Decision latency is one of the most significant contributors to inefficiency and cost in pharmaceutical manufacturing. When there is too much time between getting new information about an issue and being able to change course, manufacturers run the risk of unnecessarily discarding batches. At best, delayed decision-making slows production and negatively impacts yield.
However, new automated scheduling platforms are designed to reduce decision latency.
Algorithmic scheduling uses machine learning and automated algorithms to collect and analyze real-time data feeds from the shop floor. The algorithms connect to and constantly monitor manufacturing data – providing automatic schedule updates whenever significant changes need to be made to operations.The result is speed, accuracy and agility.
Algorithm-driven platforms, such as SmartFactory Rx®, are revolutionizing the scheduling paradigm. They enable schedulers to rapidly run multiple types of scenario analysis and predictive analytics when there’s an issue. Highly reliable results are delivered instantly to the operators, reducing the time it takes to respond to schedule changes and dispatching resources to where they are needed most.
The improvements in data achieved through an algorithmic approach also allows for continuous improvement efforts that help manufacturers understand and reduce bottlenecks. For more on how to reduce decision latency, and the benefits of doing so, visit our blog, “Scheduling at the speed of a smartphone app.”
