Across the board, manufacturers are being asked to do more with less. The proliferation and massive investment in ERPs, new software including artificial intelligence and machine learning, and the Internet of Things (IoT) are generating an explosion of manufacturing big data!
All business owners want to know how they can leverage their data to make decisions and gain an advantage. Entering 2021, the big data economy has arrived, and combined with major advancements in technology there is plenty of opportunity awaiting companies across the country. COVID-19 disrupted the entire world, but it also made us all rethink the way we do business, and manufacturing indeed wasn't left out. Technology has helped manufacturing efficiency during COVID-19. We are now collecting more data than ever before, and this is enabling the next generation of smart manufacturing practices.
The future of big data analytics
Manufacturers are looking toward big data analytics and predictive maintenance for the shop floor, but many are not actively collecting the required data. According to Research and Markets, big data analytics in the manufacturing industry is set to exceed $4.5 billion by 2025!
Why is it that we don't let data tell the real story? Organizations are sitting on vast amounts of data, but they still lack the means to derive relevant insights from their manufacturing process-related data. While traditional business intelligence tools have helped organizations begin to better understand their manufacturing processes, they have done little to empower those organizations to take operational control and execute better because of the insights they gain.
"Did you know that a staggering 15 petabytes of new data are generated every day? If you're trying to visualize this, that's equivalent to about 300 million four-drawer filing cabinets of paper. What do businesses do with all of this data?"
- Ryan Raiker, Do you have a Data Hero on your team?
The digital shift has accelerated thanks to COVID-19, and big data is powering the digital transformation of the factory floor. Advancements in technology like machine learning, computer vision, robotics, sensors, cloud computing, and better network infrastructure have demonstrated the ability to increase supply chain resiliency for manufacturers who adopt them. Insights into and control over every aspect of the manufacturing process—purchasing, quality control, machine operation, and maintenance—allow manufacturing leaders to operate with small workforces.
More data is being collected now than ever before, and more manufacturing organizations are starting to understand what can drive digital transformation and real innovation. Many leaders now know where the data lives and understand what they want to do with it. However, they need the right technology to help them move past some hurdles and begin leveraging the benefits from the collection of big data. Technology is available, but many don't know where to find it.
Better understanding manufacturing data
Like any other specialty area, understanding manufacturing process data requires tools that are optimized for the task. Existing tools provide no meaningful help when it comes to understanding and analyzing manufacturing data. These days, manufacturers face a variety of challenges. With tools that are specifically designed for understanding and controlling manufacturing processes, we can gain insights and capabilities not possible before.
A lot of the digital solutions in manufacturing involve predicting problems before they happen so managers can keep facilities at peak capacity. These types of programs include predictive modeling and maintenance of sensors as well as an understanding of past conditions and how they relate to future instances. The latest advancements in leveraging big data for manufacturing include process monitoring software that captures measurement and process data from all machines on the floor. Data is collected across all shifts, and individual machines can be examined in detail to enhance peak performance. These manufacturing software tools are integrated directly into SPC and other reporting systems.
Shop floor managers need technology to detect variances in cycles and sub-cycles and reveal exactly which part of the cycle is causing the problem. This is now possible, as machine learning enables technicians to maintain tools predictively rather than create unexpected downtime when tools need to be repaired or replaced. Thanks to historical data, deviations trigger an alarm so the cause can be addressed immediately.
No amount of manual process analysis and design work can ensure that people will work the way you expect, so paying consultants tens of thousands of dollars a week won’t necessarily solve your problem. To truly understand how your manufacturing processes perform and avoid backsliding, you need to monitor what happens. You have to understand, for example, how long certain methods take, whether people adhere to the standards, and how many different variations in the manufacturing process occur.
Manufacturing Execution Systems have long provided users and management teams with key information about the manufacturing process, but between advancements in technology and the collection of big data, MES solutions are now available that can collect production and process data across a range of systems.