Using AI to Solve Complex Global Supply Chain Management Challenges

We are noticing an increasing level of excitement about the possible applications of artificial intelligence (AI) in supply chain, along with some skepticism and lack of enthusiasm from the traditionalists. AI definitely has the potential to enrich our everyday business activities, but how far have we got?

How Orel IT see AI in the supply chain

AI is intelligence exhibited by machines, or when machines mimic or can replace intelligent human behavior, such as problem-solving or learning.

It can be applied in two ways:

  • Automating processes and actions so they can operate without the need for human intervention
  • Assisting the human decision-making process in day-to-day operations by reducing errors and identifying bias, especially in data analysis

We can provide applications in logistics & Supply chain planning

Warehouse logistics and transport operations generate huge volumes of data. To gain full benefit from this data we need to apply analytic tools to gain better insights. Orel IT Machine learning techniques can be used to streamline and automate processes such as load forecasting and vehicle scheduling. New AI software includes functionality that teaches computers how to provide real-time information from the raw data, on which key decisions then are based.

ML can provide the best possible demand scenarios based on intelligent algorithms and machine-to-machine analysis of big data sets, using work tools that run in a continuous loop. This kind of capability could optimize the delivery of goods while balancing supply and demand, and wouldn’t require human analysis except for the setting of parameters.

Anticipating Orders Before they are Placed

Orel IT can provide services and has the ability to shorten delivery times and improve efficiency For example, with our help global supply chain managers could use AI systems to detect risks in trade shipping lanes and, using shock-detecting sensors, potential damages to cargo; they could then take corrective action and minimize operational delays.11 Within warehouses, machine learning systems may be able to recognize common scenarios and trends, and link these to specific customers and orders;

anticipating the content of an order, these systems would then pre-pick-and-pack without first waiting for orders to be placed.

Robots and Self-Driving Vehicles

Orel IT predicts and looking forward to build innovative solutions that warehouses of the future will deploy the next generation of self-driving vehicles, such as autonomous forklifts, carts and pallet movers, which will be able to navigate without the aid of magnetic strips or other guides.

How Orel IT Supply Chain Optimization Is Improving Management and Efficiency

Some of the key factors that we are planning and machine learning can help identify include inventory levels, supplier quality, demand forecasting, product planning, procure-to-pay, transportation management and more.

How we orel IT is ready to serve your business goals and priorities by our solutions:

  • Keep up with customer demands and delight customers
  • Improve service levels
  • Reduce inventory and/or logistics costs
  • Improve the speed in decision making and fuel innovation