The Digital Twin has become a common word, and it is easy to imagine what it means. But what is a Digital Project Twin? We explain the differences and why it will revolutionize project management in mechanical and plant engineering.
What is a Digital Twin and why is this approach too short-thought
Let's start with the basics. A Digital Twin is a digital copy of real tangible or intangible objects and processes. For example, a real factory, its machines, conveyor belts and production processes can be virtually mapped as digital copies. This quite often has the aim and benefit to simulate and calculate various scenarios in configuration or adaption – without affecting or even interrupting the real running production.
The Digital Twin has proven itself for the optimization of production processes. By now, a wide range of industries started working with Digital Twin technology. Unnoticed by many experts, however, is that there is another essential step in the project life cycle - even before the running production. The initial setup of the machine or plant.
It’s time to launch the Digital Project Twin
Even if the future production plant is already designed and simulated virtually during the planning phase, the real construction is still largely analogous. In the worst case, a completely new factory has to be built on a greenfield site. There are no innovative sensors to generate terabytes of measurement data from production steps that are already in progress or to transfer it into the data center via lightning-fast fiber optic cables. Just the spade, the construction site and the CAD drawing on the construction container’s wall.
The Digital Twin thrives on mapping the real processes of the running plant as accurately and realistically as possible. This is the only way to derive valuable insights and concrete recommendations for action. There are interesting parallels to project management here!
Project management in the construction of plant and machinery also depends on a permanent flow of information between the construction site and project headquarters. This is the only way to identify deviations from the schedule or current changes to the plan at an early stage and to take countermeasures. So why is there no Digital Project Twin yet?
Digital project management in machinery and plant engineering
In machinery and plant engineering, just as in the Digital Twin, there is sufficient data. Nowadays, digital planning generates perfect 3D CAD data, simulated in virtual commissioning and with detailed schedules or work breakdown structures and extensive material parts lists. The biggest challenge now is to take this Digital Project Twin from the drawing board to the analog construction site.
No matter how well a project has been planned. On-site conditions or humans create volatile factors that are difficult to consider in advance. In the same way, a Digital Project Twin requires that real project data be permanently captured and added to the virtual copy. Only this way is it possible to obtain as accurate a picture as possible of the current progress and its deviations, problems, and processes.
Now, what is the difference between Twin and Twin?
The Digital Twin aims to reproduce the real factory in production in order of being able to experiment with the virtual clone. The Digital Project Twin, on the other hand, pursues the goal of reflecting as closely as possible the exact project reality of the machine or plant to be built by the time the project is completed. Since the conditions and problems in the project are constantly changing up to the start of production, this is an equally demanding task. However, while modern technologies, such as the automatic creation of point clouds, are already very advanced for the Digital Twin, the foundations for the Digital Project Twin often have to be laid first.
It is obvious that a Digital Twin aims at obtaining a 1:1 image, reducing production times or saving material. Here, the Digital Project Twin rather pursues the intention of saving resources during the set-up process and to show deviations of the reality from the project planning as early as possible. Be it through time savings during assembly, in the collaboration between client, supplier and sub-supplier or indirectly in the project management expenditures itself. It is also conceivable to save paper by digitizing checklists, test or measurement protocols and acceptance processes.
One discipline, however, is shared by both twins. In the area of predictive maintenance, for example, it is possible to calculate failure probabilities through the Digital Twin and with the help of artificial intelligence (AI). A Digital Project Twin could also explain the causes of later failures in production through early, consistent data collection, for example in defect management in the ramp-up phase. Today, there is often still a great deal of confusion about the origins here.
So how do we get to the Digital Project Twin?
The critical point is data, which is just as necessary for a Digital Twin as it is for a Digital Project Twin. If we do not succeed in bringing together the most up-to-date data at a central point and making it available, there can be no representation of real conditions. In the first instance, therefore, project management requires a central system with various interfaces to upstream and downstream applications as well as dedicated solutions for mobile data collection by all project participants directly on site.
The second step is to specifically examine analog processes already on site during the installation of the machine or plant. Is there a specific reason why a digital solution has not yet been found for this or that activity? The recording of defects or progress during the assembly of robots, components or plant parts, for example, can already be excellently mapped today with offline-capable apps. Printed checklists and routing slips for problems and acceptances, should be specifically questioned in the 21st century.
In conclusion, it must be said that creating a Digital Project Twin is not like a sprint, but rather an endurance run. No one succeeds in achieving complete data continuity overnight in just one massive tour de force - certainly not large, multinational corporations. With the central data hub as basic framework, it is better to focus on digitizing smaller processes and areas step-by-step. Later, you jump from trade to trade or department to department. Let's take the first step together - with COMAN software you get an innovative core to live your Digital Project Twin.