AMS Speaker Spotlight: Contextual Data: Solving AM Challenges – 3DPrint.com

Authentise Founder and CEO, Andre Wegner, will participate in Additive Manufacturing Strategies 2022, Panel 2: Workflow and software for AM.

Additive manufacturing has made great strides over the years, but it still faces common issues. Intuitive data can provide the necessary solutions, but only if one changes direction. Instead of big data, think about contextual data. Authentise has done just that over the past decade through its 3Diax and aMES platforms.

Contextual data is the end goal when it comes to workflow software and is defined as basic information that enables better understanding of processes. Breaking this down further requires data used in Industry 4.0, such as sensor data, and data outside of automated channels, such as operator data. Context data then aggregates these data points into the “context” of the part. This “context” can provide deeper insight into producing parts more efficiently.

Workflow software provides the means to collect and use contextual data while being central to the efficient running of your operations. Such systems (often referred to as Manufacturing Execution Systems or “MES” for short) offer many benefits, ranging from increased return on investment to changing the flow of data in factories. In addition to these, other benefits are still being researched today. Like the idea of ​​connectivity – the interconnection of platforms, systems and applications.

It’s the opposite of the data silos that still dominate the Industry 4.0 landscape. These are situations where the software does not allow data transfers between departments or projects, which complicates internal processes. In other words, it creates a huge waste of time for everyone involved. In additive manufacturing, where projects are unique and usually fast-paced, avoidable wasted time can lead to undesirable problems. This is where workflow software comes into play.

Unmet needs of Industry 4.0

Workflow software is essential to work well in a high-mix, low-volume industry like additive manufacturing. For example, orders for similar parts are much easier to manage with shared data from past orders or other departments. Here, contextual data can create closed data loops to counter any redundancy encountered.

Now let’s dive into some specific functions offered by contextual data. First, we have real-time data tracking for workflow software users. This provides customers with transparency to check the progress of their projects, all with the benefit of completing the entire process on a comprehensive schedule. This then allows for better understanding via local background data.

Representation of the aMES platform.

Two other unique features are digital benchmarking and piece idea.

Digital Benchmarking uses process data and automated data to determine the efficiency of system operations, as many project metrics cannot be determined (such as time to completion) by individuals alone. sensors. Benchmarking complements traditional data by running self-checks on metrics that may not be monitored.

Idea-to-Part is the union of several modules to allow customers to enter design values. While guiding the customer through a series of optimizations that affect their order. In post-production, the use of manufacturing data is returned to the design modules. This creates a closed loop of data that enables re-iteration of design, reduces time spent designing new products, the cost of initial failure, and early determination of quality.

Contextual data, agile manufacturing, and high-mix, low-volume industries mesh seamlessly. With agile manufacturing, companies can manage the ever-changing needs and wants of customers. This requires flexibility that other platforms besides workflow software cannot provide. Contextual data creates the foresight and the path to make these changes seamlessly. High-mix, low-volume industries like additive manufacturing have to deal with unstable supply chains, customers, policies and markets. As uncertainty grows, businesses need more support to turn these trials into opportunities.

Now that the importance of workflow software and contextual data has been established, the next question to ask is who can offer a solution. The Authentise platform has done what is mentioned and more for many businesses, from established companies like Boeing to start-ups getting their foot in the door. For Boeing, the aThe MES platform has reduced the time it takes to process an order by 80% while decreasing construction preparation time by an average of 95%. This software creates an all-in-one process from part specification to printing and finally delivery, all with the benefit of being transparent so customers can track their orders.

Workflow software, combined with the power of contextual data, will be the future of all things manufacturing.