THANK YOU FOR SUBSCRIBING
Manufacturing Technology Insights | Friday, August 02, 2024
Artificial intelligence (AI) in manufacturing refers to applying technology to automate difficult operations and reveal hitherto unidentified patterns in workflows or processes.
Fremont, CA: AI can provide the most value to production and planning floor operations in manufacturing. 4IR technology will enable smart production with digital factories. In 2020, the IFR (International Federation of Robotics) reported that 2.7 million industrial robots were in use in companies globally. This represented a 12% rise over 2019, and with digitalization projects expanding rapidly, the trend is expected to continue.
Stay ahead of the industry with exclusive feature stories on the top companies, expert insights and the latest news delivered straight to your inbox. Subscribe today.
Manufacturers will continue to invest in AI and machine learning to reduce production costs and enhance time to market. In the aftermath of a worldwide pandemic, manufacturers will strengthen their businesses by using technologies that automate jobs, foresee interruptions, and provide end-to-end control over all operations.
Let's look at some AI use cases in manufacturing.
Artificial intelligence in logistics
Overstocking and understocking inventory are common issues in manufacturing. Overstocking typically results in waste and poor profitability, while understocking can lead to a loss of sales, money, and customers.
Manufacturers may leverage technology such as 3D printing to build serial components in-house or at near-shore facilities, minimizing their dependency on remote, low-cost manufacturing locations and improving inventory management.
AI-based robots
AI robots in industrial facilities use machine learning algorithms to streamline repetitive operations and decision-making. These algorithms are self-learning, so they continuously get better at managing the tasks they are given.
Furthermore, AI robots are less prone to mistakes and don't require as many breaks as humans. Thus, producers can quickly expand their output.
Artificial intelligence in supply chain management
Manufacturers may optimize last-mile delivery by evaluating several scenarios (in terms of time, cost, and income) with AI-enabled tools. In addition to using past data to anticipate delivery times, artificial intelligence (AI) can track driver performance in real time, forecast the best delivery routes, and analyze traffic and weather reports.
AI can also give producers more control over their supply networks, enabling them to monitor and track inventories and plan capacity. By implementing a predictive and real-time supplier evaluation and monitoring model, they can quickly determine the level of supply chain interruption and receive notifications when a supplier fails.
AI for factory automation
Factory operators traditionally rely on their experience and intuition to monitor multiple signals displayed across numerous screens and manually adjust equipment settings. This approach places the burden of troubleshooting, running tests, and other tasks on the operators, adding further strain to their workload. Consequently, operators may take shortcuts, incorrectly prioritize activities, and not focus on adding economic value.
More in News