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In an interview with the Wall Street Journal, Matthias Winkenbach , director of MIT’s Megacity Logistics Lab, details how last-mile analytics are yielding useful data. After examining their data, UPS found that trucks turning left were costing them a lot of money. This transparency is valuable to shippers, carriers, and customers.
Traditional supply chain analytics and decision-making focused on risk avoidance and control. The more data you have, the more costs you save. And it has quite some catching up to do – the smart manufacturing industry is set to grow from $250 billion in 2021 to $658 billion in 2029.
An innovative application of the Industrial Internet of Things (IIoT), SM systems rely on the use of high-tech sensors to collect vital performance and health data from an organization’s critical assets. What’s the biggest challenge manufacturers face right now?
Finance : Immediate access to market trends, asset prices, and trading dataenables financial institutions to optimize trades, manage risks, and adjust portfolios based on real-time insights. This immediate access to dataenables quick, data-driven adjustments that keep operations running smoothly.
When these systems connect with external groups — customers, subscribers, shareholders, stakeholders — even more data is generated, collected, and exchanged. The result, as Sisense CEO Amir Orad wrote , is that every company is now a data company.
Gathering data from machines, sensors, operators and other Industrial Internet of Things (IIoT) devices, they provide accurate and up-to-date insights into the status of production activities. Reduce risk, maintain compliance and increase ROI with applications built on 30+ years of market-leading technology.
Modern factories are full of machines, sensors, and devices that make up the Internet of Things. All of them generate a trail of performance-tracking data. The challenge for manufacturers is to capture all this data in real-time and use it effectively. Improving the supply chain and mitigating its risk.
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