffic. In due course, both autonomous and non-autonomous vehicles will participate in this ecosystem with a goal of minimizing road congestion and improve overall improving motorist and pedestrian safety.

A recent study on maturity of Asset Efficiency from Infosys and the Institute for Industrial Management (FIR) at Aachen University revealed that 85 percent of manufacturing companies globally are aware of asset efficiency, but only 15 percent have implemented it at a systematic level. Current challenges include lack of instrumentation of the assets, missing real-time data analytics, lack of context due to missing information from other systems, and lack of a holistic focus with other aspects of efficiency like energy, utilization, operations, and serviceability.GOALTo collect asset information efficiently and accurately in real-time and run analytics to make the right decisions