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How AI is optimizing Supply Chain Management

By ESOutlook | Monday, February 04, 2019

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In the age of fourth industrial revolution, Artificial intelligence (AI) has touched and provided solutions in almost every sector including Supply chain management. AI provides contextual intelligence which helps in reducing operations costs and inventory and responds to clients quicker. The adoption of AI technologies like machine learning provides new insights into a wide range of aspects, including logistics and warehouse management, collaboration, and supply chain management.

Artificial Intelligence in Logistics has provided quick and precise solutions like:

- Intelligent Robotic Sorting  has resulted in high-speed sorting of letters, parcels, and palletized shipments

- AI-Powered Visual Inspection takes photos of cargo using special cameras allow identifying damage and identifying an appropriate corrective action. This helps in using the space appropriately and preventing damage of the cargo.

Generative Design

Manufacturers use artificial intelligence through a new process called generative design. It works this way: Designers or engineers input design goals—along with parameters for materials, then manufacturing methods and cost constraints are given into generative design software. The software then explores all the possibilities of a solution, and quickly “generates” design alternatives. Finally, it uses machine learning to test and learn from each of its iterations to find the best solution.

Predictive maintenance

Sensors and advanced analytics embedded in manufacturing equipment which allows machines to send report their conditions on an up-to-the-minute basis. It saves businesses valuable time and resources, including labor costs, while guaranteeing optimal manufacturing performance. Predictive maintenance is used as a preventive measure by responding to alerts and resolving machine issues.

AI forecasting accuracy

AI enables the tracking and measurement of all the factors that are essential to improve demand forecasting accuracy. It provides a continuous loop of forecasting, continuously adjusting the forecast based on real-time sales, weather and other important factors. All this information could be used to easily reschedule warehouse management, with self-driving forklifts, automated sorting, and self-managing inventory systems powered by drones and other ground vehicles.

Production planning

Companies were not able to execute production planning and factory scheduling accurately before using AI technologies like machine learning. Now they can do that because the technology enables them to analyze a wide range of constraints and optimize for them.

By using AI technology, businesses can reduce supply chain latency for parts utilized in the customized products, AI to predict the demand and optimize the flow of those critical parts to keep production constantly moving.

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