Artificial intelligence

Machine Learning Cases in Business Industries

Innovative technologies appear every day. Today the center of development is machine learning based on artificial intelligence. ML applications and programs will become an integral part of the optimization and success of companies. Already, these tools are helping to proactively detect equipment malfunctions, create personalized recommendations for customers, and find rational approaches to problem solving. Such programs cope with some tasks perfectly, while others still require the attention of people.

In this article, you will find out in which areas of business machine learning programs are already used.

Manufacturing: tracking the production process, reducing the number of equipment breakdowns

Repair and purchase of new equipment can lead to the fact that factories and plants will be forced to spend millions of dollars from the budget. Machine learning is able to read information from data and capture the conditions in which this or that breakdown or failure occurs. With this information, engineers will be able to eliminate the conditions that lead to this.

Control and management:

– tracking the production process, identifying defective goods and finding the cause of the spoilage;

– reduction of time for carrying out some operations;

– reducing costs by using less raw materials;

– process automation.

Simatic, using machine learning, was able to automate the production of many types of goods by more than 70% without firing employees. Moreover, the company got rid of defective goods and increased the number of manufactured products by several times.

Artificial intelligence is able to independently monitor the security of data, monitor critical changes that may lead to leakage. The program can immediately send all changes for review to security personnel who will eliminate the threat.

Search for new sources of mineral products. The main problem for oil companies is finding new locations for eruptive rocks. ML can take care of this. It is conducting a thorough analysis of locations where mining operations are already taking place. Finding criteria similar to the previous ones, it is possible to establish new oil deposits with a sufficiently high accuracy.

Finance: analysis and identification of risks and combating fraud

As a rule, the company’s employees are engaged in determining the creditworthiness of the client. This is a time-consuming process and sometimes there are mistakes when loans are provided to people who are unlikely to be able to repay the given amount within a specified period of time and are not provided to solvent clients. A machine learning program can analyze all previously taken loans, collect information whether the loan has been paid, whether there have been cases of delays and provide information to a bank employee.

Anti-fraud. The number of fraudulent activities in banks only increases annually. Impostors find new ways to steal money from bank accounts. The algorithm can be taught to identify signs of fraud and stop their activity.

Medicine: medical examination and the use of a robot during surgeries

One of the advantages is that hospitals and clinics can use programs where all symptoms of diseases will be indicated, and diagnoses will be made immediately.

One of the revolutionary cases is Corti artificial intelligence. The system, by analyzing the responses of people calling the ambulance, listening to their breathing rate, helps to determine cardiac arrest. In one experiment, Corti was able to identify over 90% of cardiac arrest.

Naturally, such a system cannot be used without a qualified specialist, therefore in many European countries such systems are already being installed that work together with dispatchers.

Already, a huge amount of work is being done to create robots that can independently carry out some types of simple surgeries. The developers are now perfecting this process, since everything in medicine has to work with 100 percent accuracy. This approach will allow surgeons to devote more time to complex cases.

Ecommerce & Marketing: predicting likely customer actions and inventory

Algorithms can learn to recognize customers who are likely to place an order. What’s more, it can be configured to create personalized recommendations based on previous purchases for each loyal customer. To increase the number of placed orders, algorithms can provide each customer with a system of discounts that will motivate them to purchase.

Companies that have already implemented these algorithms report that the average check has increased by more than 40%; and the number of customers returning to make a purchase increased to 45%.

Analysis of top products and control of purchases. ML is able to determine which products are in the greatest demand and independently register the purchase of new products in order to reduce the waiting time for new deliveries.

Ecommerce companies can find a useful ML platform solution today. The sooner you implement such technology, the faster you can reap the benefits.

Logistic operations

As in manufacturing, machine learning helps you to know ahead of time when a crisis is coming. Malfunction of the vehicle that delivers the goods to the warehouse; damage to goods during loading or unloading, and more. Even a single section failure will lead to a series of problems that negatively affect your customers’ experience and increase costs.

Supply Watch is helping DHL immeasurably. It monitors the weather in different regions, analyzes traffic on the roads, and also monitors the issue of environmental friendliness of processes.

Conclusion

According to experts’ prognosis, the volume of machine learning applications in various business areas will increase by 40% by 2024.

By using innovative algorithms companies cut down on expenses, learn about potential problems before they arise and improve buyers’ experience.

Angela Scott-Briggs

Editor, TechBullion.com | Interested in Innovations in Business, Finance, and Technology .

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Angela Scott-Briggs

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