Democratizing Data is the Key to Unleashing Industry 4.0's Potential

In the world of manufacturing, data has become the new gold, and manufacturers are increasingly recognizing its immense value in their daily operations.

However, the challenge isn't a lack of data—it's often an overwhelming abundance. The real difficulty lies in interpreting and analyzing this data effectively to make smarter, more informed decisions that drive operational excellence.

Research shows that manufacturers produce 1,800 petabytes of data each year. 

Research shows that manufacturers generate 1,800 petabytes of data annually. To put this in perspective, a single petabyte is equivalent to 500 billion pages of printed text. In fact, the manufacturing industry's data output is double that of the next closest industry.

With data flowing from numerous systems, people, and processes within a facility, manufacturing leaders face the daunting task of harnessing this information effectively. Where should they begin to ensure that their data can guide them to operational gold?

Sorting through different types of data

In addition to the massive amounts of data produced within the manufacturing industry, challenges lie in the vast types of data categories that exist. There is common data, metadata, image data and sensor data, just to name a few. Adding another layer to the challenge of manufacturing data are the isolated silos that prevent information from being distributed – and understood - throughout organizations.

Gathering, organizing, understanding, and disseminating data is often easier said than done. Further complicating this data democratization task is the fact that previous software tools for manufacturers are only point solutions – they were designed to address one problem – managing production. While they may be effective in that one regard, they were never intended to decipher the information gathered in the process.

Death by a thousand SaaS cuts

This challenge that has become more evident over the past 10 to 15 years is what is called “death by a thousand Software as a Service (SaaS) cuts”, or multiple point solutions that don’t talk to each other. Despite being evolved when compared to legacy expensive to maintain on-prem solutions, natively cloud software still often results in manufacturing teams passing around spreadsheets, sending emails, and trying to organize manufacturing data so that it’s comprehensible. 

Is all lost in this quest to modernize at the expense of data still being stuck in siloes? No, in fact there are innovative manufacturers who are employing new architectures to leverage big data and data lake technologies.

Companies like SpaceX, Blue Canyon Technologies and Saronic Technologies have figured out how to democratize access to data. They empower their employees to build applications on top of existing data or APIs within their factories, enabling quicker business solutions. This mindset eliminates the time and resources required for custom solutions or software iterations, accelerating manufacturing improvements.

Introduce your data to an observability layer

What do these manufacturing data solutions look like? What do they mean and how do manufacturers implement them? How do they make data more accessible?

It starts with implementing an observability layer in your manufacturing facility. Democratizing data comes from a bottoms-up perspective that empowers employees at all levels of the organization, instead of a waterfall, or top-down approach. The first layer of processes and machines on a factory floor is where manufacturers need to begin, with the objective of data gathering.

With the gathered data, manufacturers need to publish data through a common Application Programming Interface (API). An API produces error messages and allows developers to build a more resilient system. Acquiring data produced from sensors, creating the right APIs to get all this data in, and then making that data available is the next step.

This process empowers departments from the top down. The production department can request yield reports from quality control personnel before redesigning a manufacturing process. Design can learn its yield numbers and different departments within an organization can empower each other to create more data-driven conversations. When this happens, factories begin to operate more efficiently, leading to more automation.

Implement a data lake strategy

Throughout manufacturing, there are different processes and modalities that organizations use to get automated information into a centralized system. By utilizing data lakes, manufacturers can move all of this data even if it’s occurring within different processes and systems. Through a data lake strategy, APIs can move data without a single source of truth. 

People often confuse a single source of truth with a single piece of software like a large Enterprise Resource Planning (ERP) system or a Product Lifecycle Management (PLM) implementation. With data lakes, manufacturers can still utilize an ERP or PLM application, but they don’t have to restrict employees to a single software. Data can be moved to a larger data lake that adds observability and visualization.

Instead of connecting to an ERP or PLM, you can send the data from a data lake to the overall hardware lifecycle to be used later. This approach enables engineers to develop complete applications on top of the data lake, integrating seamlessly into the manufacturing loop and allowing for real-time iterations in the production process. The advantages are significant: engineers can create not just visualizations, but also powerful applications, all driven by APIs.

In the last year, there has been a massive acceleration of novel applications assisted by new AI technologies where engineers describe the application they want to develop and let ChatGPT or GitHub Copilot create the code. As remarkable as it sounds (and it is), the APIs and data lakes are key to enabling this vision that is part of Industry 4.0. 

Automation and robotics were an amazing development within manufacturing – but the productivity gains they enabled were restricted because of data silos on the manufacturing floor. So, what really is Industry 4.0? It is getting these methods of uploading data out into the broader system and then making it available for your entire workforce to develop additional logic that improves communication.  

The picture becomes clearer in the cloud

Historically, manufacturers have been challenged with moving to the cloud. But a cloud strategy is imminent for the industry because of the massive power available in the cloud. 

There are a variety of cloud configurations, from utilizing a cloud provider for all of your data to keeping all of your data in your data center. At First Resonance, we see manufacturers trending towards using hybrid cloud configurations.

Manufacturers utilizing a hybrid cloud architecture are jumping ahead of competitors because they can empower their workforce in more cost-effective and scalable ways.

The future of manufacturing is exhilarating, but it’s still in its early stages. Innovations made possible by cutting-edge technologies, with data at the forefront, are enabling companies to become more flexible and agile. Manufacturers are now moving data across their entire operations, not just the factory floor, empowering their workforce to make informed decisions through this enhanced process flow.

Real manufacturing magic is happening, and it’s not just hype around AI, machine learning, or virtual reality. Monumental advances are emerging from empowering today’s manufacturing employees with data and intuitive data interfaces. This transformation will revolutionize entire operations and the industry as a whole, propelling manufacturing into the promised future of Industry 4.0.