How digital twins enable autonomous operations
February 1, 2022
1. What is a digital twin in manufacturing?
A digital twin is a virtual representation of a potential or actual product, asset or process. As applied to manufacturing operations, a digital twin allows to fully model complex processes to either simulate them in support of trade-off analysis or optimize them in real time, leveraging such techniques as machine learning.
2. What is manufacturing operations management?
Manufacturing Operations Management, or MOM for short, is the critical “layer” of applications between plant level control end the enterprise domain. The typical MOM solution is the MES (Manufacturing Execution System) that typically coordinates production resources to execute a production plan within compliance and quality. Other typical MOM level solutions are Quality Management Systems (QMS) and Logistic Execution Systems (LES) that orchestrate material flows within the plant.
3. How are digital twins used in manufacturing?
Legacy MOM architectures are usually fragmented and poorly integrated, which doesn’t allow to manage the increasing amount of data required to optimize end-to-end operations. Leveraging the power and scalability of the cloud, an operational digital twin federates the disparate data from MOM and Control systems to deliver a constantly updated model of end-to-end operations plant personnel can readily understand. This model can then be used for a wide range of use cases, from classical reporting to event-driven real-time production optimization leveraging AI and ML.
4. The manufacturing benefits of digital twins
Manufacturing leaders are embracing digital twins to drive 360-degree value. Use cases range from predictive maintenance to advanced quality control and energy optimization, adding up to between 15 and 25% OEE optimization depending on industries. But the real value of a digital twin doesn’t readily meet the eye: