Implementing AI in Supply Chain
How do businesses apply AI in managing various aspects or steps of the supply chain network? Transportation, manufacturing or quality control are some examples of the areas in which the AI can be implemented for the supply chain.
Artificial Intelligence (AI) is playing a continuously growing role in various operations across different industries, and when it comes to supply chains, it is also casting an increasingly wider net. AI, after all, helps deliver more efficient and faster operations, maximized productivity, and less uncertainties. With AI and machine automation, supply chain and logistics companies are better able to manage the complexities and intricacies of the business.
More specifically, supply chain networks can use AI to automate certain operational functions such as inventory management, transportation schedules, tracking, workplace safety analysis, quality control, among others. With supply chain processes now streamlined and better monitored, the margin of error is reduced, production cycles become speedier, and operational costs are lowered.
How Is AI Applied in Different Areas of the Supply Chain?
It is imperative for companies to get their supply chain right, especially at a time when consumers expect their orders fulfilled and delivered at their doorstep much quicker and in perfect condition. However, supply chain is much more complicated and intricate in that it involves many different processes, organizations, people, and technologies. And while coordination among all these essential parts of the network is key, there is only so much one can do without automation and AI.
How do businesses apply AI in managing various aspects or steps of the supply chain network?
Companies use AI to run their transportation activities and minimize transportation disruptions. For instance, weather data can be integrated into logistics management so logistics service personnel can be alerted about inclement weather. In turn, they can make adjustments with regard to transportation routes and delivery schedules, as well as recommend courses of actions.
AI is also better equipped to track goods that are in transit with their carriers, making it easier to predict delivery schedules and anticipate delays. And because AI makes it easy for logistics companies or logistics departments to access vital information, such as account information and addresses, they are able to optimize routes. This means having one truck make deliveries in one area instead of two trucks covering the same route in a given day.
AI software and AI-based automated tools, like robots, can be used by manufacturing departments to enhance productivity and safety. For instance, robots or machines with AI software can work side by side with humans in the production line and take care of hazardous tasks or those that require a combination of repetitive action and precision.
Moreover, AI can also help analyze data where workplace and manufacturing area safety are concerned. AI can therefore mitigate risks and enhance safety of not just the workers but also the materials inside the warehouse and production floor.
Additionally, AI software can help keep track of raw materials used in the manufacture of products and manage the consumption of these materials such that no shortage occurs. A shortage of raw materials can impede production and delay delivery of finished products.
AI can also keep data regarding machine and equipment maintenance. It can keep track of their checkup, cleaning, repair, and replacement schedules and alert the appropriate personnel about them. This way, manufacturing equipment are always kept in tip-top shape. The less equipment damage and malfunction occur, the less companies have to spend on unexpected repair costs, and the less expenses they incur to cover the resulting loss of productivity.
In quality control and improvement of products and services, AI techniques can be used to predict, anticipate, avoid, and prevent quality issues. For example, AI-based image analysis tools can promote a higher level of manufacturing precision. They can do an automated quality inspection and identify defects in the finished products, as well as detect missing parts or components.
Moreover, high-resolution cameras equipped with powerful image recognition technology (and even sensors) can do a visual inspection of the production line. This ensures uniformity in output. These cameras can also detect trends then interpret and analyze the data they captured. The data collected can help with automating documentation and tracking of product quality.
Eventually, AI-based quality control processes can reduce costs related to manual product inspection, manual intervention, and quality assurance. With AI, future product recalls and losses can be avoided, thanks to its ability to spot anomalies early on and suggest preventive maintenance on machines and equipment.
AI-based demand forecasting can significantly reduce errors in supply chain networks. With companies having automated inventory management, they won't have to experience out-of-stock situations. There won't be problems related to processed yet unfulfilled orders, which could mean the need to issue refunds to customers and writing these off as losses.
Moreover, AI-based tools can analyze data and trends related to customer behavior, as well as consider economic parameters and other external factors that would affect the consumers' purchase power. This can help companies forecast a surge or decline in consumers’ demand for certain products. A foreseen rise in demand can, in turn, help companies plan to boost their inventory and prepare stocks, while a foreseen drop in demand can help them plan countermeasures to prevent an over-excess in inventory.
AI can gather and analyze logistics data to promote smarter container shipping. This data helps the container shipping industry make more informed decisions and better deal with challenges related to moving their cargo and delivering their shipment to their destination.
More specifically, shippers, carriers, and freight forwarders can better plan and optimize their travel time, resources, and costs. They will be able to tackle shipping problems and outline solutions, like looking for an alternative port if the original destination port is closed off or dealing with travel bans and closed points of entry in the event a pandemic hit.
As every step or aspect of the supply chain network moves forward in its application of artificial intelligence, all companies involved need a fast and reliable system to update these AI applications. PurpleDye is the best platform to use for creating, improving, and maintaining the AI software of any company.