5 Advantages of Predictive Analytics in Manufacturing
Predictive analytics has been around for decades, but with easy-to-use software becoming more common, predictive analytics is no longer just for mathematicians and statisticians. Now, business analysts and manufacturing experts are using these technologies to increase their bottom line and competitive advantages.
Predictive analytics is the combination of historical data AI and machine learning technology. It helps manufacturers understand, monitor, and optimize their processes. Predictive analytics also identifies trends, anticipates potential problems, and can supply recommendations to maximize performance.
Here are 5 specific ways that Predictive Analytics can be used to aid in your manufacturing process.
1. Reduces manufacturing costs
Predictive Analytics can help reduce mistakes that result in avoidable waste, thus saving money usually spent on raw materials.
Beyond material costs, you can strengthen the capabilities of your MES by identifying other significant costs for your business, pinpointing points of congestion in your operations, and optimizing the control loops (such as supervisory control and data acquisition or SCADA and distributed control systems, aka DCS) in your business to improve operational efficiency and profitability.
2. Preventative maintenance
Collecting data can help predict when maintenance is needed, not assumed. This increases the equipment’s uptime, giving managers a chance to plan needed maintenance or make necessary adjustments before a failure occurs.
3. Alerts to quality issues
Identifying maintenance and quality issues earlier can add value to applications that rely on materials whose prices are volatile. The method of tracking performance allows you to be alerted to processes that may run out of tolerance or compromise quality. When processes can be stopped early or adjusted, material waste or rework can be reduced or eliminated.
Predictive demand analytics can even be used to manage labor and talent acquisition more effectively in an unstable and ever-changing market. Specifically, the Skills Gap is one of the biggest concerns for manufacturers. Manufacturers may predict what skills and labor will be needed in the future by extending data from the process, to the plant, to the planet. This means working with educators to upskill or reskill the existing workforce to meet labor needs or post jobs earlier.
4. Attracts Valuable Talent
In the face of an approaching skilled labor shortage, predictive analytics and machine learning technology can help manufacturers attract digital-native talent. For many factories, recruiting and retaining talent is challenging, so the opportunity to work with leading-edge solutions provides added value to a business.
5. Increases revenue
Predictive Analytics has become a solution for tackling production pain points, such as the ones listed above. This AI-powered technique uses historical and real-time data to predict critical future outcomes, reduce risk, improve operations and reduce costs. All of these benefits working together or isolated can help a business discover and increase revenue and profits.
The Future of Predictive Analytics
Manufacturing stands to benefit more than other sectors from predictive analytics. Manufacturing generates massive amounts of data, requires repetitive manual tasks, and produces multipronged problems beyond the scope of traditional tools.
Predictive Analytics still has room to grow. Due to its ability to deliver high fidelity data, we anticipate that Predictive Analytics will improve remote and mobile diagnostic analytics. This trend can mitigate the demand for field technicians. Additionally, high-confidence remote diagnostics may be able to provide maintenance recommendations to on-site operators as well, thereby reducing the need for field technicians even further.
Analytics may increase subscriptions, insurance policies, or warranties. Connected devices may lead to more flexible equipment. As demand changes, so can the subscription and features.
For example, subscriptions give OEMs the ability to add or take away features, data tracking, and software remotely.
We can only imagine the capabilities possible as technology and AI specifically transform further.
Who should use Predictive Analytics in Manufacturing?
Predictive analytics provides the ideal solution to many complex manufacturing issues, whether it is improving quality, reducing downtime, or optimizing efficiency. Bottom line, it helps factories and businesses increase profits, making it the ideal tool for anyone looking to grow their company.
Start leveraging Predictive Analytics in manufacturing with Profit Velocity.
By accessing data that’s readily available in your ERP and supply-chain systems, Profit Velocity helps manufacturers grow profits by 450 basis points or more. Our mix-management tool identifies large profit opportunities that lay hidden in your operations. We then set up a fully configured cloud-based platform that enables you to generate significant profit gains.
Contact us using the form below to see how leveraging predictive analytics and the innovative technology of Profit Velocity can transform profitability in your business.