All specialty chemical manufacturers want to consistently meet their customers’ order fulfillment expectations — including the ability to fulfill orders with unusually short lead times. Arguably the most important element in doing this is the ability to produce right-first-time products with maximum efficiency and at minimum cost.

 

We’ve previously discussed the enablers to right-first-time, so let’s assume here that the process is reasonably well understood and controlled.

 

Even with this optimistic outlook, there are still events to be managed throughout any given week or day. This includes those that can be predicted (such as planned equipment maintenance) and those that cannot (such as unplanned emergency orders from your biggest customer or equipment failures, to name just a few).

 

Model-based scheduling enables you to easily create optimized schedules when faced with both planned and unplanned events. Since these models represent the full complexity and optionality of a manufacturing operation, including production rates, constraints, efficiencies, set-up times, sequencing, and site logistics, they can be used to determine the optimal way to manage a disruptive event.

 

To tap into the full power of model-based scheduling, you have to be able to:

 

• Leverage your MES system to automate event recognition

• Subsequently inform the scheduler/scheduling model as soon as possible via automated or manual means, in order to modify the schedule as necessary

• Update and dispatch the resulting changes to orders and the associated raw materials, recipes, operating procedures and production targets via workflow automation, also coming from your MES systems

 

It’s important to note that model-based scheduling is subject to its own vulnerabilities — in particular, a failure to update the model to reflect process changes due to conditions changing with time. But, given all the real-time data collected, we will soon see model-based schedules that are auto-tuned by using MES systems to monitor for changes in the average and anticipated variances of key parameters, and updating them accordingly.

 

We have seen specialty chemicals producers achieve an improvement of 8 to 12 percent in on-time order fulfillment by ramping up their customer responsiveness — aided by production scheduling and manufacturing execution solutions from AspenTech. The greater operational agility and flexibility gained from these systems is directly contributing to improved customer outcomes for chemical companies around the world!

 

 

To learn more about how model-based scheduling and other best practices can deliver bottom-line results, read our recent white paper Manufacturing Excellence in Specialty Chemicals: Six Essential Levers.