IoT, robotics and machine learning set to transform the supply chain, suggests Inmarsat research

Transport and logistics businesses are investing in Internet of Things (IoT)-based smart technologies to help them take advantage of the wealth of opportunities that the Fourth Industrial Revolution offers.
9 months ago

4 May 2018

Transport and logistics businesses are investing in Internet of Things (IoT)-based smart technologies to help them take advantage of the wealth of opportunities that the Fourth Industrial Revolution offers. This is according to research data collected by Inmarsat, the world’s leading provider of global mobile satellite communications, which reveals that the sector is prioritising IoT, machine learning and robotics to increase efficiencies across the supply chain.

Inmarsat’s ‘The Future of IoT in Enterprise’ report, featuring responses collected by Vanson Bourne from 100 large global transportation companies, found that respondents see IoT as the top priority in their approach to digital transformation, with 36 per cent having already deployed IoT-based solutions, and a further 45 per cent expecting to roll the technology out by 2019.

The research further revealed that transport companies are rapidly exploring a wide range of other next generation technologies in the pursuit of digital transformation.  The most popular are machine learning (37 per cent), robotics (37 per cent) and 3D printing (29 per cent).

The supply chain looks set to be one of the biggest beneficiaries of this drive towards digital technologies, with 14 per cent already reporting visibility and efficiency improvements in their supply chains and a further 65 per cent expecting to achieve this in future.

Commenting on the findings, Mike Holdsworth, Director of Transport at Inmarsat Enterprise, said: “The industry is clearly making significant strides towards digital transformation, with IoT-based solutions, used in conjunction with robotics, automation and machine learning, helping to transform the way that goods are manufactured, stored and delivered. Companies that proactively invest in these technologies will be able to facilitate more secure and profitable operations across their supply chain.

“Connected machines that can quickly locate and retrieve stock, self-navigate through any environment and make automatic route corrections based on real-time information updates will prove invaluable for any logistics organisation,” he continued. “Smart robots and unmanned aerial drones that work without rest breaks, carry heavier loads and quickly bypass areas of heavy traffic or congestion will be hugely important.  They will enhance supply chain management, while their ability of to self-diagnose faults and schedule predictive repairs will be vital for minimising down-time and reducing maintenance costs.”

Holdsworth concluded: “Data-driven smart machines that use sensors to transmit and receive information will need to remain in constant communication through every stage of the worldwide supply chain to be effective. However, this can be especially challenging in ‘blackspots’ with little to no mobile coverage. For logistics companies to access the full value of IoT based solutions, the importance of reliable, continuous connectivity cannot be underestimated, and this is only achievable through a dedicated satellite communications technology.”

Inmarsat’s L-band services offer a global satellite network that provides critical connectivity for with up to 99.9% uptime, allowing reliable end-to-end communications between smart machines, robots and device sensors across any region on Earth. This ensures that even in the most isolated or hostile environments, transport and logistics companies maintain real-time synchronisation between their assets and are able to gather all valuable data needed to make necessary workflow improvements that will drastically increase their chances of success in a competitive digital world.

Source: Inmarsat

Illustration Photo: Robots used at Amazon fulfillment centers (credits: SDOT Photos / Flickr Creative Commons Attribution-NonCommercial 2.0 Generic (CC BY-NC 2.0))

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