Food / Beverage

Software applications that streamline and automate business processes throughout the supply chain to improve planning, optimise inventory levels, reduce costs, and respond quickly to changes in customer and supplier demand.

The future of AI for the food and drink supply chain

The hype around AI has continued to soar during the beginning of 2019

11-Mar-2019
The future of AI for the food and drink supply chain
The hype around AI has continued to soar during the beginning of 2019. So much so, that 40% of Europe’s AI startups have been found to actually lack the intrinsic AI element to their day to day business. Trending or not, the capabilities of AI cannot be denied - especially in their possibilities to revolutionise standard supply chain practices.

This article will explore the three main benefits that have arisen and will continue to benefit businesses along the supply chain in 2019:

Improved buyer-supplier relations
Due to its ability to efficiently interpret substantial amounts of data in foreign languages, Natural Language Processing (NLP) is an incredibly important element of artificial intelligence and machine learning. This means that big data from suppliers can be audited in a streamlined manner and uncover information that was previously incomprehensible due to language barriers.

Machine learning (ML) and predictive analytics are other facets of AI that will soon become intrinsic to supplier selection and supplier relationship management. This is due to their ability to understand and predict every scenario during every single supplier interaction. By using ML and predictive analytics, businesses can generate data sets such as supplier assessments, audits and credit scoring. Information such as this can help justify important decisions such as choosing a supplier, without just having to rely on referrals or reviews from other clients.

Increasingly thorough quality and problem checks
Integrating AI into the supply chain will allow many companies much more contextual intelligence in 2019. According to a report by DHL and IBM, one of the main technology’s to allow for this will be AI-Powered Visual Inspection. These are next-generation specialised cameras that identify damage of cargo and can identify appropriate corrective action.

IBM Watson is currently using this cognitive visual recognition capabilities to do maintenance checks of physical assets with AI-driven visual inspection. By using a camera bridge to photograph cargo trains, they are able to identify damage, categorise the damage caused and determine the suitable restorative action to take place. As the organisation gathered and processed more data, Watson’s AI-powered visual recognition capabilities progressed to an accuracy rate of over 90% in just a few months. Their model and process can be modified and adapted to other variations of logistics, but not limited to aircraft, vehicles and ocean vessels.

Growingly efficient deliveries
UPS has predicted that the company saves $50 million a year, for every mile that its drivers cuts from their daily routes. In fact, UPS has been using this technology since 2016, proving that AI is filtering through supply chain organisations quicker than thought. This is achieved by their implementation of ORION, an On-Road Integrated Optimisation and Navigation AI-Powered GPS tool, that advises their drivers on the most efficient routes for their fleet.

Instead of using a traditional map database, drivers and vehicles submit data to the ORION database which then uses algorithms to create the quickest and most logical route for their fleets. Their next-generation GPS tool allows routes to be changed whilst drivers are in transit, depending on road conditions and other factors that could increase wear and wear on their fleet. The result? Reduced delivery miles by 100 million, saved resource, reduced emission and minimise damage to their fleet.

There is also growing evidence of AI being used to predict when orders will arrive and depart from suppliers’ warehouses. Lineage Logistics uses the technology to keep their fresh food deliveries cold when delivered to their trade customers. By using AI to predict the path of their deliveries, it means that employees can preemptively arrange pallets in optimised positions so that items that will stay at the warehouse are put further in the back whilst items with a shorter shelf-life are placed nearer to the front. Since incorporating AI into their supply chain, Lineage has increased its efficiency to move 20/30 million pounds of food a year by 20%.

Conclusion

If the above benefits sound like something that could be advantageous to your business, there has never been a better time to conduct research into how AI can be implemented into your supply chain strategy. For business owners that are concerned about the ethical dimensions of AI, it is nonetheless still important to keep these technological advancements on your radar to avoid being left behind the innovation curve in 2019.

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