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This is an excerpt from the AI case studies bible. Make sure to get your copy now!
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The supply chain entails materials, products, and packaging of most of the items used in daily life, and the invisible ingredient to its efficiency and success is artificial intelligence (AI). Most companies are making the shift from remote monitoring to the optimization of controls and advanced autonomous systems of AI to boost functionality.
Productivity is greatly enhanced when AI is deployed to predict demand and assist with network planning. By having a system that can assist with capacity planning, and generate reliable market forecasts, businesses can better adapt to the situation at hand.
Some example applications of AI in the supply chain are:
- Accurate Inventory Management
- Warehouse Efficiency
- Enhanced Safety
- Reduced Operations Costs
- On-time Delivery
For instance, Echo Global Logistics which is based in Chicago, USA, uses AI to provide supply chain solutions to optimize shipping and logistics requirements to allow consumers to move their products quickly, efficiently and economically. Coyote, a logistics company acquired by UPS utilizes a wide range of approaches – including statistical forecasting, AI and deep learning – to pair customer knowledge with external data (such as real-time and weather traffic) so that manufacturers anticipate challenges, including delays, before they occur. As a result, they prepare replacements so that supplies come still on schedule.
According to Toorajipoura et al., 2020, AI can deliver so many benefits in the operations of supply chain and logistics including cutting costs by mitigating risks and reducing redundancy, faster deliveries via optimized routes, better forecasting, and more efficient customer service. To be valuable in the supply chain, AI should have access to real-time data and external data, it should be able to support the ultimate goal irrespective of the constraints, and all engines should be highly scalable, autonomous, and assist decision making. The integration and consolidation of different data sources is obviously a challenge for many organizations that lack a proper data strategy. Something the Tesseract Academy can help you with.
In summary, AI supply chain systems help reduce dependency on manual efforts thus making the entire process faster, safer and smarter. This helps facilitate timely delivery to the customer, accelerate traditional warehouse procedures, and remove operational bottlenecks along the value chain with minimal effort to achieve delivery targets.
As companies are trying to become pandemic proof after the COVID-19 pandemic, we should expect greater adoption of these technologies. Furthermore, the synergies between internet-of-things, blockchain and AI is expected to bring explosive growth and change in the world of supply chains.
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