By Dr. Kandis Boyd Wyatt
Faculty Member, Transportation and Logistics, American Public University
Supply chain management includes monitoring the entire creation process to successfully deliver a product to a customer. As a result, more advanced monitoring techniques are needed to remain competitive in an innovative environment. One method is to introduce artificial intelligence (AI) into the supply chain to better identify clear streams of revenue.
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The Value of Artificial Intelligence
AI has several definitions. However, many experts agree that AI is concerned with two basic ideas: 1) the study of human thought processes (to understand what intelligence is) and 2) the representation and duplication of those thought processes in machines, including computers and robots.
Writing in SupplyChain Dive, Matt Leonard says, “Supply chain professionals are optimistic about the potential for artificial intelligence within their operations, but they have also struggled with the technology during the coronavirus pandemic.”
Leonard cites a recent survey, which polled more than 500 supply chain managers and planners using AI. A total of 90% of respondents believe AI will transform supply chains for the better by 2025, while 82% have been frustrated by AI-powered decisions during the course of the pandemic.
Based on my years of experience, it takes time to understand artificial intelligence and how it is infused into the supply chain. To understand what artificial intelligence is, it is useful to examine those abilities that are considered signs of intelligence:
- Learning or understanding from experience
- Making sense out of ambiguous, incomplete, or even contradictory messages and information
- Responding quickly and successfully to a new situation (i.e., the most correct responses)
- Understanding and inferring in a rational way, solving problems, and directing conduct effectively
- Applying knowledge to manipulate the environment and situations
- Recognizing and judging the relative importance of different elements in a situation
A computer can be considered smart, say, only when a human interviewer posing the same questions to both an unseen human being and an unseen computer cannot determine which is which.
As a result, my concept of a successful AI tool includes an autonomous and relatively small computer program. This program observes and acts upon a changing environment and directs its activities toward achieving specific goals related to the above changes by running specific tasks autonomously.
Specifically, machine learning, which is a form of AI, can describe the learning capabilities from a computer’s perspective. These capabilities are modeled after humans, but are generally more simplistic. They can be used to enhance the customer experience.
Robotics Is a Baseline Concept
Robotics are key to automating the operational environment. A robot is an electromechanical device that can be programmed to perform manual and/or mental tasks. Robots can be used in multiple capacities in operational management.
Examples may include building mass-customized products, working in product warehouses by finding, sorting and dispatching goods, and delivering them to customers. Robotic systems are the combination of robotic technology along with value-added operations and management systems meant to allow for greater productivity at lower costs.
According to Stefan Spendrup in IT ProPortal: “In just a few decades, industrial robots have become commonplace in factory settings across the world, and they only continue to gain popularity for their productivity and profitability. Intelligent technology can monitor and manipulate the events happening around them by fusing their sensor data and making use of local conditions to decide on a particular course of action of how to behave or control objects in the physical world.”
In order to have a fully functioning robotic system, a language needs to be developed to communicate with the technology. Natural language processing (NLP) technology gives users the ability to communicate with a computer in their native language.
This technology allows for a conversational type of interface, in contrast to using a programming language that consists of computer jargon, syntax and commands. NLP includes two subfields:
- Natural language understanding that investigates methods of enabling computers to comprehend instructions or queries provided in ordinary English or other languages.
- Natural language generation that strives for computers to produce ordinary spoken language so that people can understand them more easily.
The Key to Robotics in Supply Chains Is About Perception and Vision
Machine translation of language, robotics and artificial intelligence allow computers to translate from one language to another, enabling a broader reach to more potential customers in operational management.
Bob Trebilock highlights this point in Supply Chain Management Review, stating that, “the key to robotics in the supply chain isn’t manipulation. It’s about perception, and perception is vision.” Therefore, computer programs can allow complex systems to interact directly with customers by enabling the AI vision.
About the Author
Dr. Kandis Y. Boyd Wyatt, PMP, is a professor at American Public University and has 20 years of experience managing projects that specialize in supply chain management. She holds a B.S. in meteorology and an M.S. in meteorology and water resources from Iowa State University, as well as a D.P.A. in public administration from Nova Southeastern University.
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