Manufacturing organizations are hardly an avant-garde AI implementation. These sectors are typically quite traditional and reluctant to embrace new technology trends, especially if they are not solid market-proven. However, things are – slowly but surely – changing. AI started to gain a well-deserved spotlight as it became evident that it is a safe way to increase the overall operational performance. Under the broad “Artificial Intelligence” term” are hidden plenty of different approaches are hidden able to cover specific manufacturing companies’ needs perfectly, regardless of how different they may be.
Below we present some of the most effective, tech-oriented solutions for the manufacturing industry.
AI-based solutions that use intelligent sensors can be a very effective separation and sorting technology, which enable mining companies to make the most of every mining facility, increase profits, increase overall effectiveness, and – in general – improve operational performance.
So-called smart sorting typically uses several technologies, IoT and deep learning included. Within these systems, AI algorithms, triggered by sensors, can be used to improve diverse mining processes.
AI-based solutions should be hailed the most for safety increment for both employees and equipment. Typically, there was a need for regular and thorough inspections, which was cost- and time-consuming. With AI-driven technologies such as IoT, computer vision, digital twins, and so on, mining companies are capable of skipping and accelerating the processes.
With smart technologies, operators can remotely check the shape of the machines, vehicles, and other equipment; wearables sensors can detect, for example, the state of health and well-being of drivers on-site and monitor all the parameters underground. All of that helps to forecast potential hazardous/emergencies and avoid or reduce the risk of damages.
First, when it comes to analysis samples, smart algorithms deliver more reliable results in a much shorter time compared to traditional methods.
Second – image recognition can automatically determine the type of discovered minerals saving time and effort for onsite workers.
Third – automated vehicles and network that consist of intelligent sensors significantly increase safety in work environment ultimately leads to cut costly delays in operational processes.
Artificial intelligence that shifts raw materials mining from a people-oriented operation to a process-oriented one is critical to upgrading accuracy, error elimination, and faster decision-making processes.
Machine learning and computer vision make it possible to automatically determine the rock samples, and drilling data can examine the type of discovered minerals with the highest high level of accuracy. Reducing the amount of human labor (people no longer need to collect data physically) helps mining operators cut operational costs.
They can install automation tools to remotely control their assets and design automated-triggered scenarios and interactions that should occur under certain conditions. Specifically, Automated Guided Vehicles are gaining more and more recognition in the mining industry.
Mining vehicles, drones, autonomous drilling systems, and hauling fleets simultaneously increase safety in the work environment and operations productivity.
Automating mobile assets equipped with wireless sensors that can gather data reduces or removes the need for human presence on-site, leading to increasing workforce safety.
Moreover, predictive analysis and insights conducted by AI solutions such as remote sensors allow mining operators to foresee better and prevent any dangerous incidents. A sophisticated AI-based tracking system, enabled with wireless-connected devices, provides operators with the capabilities to coordinate workers and – if necessary – warn them not to go to certain areas.
No other factors could cover the last-mile disruptions preventing customers from getting what they paid for as soon as possible. A smooth and seamless supply chain increases the organization’s efficiency and improves customer satisfaction.
However, typically the supply chain was also the most vulnerable stage of a business’s workflow because of the variety of factors that could potentially influence the whole process. AI, yet, could tame them by releasing potential bottlenecks.
AI algorithms analyze the entire array of multi-sourced data (such as warehouse locations, product flows, demand forecasts, planning, scheduling of manufacturing operations, and so on) to enable businesses to establish the best possible process.