This enables organizations to test desired changes to their production process before full implementation without interfering with the existing production chain. It also allows companies to input real-time operating data into their digital models to forecast when components of the process will need to be repaired or replaced, identify single points of failure, and otherwise find ways to increase the operating efficiency of their manufacturing process.
As every modern industry has learned, ones and zeros often cost significantly less than iron and steel. Being able to test out and tweak aspects of one’s manufacturing chain without having to purchase and implement physical equipment to test out can result in significant savings to time and resources. An organization can simulate the use of different manufacturing equipment, new sourcing options, alternative materials, and more without touching or interfering with their existing real-world process. Leaders can also test out different operating parameters to see what their peak output looks like and find out which factors result in maximized efficiency to meet their organizational goals.
Bottom line, manufacturing digital twins can answer what works and what doesn’t without tampering with existing processes in order to help leaders make smart decisions.
But, What About Manufacturing Execution Systems?
If the concept of using data to improve the manufacturing process sounds familiar, that is because many organizations are already doing it through the use of an MES or, Manufacturing Execution System. An MES uses real time data to track how equipment is performing in order to increase throughput and reduce costs. Sounds a lot like a digital twin, right?
In actuality, an MES can be considered a type of simple digital twin. However, here is the key difference. An MES (typically) is not a wholistic and centralized representation of an entire manufacturing process. With a true digital twin, all of the data being produced within the production chain is collated into a working model that captures a comprehensive view of the system as a whole for easier testing and visualization. An MES is a great foundational starting point for a manufacturer to develop a digital twin.
A digital twin can be considered the next step or evolution of an MES in order for a manufacturer to adapt to the changing technological capabilities of the world around them.
Digital twins are increasingly becoming a standard method of business intelligence and process improvement. In fact, Gartner listed the digital twin as one of the top ten strategic tech trends in 2017. As data becomes increasingly more critical to organizational decision making, having a wholistic virtual model to test real world effects is the most effective tool to stay innovative and successful. To learn more about how digital twins and IoT can be used to improve your processes, reach out to us today.