Currently the terms Artificial Intelligence, Machine Learning e Deep Learning are on the rise in the business world, but for some sectors, these technologies are still embryonic and are in the early stages of implementation.
But what are these innovations? good, the Deep Learning is a subarea of Machine Learning where algorithms are developed in several layers of processing and both are part of Artificial Intelligence. Most modern models of Deep Learning are based on artificial neural networks (ANNs). ANNs were inspired by the biological brain and learn from processing a set of data, distinguishing features, recognizing patterns, learning hidden interrelationships, grouping objects and processing abstract information. Thus, they can help in solving several problems in the supply chain leaderssuch as optimization, forecasting, image recognition and decision support.
The most discussed application area with artificial neural networks (ANNs) is demand forecasting, as it is an ongoing problem for organizations and extremely important for supply chain management. Many applications have shown that the use of ANNs is more accurate in predicting future demands compared to traditional forecasting techniques. Another use of ANNs that emerged in the literature was in optimization problems, such as lot sizing, vehicle routing problems and decisions related to inventories. ANNs can also be useful for production planning and preventive maintenance. In addition, it can be used to automate processes, maneuver autonomous vehicles and recognize objects due to its image processing capacity. They have become very attractive for solving various problems because they are adaptable to changes.
Finally, a very promising field for the use of Deep Learning it is in support of decision making, due to its pattern recognition abilities. According to Gartner, 16% of companies report a high level of automation in decision-making, with an expectation of reaching 65% in the coming years. Another interesting piece of data highlighted in the Gartner survey is that 21% of companies use Artificial Intelligence to automate decision-making in transport, with an expectation of 56% for 2025. Therefore, due to the numerous applications, the Deep Learning can help with the complexity of supply chain management.
The 28th International Supply Chain Forum (October 18 to 20, 2022) will bring numerous presentations on innovation and technologies applied to Logistics. More information about the event on the website www.forumilos.com.br
References:
– Leung, HC (1995, June). Neural networks in supply chain management. In Proceedings for Operating Research and the Management Sciences (pp. 347-352). IEEE.
– Min, H. (2010). Artificial intelligence in supply chain management: theory and applications. International Journal of Logistics: Research and Applications, 13(1), 13-39.
– Toorajipour, R., Sohrabpour, V., Nazarpour, A., Oghazi, P., & Fischl, M. (2021). Artificial intelligence in supply chain management: A systematic literature review. Journal of Business Research, 122, 502-517.
– ABOL (Brazilian Association of Logistic Operators) – Profile of Logistics Operators 2022
– Gartner – Supply Chain AI
