TY - GEN
T1 - Maturity Levels for Automation Software Engineering in automated Production Systems
AU - Vogel-Heuser, Birgit
AU - Neumann, Eva Maria
AU - Fischer, Juliane
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - The amount of software and its development effort in machine and plant manufacturing is continuously increasing to currently up to 35-50% of the development personnel. However, achieving mature automation software that is adaptable to changed requirements during runtime for lifetimes of several decades still poses major challenges for machine and plant manufacturing companies. Previous industrial case studies show that companies deal with these challenges with different success. However, maturity levels are still missing to categorize and compare companies' automation software and development processes and, thus, enable a cross-company benchmark. Available approaches from computer science to categorize software maturity often do not consider the characteristics of automation software or only focus on individual aspects of maturity. Thus, this paper introduces the results of a large-scale questionnaire study with 61 German machine and plant manufacturing companies to enlarge an established maturity classification with quantitative and qualitative results on success factors in the design of automation software.
AB - The amount of software and its development effort in machine and plant manufacturing is continuously increasing to currently up to 35-50% of the development personnel. However, achieving mature automation software that is adaptable to changed requirements during runtime for lifetimes of several decades still poses major challenges for machine and plant manufacturing companies. Previous industrial case studies show that companies deal with these challenges with different success. However, maturity levels are still missing to categorize and compare companies' automation software and development processes and, thus, enable a cross-company benchmark. Available approaches from computer science to categorize software maturity often do not consider the characteristics of automation software or only focus on individual aspects of maturity. Thus, this paper introduces the results of a large-scale questionnaire study with 61 German machine and plant manufacturing companies to enlarge an established maturity classification with quantitative and qualitative results on success factors in the design of automation software.
KW - automated Production Systems
KW - machine and plant manufacturing
KW - software maturity
UR - http://www.scopus.com/inward/record.url?scp=85145773526&partnerID=8YFLogxK
U2 - 10.1109/INDIN51773.2022.9976112
DO - 10.1109/INDIN51773.2022.9976112
M3 - Conference contribution
AN - SCOPUS:85145773526
T3 - IEEE International Conference on Industrial Informatics (INDIN)
SP - 618
EP - 623
BT - 2022 IEEE 20th International Conference on Industrial Informatics, INDIN 2022
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 20th IEEE International Conference on Industrial Informatics, INDIN 2022
Y2 - 25 July 2022 through 28 July 2022
ER -