TY - GEN
T1 - Introduction of an Assistant for Low-Code Programming of Hydraulic Components in Mobile Machines
AU - Neumann, Eva Maria
AU - Haben, Fabian
AU - Krüger, Marius
AU - Wieringa, Timotheus
AU - Vogel-Heuser, Birgit
N1 - Publisher Copyright:
© 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.
PY - 2024
Y1 - 2024
N2 - The increasing functionality of automation software in complex mechatronic systems such as construction machinery is a major challenge for companies to remain competitive. A major difficulty is that the software development in construction machinery often involves employees from different disciplines who have technological expertise about the process but little software background. Low-code platforms allow software to be developed intuitively without extensive programming knowledge. However, in mechatronics, the resulting programs are often facing the so-called scaling-up problem that occurs in case highly complex technical processes are implemented using graphical programming languages. This paper thus presents an assistant that supports the programming of automation software on low-code platforms to reduce the complexity of the resulting code. Static code analysis and machine learning are combined to enable predictions about software blocks to be used. For the example of the low-code platform eDesign, a graphical programming platform developed by HAWE Hydraulik SE, it is shown how users of the platform can be assisted in creating maintainable, reusable automation software in the construction machinery sector.
AB - The increasing functionality of automation software in complex mechatronic systems such as construction machinery is a major challenge for companies to remain competitive. A major difficulty is that the software development in construction machinery often involves employees from different disciplines who have technological expertise about the process but little software background. Low-code platforms allow software to be developed intuitively without extensive programming knowledge. However, in mechatronics, the resulting programs are often facing the so-called scaling-up problem that occurs in case highly complex technical processes are implemented using graphical programming languages. This paper thus presents an assistant that supports the programming of automation software on low-code platforms to reduce the complexity of the resulting code. Static code analysis and machine learning are combined to enable predictions about software blocks to be used. For the example of the low-code platform eDesign, a graphical programming platform developed by HAWE Hydraulik SE, it is shown how users of the platform can be assisted in creating maintainable, reusable automation software in the construction machinery sector.
KW - assistance system
KW - construction machinery
KW - data mining
KW - low-code
KW - mobile machines
KW - static code analysis
KW - visual programming languages
UR - http://www.scopus.com/inward/record.url?scp=85174450023&partnerID=8YFLogxK
U2 - 10.1007/978-3-031-44021-2_13
DO - 10.1007/978-3-031-44021-2_13
M3 - Conference contribution
AN - SCOPUS:85174450023
SN - 9783031440205
T3 - Lecture Notes in Civil Engineering
SP - 115
EP - 122
BT - Construction Logistics, Equipment, and Robotics - Proceedings of the CLEaR Conference 2023
A2 - Fottner, Johannes
A2 - Nübel, Konrad
A2 - Matt, Dominik
PB - Springer Science and Business Media Deutschland GmbH
T2 - International Conference on Construction Logistics, Equipment, and Robotics, CLEaR 2023
Y2 - 9 October 2023 through 11 October 2023
ER -