Search and selection process for categorization of data attributes, core techniques and challenges on the topic of enabling smart-troubleshooting in Industry 4.0
Abstract:
A crucial element of Industry 4.0, is the utilization of smart devices that generate log files. Log files are key components containing data on system operations, faults ...Show MoreMetadata
Abstract:
A crucial element of Industry 4.0, is the utilization of smart devices that generate log files. Log files are key components containing data on system operations, faults (unexpected glitches or malfunctions), errors (mistakes or incorrect actions), and failures (complete breakdowns or non-functionality). This paper presents a systematic mapping study analyzing research conducted on log files for smart-troubleshooting in Industry 4.0. To the best of our knowledge, this is the study that aims to identify research trends, log file attributes, techniques, and challenges involved in log file analysis for smart-troubleshooting. From an initial set of 941 potentially relevant peer-reviewed publications, 74 primary studies were selected and analyzed using a meticulous data extraction, analysis, and synthesis process. The results of the study demonstrate that the majority of research has focused on developing algorithms for log analysis, with machine learning being the most commonly used approach. The smart-troubleshooting encompasses a range of activities and tools that are essential for collecting failure data generated by diverse interconnected devices, conducting analyses, and aligning them with troubleshooting instructions and software remedies. Moreover, the study identifies the need for further research in the areas of real-time log analysis, anomaly detection, and the integration of log analysis with other Industry 4.0 technologies. In conclusion, our study provides insights into the current state of research in log analysis for smart-troubleshooting in Industry 4.0 and identifies areas for future research. The use of smart devices generating log files in Industry 4.0 highlights the importance of log file analysis for troubleshooting purposes. Further research is needed to address the challenges and opportunities in this field to integrate log analysis with other Industry 4.0 technologies for performing more efficient and effective troubleshooting.
Search and selection process for categorization of data attributes, core techniques and challenges on the topic of enabling smart-troubleshooting in Industry 4.0
Published in: IEEE Access ( Volume: 12)
Funding Agency:
School of Innovation, Design and Engineering, Mälardalen University, Eskilstuna, Sweden
Sigma Technology Information, Stockholm, Sweden
Sania Partovian received the B.Sc. degree in computer engineering, in 2008, and the M.Sc. degree in mechatronics engineering, in 2011. She is currently pursuing the Ph.D. degree in computer science with Mälardalan University. She worked in the industry and academia for more than ten years. Her research interests include smart troubleshooting and industry 4.0.
Sania Partovian received the B.Sc. degree in computer engineering, in 2008, and the M.Sc. degree in mechatronics engineering, in 2011. She is currently pursuing the Ph.D. degree in computer science with Mälardalan University. She worked in the industry and academia for more than ten years. Her research interests include smart troubleshooting and industry 4.0.View more
School of Innovation, Design and Engineering, Mälardalen University, Eskilstuna, Sweden
Alessio Bucaioni received the Ph.D. degree from Mälardalen University, in 2018. From 2014 to 2020, he worked for the automotive and industrial automation industries. He is currently an Assistant Professor in computer science with Mälardalen University. His research interest includes the development of complex software-intensive systems from software architecture to model-driven development.
Alessio Bucaioni received the Ph.D. degree from Mälardalen University, in 2018. From 2014 to 2020, he worked for the automotive and industrial automation industries. He is currently an Assistant Professor in computer science with Mälardalen University. His research interest includes the development of complex software-intensive systems from software architecture to model-driven development.View more
School of Innovation, Design and Engineering, Mälardalen University, Eskilstuna, Sweden
Francesco Flammini (Senior Member, IEEE) received the master’s (cum laude) and Ph.D. degrees in computer engineering from the University of Naples Federico II, Italy, in 2003 and 2006, respectively. He has worked for 15 years in the industry (Ansaldo STS and IPZS), in verification and validation, cyber-security, and innovation management. Since 2018, he has been an Associate Professor with Linnaeus University, Sweden. Sin...Show More
Francesco Flammini (Senior Member, IEEE) received the master’s (cum laude) and Ph.D. degrees in computer engineering from the University of Naples Federico II, Italy, in 2003 and 2006, respectively. He has worked for 15 years in the industry (Ansaldo STS and IPZS), in verification and validation, cyber-security, and innovation management. Since 2018, he has been an Associate Professor with Linnaeus University, Sweden. Sin...View more
Sigma Technology Information, Stockholm, Sweden
Johan Thornadtsson is the VD/CEO of Sigma Technology Information, the Daglig Leder/CEO of Sigma Technology Norway, and a Board Member of Branschorganisationen för Teknikinformation (BOTI), Sigma Technology Sweden AB.
