Slowing productivity has always been the harbinger for the application of new ideas to deliver growth. Providing enough products to cater to an expanding population was crucial to establishing the first industrial revolution and centuries later humanity found itself in the same situation. Productivity growth across the industrial sector fell from 2.9% from 1995 – 2005 to approximately 1.6% from 2006 – 2014…and once again a paradigm shift was required.
Enter Industry 4.0 and the digital transformation technologies that define it.
The application of digital transformation technologies is expected to assist the industrial sector, with special emphasis on manufacturing, to be agile enough to respond to change. Digital twin solutions fall into this category. The Digital twin will be tasked with leveraging a significant asset many manufacturers overlook; their data.
The ability to capture shop floor data and gain operational insight from it is the foundation of Industry 4.0. Technologies such as IIoT, edge computing hardware, and smart devices make data capture possible while analytical solutions such as simulation modeling software and the digital twin enable real-time analysis.
The digital twin is a virtual replica of physical components, processes, or facility. Unlike the average 3D model/replica, the digital twin forms a cyber-physical entity with the process it mirrors. Thus, interexchange of data across the physical and virtual ream is made possible with a digital twin.
The advanced analytics the digital twin supports helps manufacturers discover hidden bottlenecks and solve complex problems to optimize productivity. There are three major applications of digital twin technology in the manufacturing sector and they include:
The digital twin is applied as a process optimization tool in multiple manufacturing areas which include; capacity planning, predictive maintenance, supply chain analysis, resource allocation etc. For example, an oil and gas service provider tasked with servicing customers across North America struggled with expanding its storage capacity to meet fluctuating demand. Increased customer demand meant storage tanks of different sizes and configurations were required.
To accurately evaluate its capacity requirements, the service provider developed a digital twin of its current facility’s operations. The model implemented a combination of both discrete (batch) and continuous flow object logic to represent the products present within various stages along the pipeline and planned storage facility. System demand, or in this case product batches coming from upstream pipeline supply, were designed to be based on user-defined deterministic input schedules or random events. System infrastructure, i.e. tankage and connections, was designed to be configurable in terms of number deployed and related capacity.
The digital twin assisted the enterprise with visualizing and accurately analyzing the capacity expansion configuration it required to meet increased demand from its customers.
The cyber-physical environment a digital twin provides also support condition monitoring of the production process to capture factory data to optimize productivity. The data from condition monitoring initiatives are applied to developing predictive manufacturing strategies which can improve productivity by 20% and reduce downtime by 70%.
Applying the advanced analytics digital twins provide to manufacturing data produces the insight needed to optimize processes but implementing a digital twin starts with choosing the right technology partner. You can apply the following steps to choose a turnkey digital twin solution:
Managers in charge of selling the idea of deploying a digital twin must understand these costs in other to develop accurate ROI analysis to get C-level executives to support the implementation process.
The digital transformation of manufacturing processes using advanced analytical technologies is a continuous process that must be repeatedly deployed to achieve successful outcomes. Thus, manufacturers must approach the application of digital twins as an ongoing enterprise in partnership with experienced service providers to reap its rich rewards. Request a demo today to learn how the Simio Digital Twin can be applied to improve your manufacturing processes.