The Next Frontier for Supply Chain Management: Predicting the Future

The Next Frontier for Supply Chain Management: Predicting the Future

Model and Manage Uncertainty, Shifting Your Scheduling From Reactive to Proactive

February 06, 2019

Rarely in life does one get the chance to be on the cutting edge of technology — at least that’s what I thought before I joined AspenTech! For years AspenTech has been an industry leader in supply chain solutions through our suite of proven supply chain technologies, in use at thousands of manufacturing locations worldwide. The next wave of technology ensures AspenTech will remain a leader for many years to come.

The world of manufacturing is changing. Digitalization is the future, but many organizations don’t have a strategy past cliched mentions of “Industry 4.0,” “empowered employees” or “smart factory.”  The world of digitalization is murky and confusing, with many solution providers offering only a vague glimpse into what digitalization means for manufacturing and supply chains. 

So, what really is possible in the next wave of digitalization? With AspenTech’s technology, we can enable a supply chain to not just manage its past and present — but also to actively predict and manage the future. Seem far-fetched? Maybe it does, but this breakthrough technology really does help transcend time!

A time machine? Essentially, yes. Think of it in terms of the famous DeLorean time machine from Back to the Future: today’s technology acts as the engine that gets your supply chain moving at 88 miles per hour. We didn’t hire Doc Brown (too expensive), and we don’t have any DeLoreans in the parking garage, but what we can do is model and manage uncertainty as if it were just another variable (like shipping commitments or tank capacities).


Technologies Converge for Supply Chain Optimization

In late 2016 AspenTech acquired Mtell, a pioneer in machine learning and prescriptive maintenance. Aspen Mtell® is now part of our Asset Performance Management (APM) group. Aspen Mtell is an advanced technology with the ability to predict when equipment failures will occur, understand why they occur and prescribe what to do to avoid the failure in the future. 

What does this mean for supply chains — or, more specifically, scheduling? Aspen Mtell’s advanced notice of equipment problems, combined with the advanced optimization capabilities of Aspen Plant Scheduler™, changes the very core of how scheduling is done. Machine learning allows a scheduler to identify problems and reroute them before they ever impact the overall supply chain, much in the same way Google Maps reroutes a driver to avoid traffic.

This shift from reactive to proactive minimizes uncertainty and enables a supply chain organization to achieve performance levels that were impossible with traditional planning and scheduling methods!

To learn how Aspen Plant Scheduler and Aspen Mtell utilize existing machine learning and advanced optimization capabilities to fundamentally change the future of scheduling, view this short video demonstration. For more information, check out the related content below or contact


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