Leverage Data and Industrial Data Analytics to Take Advantage of IIoT and Smart Factories
There are billions of physical devices around the world that are now connected to the Internet that collect and share data, and the term used to refer to this phenomenon is the Internet of Things or IoT. Apply IoT to industrial manufacturing and you get the Industrial Internet of Things (IIoT) and the rise of smart factories.
The IIoT has revolutionized manufacturing factories by enabling extremely fast and efficient capture of and accessibility to immense amounts of big data. A challenge you might be facing is how to leverage data and industrial data analytics to take advantage of IIoT and smart factories. How can you leverage the full potential of your plant’s big data in order to maximize operation and stay competitive? You can use industrial data analytics.
In particular, you can use self-service analytics to solve this common industrial manufacturing challenge. This tool can help you work smarter not harder. It analyzes and makes sense out of big data providing insight into complex manufacturing processes. You can then make accurate data-driven decisions based on this insight.
Besides making your job easier and better, you get improved
- regulation compliance
- team collaboration and information sharing
- overall plant operation and profitability.
Analyze Data to Accelerate Progress
When manufacturing production runs into a problem, you need to solve it quickly as downtime is big money in this industry. It could be that the immediate cause is easy to uncover. But to ensure that an issue does not become a recurring problem, it is important to find the root cause. The challenge is differentiating between an immediate cause and a root cause. And this challenge is more intense given the complicated nature of manufacturing processes which makes accurate assessment of a problem difficult.
Again you don’t have to struggle with solving this common industrial manufacturing challenge. You can benefit from process manufacturing software such as self-service analytics. This software analyzes the data to detect operation patterns and anomalies which can be used to uncover root causes.
Moreover, through artificial intelligence and machine learning, this platform has predictive capabilities. Process experts can be alerted to potential problems, giving them time to act and prevent unplanned downtime or equipment failure. And they can share this information between facilities giving other factory teams a heads up.
Forecast and Plan Equipment Maintenance
It’s a great day when production is running smoothly. But what if there is a problem with equipment which leads to unplanned downtime? One malfunction can slow or stop production in minutes. Historically, many of you use a reactive approach, tackling problems at the time they happened. This approach can result in difficulties identifying problems which in turn can increase maintenance costs and lower productivity. A better way is a proactive approach – to use predictive maintenance through self-service analytics.
This platform has the capability to predict and prevent equipment failure. This is a big win for you and a big relief for this challenge. You can gain real-time views and understanding into production, so you can forecast and plan manufacturing processes and equipment maintenance. As a result, unplanned production stops and maintenance can be avoided, reducing costs and improving planning and reliability. Additionally, this process manufacturing software can help prevent small issues from becoming big issues which translates into time-savings and costs reductions and more importantly, into an efficiently running production.
Gain Operational Visibility to Do More with Less
Today, potentially one of the biggest issues in the manufacturing industry is the lack of skilled workers. Process teams must do more with less. Knowing this, you would want your teams to function more cohesively and effectively. And you need operational visibility at all levels allowing you and your teams to do your jobs better and easier to keep the plant running at optimum. Now, you don’t have to struggle with this industrial manufacturing production challenge. Again, self-service analytics can help.
This process manufacturing software gives you more “eyes” on the production letting you and your teams monitor operations 24/7. Another plus is that it allows you to use the full potential of your plant’s data by integrating both time-series and contextual data. With this integration, you can create specific dashboards which together make up production cockpits for live viewing of a plant’s operations.
These cockpits can provide live insight and a better understanding of operational performance. By using production cockpits, all plant stakeholders, from the board room to the control room, can contribute much more effectively to the operation. You and your teams can work more efficiently using the resources at hand. In essence, you can do more with less.
Building a foundation for innovation to leverage data and industrial data analytics to take advantage of IIoT and smart factories is a good idea. You can use a tool like self-service analytics to do this. This tool democratizes data empowering process personnel at all levels to analyze and make sense out of it. Decisions and actions are then based on data and are thus more accurate.
In addition, this tool can set the stage for root cause analysis and predictive proactive maintenance for asset management and can provide you and your teams with operational visibility. Additionally, faced with shortages in skilled workers and pressure to discover problems and act quickly on insights, it allows for a more effective and collaborative, data-driven culture.
In the end, you don’t have to struggle to solve your industrial manufacturing production challenges. You can work smarter not harder. It’s a good idea.