Johan Thornadtsson is the VD/CEO of Sigma Technology Information, the Daglig Leder/CEO of Sigma Technology Norway, and a Board Member of Branschorganisationen för Teknikinformation (BOTI), Sigma Technology Sweden AB.View more
Contents School of Innovation, Design and Engineering, Mälardalen University, Eskilstuna, Sweden
Sigma Technology Information, Stockholm, Sweden
Sania Partovian received the B.Sc. degree in computer engineering, in 2008, and the M.Sc. degree in mechatronics engineering, in 2011. She is currently pursuing the Ph.D. degree in computer science with Mälardalan University. She worked in the industry and academia for more than ten years. Her research interests include smart troubleshooting and industry 4.0.
Sania Partovian received the B.Sc. degree in computer engineering, in 2008, and the M.Sc. degree in mechatronics engineering, in 2011. She is currently pursuing the Ph.D. degree in computer science with Mälardalan University. She worked in the industry and academia for more than ten years. Her research interests include smart troubleshooting and industry 4.0.View more
School of Innovation, Design and Engineering, Mälardalen University, Eskilstuna, Sweden
Alessio Bucaioni received the Ph.D. degree from Mälardalen University, in 2018. From 2014 to 2020, he worked for the automotive and industrial automation industries. He is currently an Assistant Professor in computer science with Mälardalen University. His research interest includes the development of complex software-intensive systems from software architecture to model-driven development.
Alessio Bucaioni received the Ph.D. degree from Mälardalen University, in 2018. From 2014 to 2020, he worked for the automotive and industrial automation industries. He is currently an Assistant Professor in computer science with Mälardalen University. His research interest includes the development of complex software-intensive systems from software architecture to model-driven development.View more
School of Innovation, Design and Engineering, Mälardalen University, Eskilstuna, Sweden
Francesco Flammini (Senior Member, IEEE) received the master’s (cum laude) and Ph.D. degrees in computer engineering from the University of Naples Federico II, Italy, in 2003 and 2006, respectively. He has worked for 15 years in the industry (Ansaldo STS and IPZS), in verification and validation, cyber-security, and innovation management. Since 2018, he has been an Associate Professor with Linnaeus University, Sweden. Since 2020, he has been a Full Professor of computer science with Mälardalen University, Sweden, with a focus on cyber-physical systems. He is currently a Professor of trustworthy autonomous systems with the University of Applied Sciences and Arts of Southern Switzerland, where he is affiliated with the Dalle Molle Institute for Artificial Intelligence. He is an ACM Distinguished Speaker, an IEEE Distinguished Visitor, the Member-at-Large of the IEE SMC BoG, and the Chair of the IEEE SMC TC on Homeland Security.
Francesco Flammini (Senior Member, IEEE) received the master’s (cum laude) and Ph.D. degrees in computer engineering from the University of Naples Federico II, Italy, in 2003 and 2006, respectively. He has worked for 15 years in the industry (Ansaldo STS and IPZS), in verification and validation, cyber-security, and innovation management. Since 2018, he has been an Associate Professor with Linnaeus University, Sweden. Since 2020, he has been a Full Professor of computer science with Mälardalen University, Sweden, with a focus on cyber-physical systems. He is currently a Professor of trustworthy autonomous systems with the University of Applied Sciences and Arts of Southern Switzerland, where he is affiliated with the Dalle Molle Institute for Artificial Intelligence. He is an ACM Distinguished Speaker, an IEEE Distinguished Visitor, the Member-at-Large of the IEE SMC BoG, and the Chair of the IEEE SMC TC on Homeland Security.View more
Sigma Technology Information, Stockholm, Sweden
Johan Thornadtsson is the VD/CEO of Sigma Technology Information, the Daglig Leder/CEO of Sigma Technology Norway, and a Board Member of Branschorganisationen för Teknikinformation (BOTI), Sigma Technology Sweden AB.
Johan Thornadtsson is the VD/CEO of Sigma Technology Information, the Daglig Leder/CEO of Sigma Technology Norway, and a Board Member of Branschorganisationen för Teknikinformation (BOTI), Sigma Technology Sweden AB.View more