Innovation in the manufacturing industry has allowed facilities to become more software-oriented than ever before. Data collected during standard operations can identify inefficiencies even when they are relatively minute, allowing for adjustments that will make processes as streamlined as possible. Over time, these manufacturing data analytics can increase production rates, limit waste, and even save energy.
As the use of sophisticated sensors increases, allowing real-time data to be available for analysis, the capacity of big data in the sector may even become more powerful.
Read on to find out about how to transform your manufacturing processes with the help of manufacturing data analytics.
Increasing cost efficiency and ultimately fattening the bottom line
Purchasing is a standard part of most companies’ supply chains, but one that can easily be ignored when you’re too busy trying to improve upon other aspects. Starting off from a faulty supplier or one that is a few cents too expensive per component may not seem like the end of the world, but if you produce thousands of products a day, a cent here or there will turn into thousands of dollars on your ledgers.
Manufacturing data analytics can help you understand the cost and efficiency of every component in your production lifecycle, all the way from your suppliers’ trucks. Advanced manufacturing data analytics can help you reach better decisions by visualising how each aspect impacts the final result. If certain components are constantly failing or are not doing exactly what they need, powerful analytics will help you spot them before they become an issue.
Predictive maintenance with manufacturing analytics
Manufacturing systems are constantly operating under heavy loads and any stoppage in work can translate to spiralling losses. Few things are costlier to a manufacturer than downtime. In some industries, it can cost thousands of dollars per minute and millions of dollars per year. Now, with all of the various sensors and connected devices included in today’s advanced equipment, it’s possible for manufacturers to use algorithms to uncover complications before they arise and fix minor issues before they become costlier problems.
Predictive maintenance has the potential to save manufacturers millions of dollars over the course of a year, prolonging the life of equipment and ensuring efficient operations. Thanks to the growth and advancement of big data platforms, it’s becoming easier and more cost-effective to gather these insights.
Effective time management translates to more productivity
One of the biggest problems manufacturers run into is wasted time. While manufacturing chains can be built with efficiency in mind, different factors may play a contributing role in reducing the overall efficiency of the line because of poor installation, misuse, or simply a lack of downtime coordination.
By using sophisticated data analytics and platforms, companies can gain real-time insight into how well their manufacturing lines are operating, both on a micro and macro scale. Understanding how downtime for a single machine can affect the chain, or how different configurations may improve overall efficiency, isn’t just a pipe dream, it should be a necessity. Generating actionable data that lets you realise real improvements in the overall process is a major advantage of applying analytics to manufacturing.
Create better demand forecasts for products
Every manufacturer knows that they are not just making their products for someone today, but also for the perceived demands that will/may emerge in the near future. Demand forecasts matter because they guide a production chain and can be the difference between strong sales or a warehouse full of unpurchased inventory. For most companies, forecasts are based on previous years’ historic values, and not on more actionable forward-looking data.
However, manufacturers can combine existing data with predictive analytics to build a more precise projection of what purchasing trends will be.
Manage your warehouses better
Another overlooked aspect of the manufacturing process is storage. Once products are ready to be shipped, they must be placed in warehouses before leaving for their destination. At this point, seconds and minutes become important, especially in a world that is increasingly embracing ‘just-enough’ and zero-inventory models.
Managing warehouses is more than simply finding space for products to wait. Establishing efficient arrangement structures, better product flow management, and the most effective replenishment procedures can improve operations, as well as your bottom line. Advanced analytics make it easier to understand how to improve your inventory and manage your warehouses better.
Bringing your manufacturing processes into the 21st century can be a straightforward process. By incorporating robust analytics and visualisation tools, you can build a more granular understanding of how your production line operates, and how you can streamline it further.
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