Abstract
The contemporary market creates a demand for continuous improvement of production, service, and management processes. Increasingly advanced IT technologies help designers to meet this demand, as they allow them to abandon classic design and design-testing methods in favor of techniques that do not require the use of real-life systems and thus significantly reduce the costs and time of implementing new solutions. This is particularly important when re-engineering production and logistics processes in existing production companies, where physical testing is often infeasible as it would require suspension of production for the testing period. In this article, we showed how the Digital Twin technology can be used to test the operating environment of an autonomous mobile robot (AMR). In particular, the concept of the Digital Twin was used to assess the correctness of the design assumptions adopted for the early phase of the implementation of an AMR vehicle in a company’s production hall. This was done by testing and improving the case of a selected intralogistics task in a potentially “problematic” part of the shop floor with narrow communication routes. Three test scenarios were analyzed. The results confirmed that the use of digital twins could accelerate the implementation of automated intralogistics systems and reduce its costs.
Highlights
Sophisticated IT system solutions open up new horizons for the development of technical measures applicable in diverse areas of the economy [1,2]
The term Industry 4.0, which alludes to the past industrial revolutions, stands for the newest revolution, which essentially involves the digitization of processes and their components [5]
The introduction of technologies and solutions associated with the Internet of Things (IoT), Cloud Computing, and Cyber-Physical Systems drives the Fourth Industrial Revolution [7]
Summary
Sophisticated IT system solutions open up new horizons for the development of technical measures applicable in diverse areas of the economy [1,2]. Even if the required data could be collected, there still remain additional challenges associated with the highfidelity model approach, which include data storage management and constraints on data transfer, computing power, and decision support time For these reasons, a digital twin is assumed to be a virtual representation of a specific physical system. By tracking and modeling changes that take place over time in the virtual representation as a function of input variables to the system, one can approximate the past, present, and future states in order to control the decision process [10] In this context, digital twins are used to model systems and to collect and analyses information about processes and people, and can be employed to solve complex problems.
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