Belt conveyors are complex machines that require all components and parts to work together in a harsh and demanding operating environment. A major challenge in designing, building, and operating conveyors is the difficult truth that the real-life operation and performance of a conveyor can differ from design expectations. Even identical conveyors, when installed and operated side-by-side, may see different performance issues. Meeting a client’s operation expectations is always a challenge for belt conveyor designers, and the many design variables and complex operating conditions can easily bring confusion and get in the way of the clear goal to have the conveyor transport the required amount of material from point “A” to point “B” reliably.
The concept of conventional reliability prediction requires information, and a considerably amount of these data comes from the real system that is operating. Failure data, performance history and other maintenance/operation issues are of utmost importance to drive the reliability. True system reliability comes from quality-of-design/manufacture and operating/maintenance conditions. When a conveyor system performs poorly, it is all too easy for the designer to blame operations, and for the operations to blame the design. There is a clear gap between design engineering and operations/maintenance. The more well-known the operating conditions are, the more cost-effective decisions can be made, without sacrificing reliability. Knowing exactly how each component responds to every operating condition and what effect each design decision will have on operations, opens the door to the next level of belt conveyor operation and maintenance. The truth is that when design and operation do work together, there is a lot that can be improved. Here is where the digital twin plays an important and decisive role.
thyssenkrupp’s Belt Conveyor Digital Twin
thyssenkrupp, in partnership with the North American-based Overland Conveyor Company (OCC), have developed a Digital Twin for belt conveyors, using the powerful and well-known Belt Analyst™ software as the framework. The goal of the conveyor Digital Twin is to enable active operating feedback so the conveyor can be continually evaluated, to ensure the conveyor system is operating as designed. The combination of a reputed belt conveyor tool with the know-how from decades of experience fills the gap between the design and operation of belt conveyors perfectly. This continuous learning about the assets particularities drives operational decisions and innovations in a precise and faster manner, as the industry requires.
How does thyssenkrupp’s digital twin work?
thyssenkrupp’s Digital Twin bridges the gap between operation/maintenance and asset design, enabling a complete understanding of the behavior of every major component against the changes in the real operation variables. These real-time analyses brings up the results immediately, enabling a faster and more accurate decision-making process. A classic example is the discussion whether it is the design that has to be changed or the operational parameters that have to be adjusted.
The literature defines a Digital Twin as “a dynamic virtual representation of a physical object or system across its lifecycle, using data to enable understanding, learning and reasoning”. That is exactly how thyssenkrupp’s Digital Twin solution works.
Practically speaking, the following steps holistically describe thyssenkrupp’s Digital Twin process.
1. Data Model: A dynamic virtual representation of the belt conveyor is modeled in the Belt Analyst - Digital Twin. Every major component and systems data models are already engineered and built-in.
2. Analytics: Calibrate the model in virtual environment by importing real operating data into it and simulating different operating conditions to match reality. thyssenkrupp’s Digital Twin is capable of running various dynamic simulations such as starting/stopping and constant running under different load conditions, due to its physics-based engine which enables a complete understanding of the behavior of the asset. These load analyses are completed for each individual major component of the asset.
3. Knowledge Base: Years of design evaluation knowledge is built into the automated evaluation process to catch when a conveyor is running beyond the design intentions. Furthermore, thyssenkrupp engineers regularly review and evaluate to ensure operating and design change recommendations adhere to expert logic. The decisions are ultimately made by humans. The analysis of all possible improvement solutions is done by experts and recommendations are then made for implemention.
Cases that the thyssenkrupp’s digital twin can be applied
- Conveyor capacity upgrade and/or revamp: The first step in any revamp or upgrade is getting a quality understanding of the limits of the existing system. The Digital Twin creates a perfect benchmark matched to the existing conveyor so that incremental evaluations of capacity increase can be trusted, and clear feedback can be given as to exactly which components need to change to achieve production increase goals.
- Unreliable systems: Conveyors that are constantly failing with chronic problems can benefit from the Digital Twin to find the root causes of the failures.
- Reliable commissioning of new systems: Get instant feedback during the commissioning of a new conveyor as to whether the design is compatible with the operating requirements.
- Power consumption analysis: Analyze the power demand to understand where excess power is being consumed and correct it.