Making smart manufacturing easy

It’s no secret that #SmartManufacturing is hard. In fact, our work over the past decade has helped us form a deeper understanding of and appreciation for the challenges faced by manufacturers when it comes to implementing scalable machine learning approaches. The hurdles are manifold, from time-consuming prep work and intricate tuning processes to the complex landscape of diverse, unique, and changing problems.?

Yet we’ve often urged manufacturers seeking greater operational efficiency and improved business outcomes to turn their attention to the long tail – the intricate web of unique problems where the most value can be found. Several factors impede the pursuit of the long tail. Firstly, the painful setup process required to get AI running often becomes a roadblock. Identifying thresholds and grouping variables for analysis is a time-consuming endeavor that operational teams would rather avoid. A lack of problem recurrence also makes analysis all the more complex. Secondly, connectivity poses another overlooked obstacle, with the time-consuming integration of plant systems into analytical systems requiring extensive IT work. The million-dollar question then is – how can we overcome such challenges? The simple answer is an out-of-the-box, ready-to-integrate intelligent, user-friendly software system.

Falkonry’s recently announced seamless compatibility with iba provides a ready-to-integrate solution for the data challenge. By seamlessly integrating with iba, and other off-the-shelf industrial data middleware, we remove the upfront struggles of software development and policies surrounding network firewalls. This means #manufacturing operations leaders can focus on what is in their data and extract value from it, rather than grappling with data transfer logistics. As for the arduous prep work we mentioned earlier – Falkonry works out-of-box and removes the extensive upfront manual efforts required to get #AI up and running, eliminating the need for time-consuming data labeling, structuring, and feature engineering. Additionally, the system continually adapts to behavior changes automatically, so now your operations team can focus on what truly matters – extracting insights from your data to optimize plant operations.?

If this resonates with you, let’s talk .

In other news

Falkonry and iba AG join hands. Falkonry AI suite is “iba-compatible” making it easy for metals, energy, and pulp and paper producers to benefit from line-scale AI #analytics .?This exciting partnership enables industrial organizations to easily transition to data-driven #automation by bringing high-resolution data from multiple sources in the plant, including legacy plant systems.

New Falkonry paper published at AIST 2023.?Our latest technical paper describes the inner workings of our new AI system designed to independently monitor all the key parameters of a plant's machinery and detect any deviations that may occur. By automatically identifying these anomalies, the AI helps plant teams make informed decisions about production and maintenance. Read the paper for real-world examples of how this AI has been successfully used in commercial steel plants, along with the workflow followed by engineers.

Original Content

Organizing Signals in Falkonry. Falkonry utilizes time series data originating from industrial systems and assets to produce insights at the system-of-system level. Read on to discover how we are able to leverage signal tree organization to make common tasks easier and AI-powered analysis smarter.

Anomaly Detection: The low-hanging fruit of AI. Find out how anomaly detection overcomes the challenges associated with labor-intensive approaches to AI, making it the low-hanging fruit of AI – capable of delivering substantial benefits at low risk and effort.?

Interesting Reads

The essential components of digital transformation. Digital transformation is not just about investing in new technologies or copying the best practices of others. The true essence of digital transformation is to become a data-driven organization, ensuring that key decisions, actions, and processes are strongly influenced by data-driven insights, rather than by human intuition.

A manufacturing investment supercycle is starting. New investments are taking place in U.S. heavy industry that are set to shape the economic landscape for years to come. Understanding how this boom plays out and keeping a competitive edge through the remainder of this decade will be crucial for manufacturers.