With Industry 4.0 taking the lion’s share of headline space, smart manufacturing technologies are bigger than ever. For many manufacturers, these concepts can seem more than just a little intimidating, if not worthy of some cautious scepticism. Fortunately, there are manufacturing technologies that have been proven by years of practical application. Industry 4.0 concepts support them with more informed data and more efficient process improvements. We’re looking at you EDI. The concept of a digital twin is another one of these manufacturing technologies anyone can implement to improve operations.
What Is A Digital Twin?
The term “digital twin” refers to a digital replica of a physical asset. This asset can be any common hardware found on any factory floor. This includes heavy equipment, a smart machine, a robot, a work cell, an inspection station or a manufacturing line. These “Physical Twins” are anything that can provide data to the Digital Twin for interpretation. Connection bridges the physical and digital to create a cyber-physical system, whereby data flows through and informs a process.
The digital twin concept can be broken down into three distinct parts:
- a physical product
- a digital/virtual product
- connections between the two products
Digital Twins birthed in the Apollo Missions
The digital twin is a true example of the Industrial Internet of Things (IIoT) at work.however, the concept outdates the term Internet of Things by decades. The term was coined by John Vickers of NASA in a 2010 Roadmap Report. however, the concept goes back even further in the NASA toolbox when the Apollo program utilized digital twins of the Command Module, Lunar Module and Lunar Rover to carry out maintenance, support, and troubleshooting activities.
How Are Digital Twins Used In Manufacturing?
As we stated before, the connection between physical and digital twin creates a cyber-physical system that feeds real-time performance data to operators, analysts, and managers.
Individuals and groups fulfilling these roles within an organization can leverage industry 4.0 concepts to analyze and interpret data to make sound predictions and carry out appropriate actions. Here, Industrial Internet of Things (IIoT), Artificial Intelligence (AI), and Machine Learning (ML) all come together to troubleshoot, raise alarms to identify potential problems, view maintenance conditions, support the various condition-based maintenance required to maintain seamless operations.
How Do The Components Of A Digitial Twin Work Together?
Analytics, Industrial Internet of Things (IIoT), Artificial Intelligence (AI), and Machine Learning (ML) technologies all have a hand in making Digital Twins work for manufacturers. Here’s how they come together to deliver leaps in process and operational improvement:
- Industrial Internet Of Things (IIoT): Connects the physical and digital systems to provide accurate data in real-time.
- Artificial Intelligence (AI): Intelligent software analyzes the data, provides an interpretation of what is physically taking place, what outcomes or problems may arise, and what actions should be carried out to maximize performance.
- Machine Learning (ML): Builds on scenarios, both experienced and potential, to execute analysis more quickly and orchestrate improvements for the physical counterpart, ideally, without human intervention.
- Analytics: Additional tools that simplify the data to communicate, diagnose, predict and prescribe actions to optimize the operation of physical systems.
How Do Digital Twins Optimize Or Diagnose To Improve Operations?
By leveraging the data they receive, Digital Twins get a snapshot of how machinery or other physical systems operate throughout a process. The data serve to build a picture of what is good performance and what is bad or what is streamlined and what is bottlenecked.
Optimization comes into the picture when historical data can inform future operations to “say” this didn’t work well last time, let’s try something else. One example of how digital twins are used in optimizing machines emerges with the maintenance of power generation equipment such as power generation turbines, jet engines and locomotives. How can we make this piece of machinery more efficient? Let’s look at the historical data and improve on past performance by trying other tweaks our engineers and machinists can implement. Or, better yet, what hypothetical concepts can we experiment within the digital realm? The same is true for Enterprise Resource Planning (ERP) software. In enterprise architecture (EA), architects create EA blueprints as a digital twin for the organization.
A more relatable example may be found in autonomous vacuums. Many homes now employ robotic servants to clean while their owners are away. Digital twin technologies could effectively map the optimal vacuum path of a room and then employ that strategy to mitigate wasted energy and clean living spaces more quickly.
Diagnostics are another huge component of digital twins’ utility. By referencing historical data for machinery, a digital twin may be able to predict maintenance intervals, make service recommendations, and ensure downtime is kept to a minimum. In his case, the digital twin isn’t relegated to just one machine or just one plant. IIoT technology can connect like-machines across an organization or several organizations to show a more complete picture of how machines perform under an array of conditions. This includes when they are most likely to breakdown or characteristics that can indicate a serious issue is looming on the horizon.
Leveraging The Digital Twin
To be certain, a digital twin and the technological concepts it relies on are no substitute for a skilled workforce. Those autonomous vacuums don’t dust or polish just yet. However, digital twins can inform and supplement your skilled workers to better utilize their machinery and improve operations overall. By now, it should be clear that implementing the concept of a Digital Twin within your organization can yield real benefit. Consider adding this invaluable tool as a complement to your business operations and remain competitive.
Epicor ERP delivers this technology in the form of a production environment. This component of the solution allows users to map their entire production process or even back-office process for simulated activities. This way, any company using Epicor ERP can experiment with their mad scientist and what if we tried this ideas on how to improve operations without the hassle of interrupting day-to-day operations. The result is a fine-tuned approach to process improvement that can be utilized in real-time after pushing the changes into the live Epicor ERP environment.
About Encompass Solutions
Encompass Solutions, Inc. is an ERP consulting firm, NetSuite Solution Provider and Epicor Gold Partner that offers professional services in business consulting, project management, and software implementation. Whether undertaking full-scale implementation, integration, and renovation of existing systems or addressing the emerging challenges in corporate and operational growth, Encompass provides a specialized approach to every client’s needs. As experts in identifying customer requirements and addressing them with the right solutions, we ensure our clients are equipped to match the pace of Industry.