Publications and Talks

@article{Angreani2023,
title = {Identifying Essential Driving Factors of Industry 4.0 Maturity Models Using Fuzzy MCDM Methods},
author = {Angreani, Linda Salma; Vijaya, Annas; Wicaksono, Hendro},
year = {2023},
date = {2023-10-24},
journal = {Procedia CIRP},
keywords = {Fuzzy TOPSIS, industry 4.0, industry 4.0 maturity assessment, MCDM},
pubstate = {forthcoming},
tppubtype = {article}
}

@article{Angreani2020,
title = {Systematic Literature Review of Industry 4.0 Maturity Model for Manufacturing and Logistics Sectors},
author = {Angreani, Linda Salma; Vijaya, Annas; Wicaksono, Hendro},
url = {https://doi.org/10.1016/j.promfg.2020.11.056},
doi = {doi.org/10.1016/j.promfg.2020.11.056},
year = {2020},
date = {2020-12-31},
journal = {Procedia Manufacturing},
volume = {52},
abstract = {A maturity model is a wide technique to measure several aspects and identify the current state of processes in an organization, which can be used as a starting point for business improvement. In the Industry 4.0 context, several terms are used to express the model, such as readiness assessment model, roadmap, framework, and maturity index. They have the same purpose of measuring how the current state of an organization unit is capable of adopting and implementing the concept of industry 4.0 in the future. Many researchers had proposed maturity models for assessing Industry 4.0 readiness and maturity since 2011 when Industry 4.0 was commenced. However, there has been no attempt to analyze empirical evidence systematically. This paper aims to analyze currently available maturity models related to Industry 4.0 and provide a synthesis on those maturity models. This paper describes a systematic literature review (SLR) of empirical studies implemented on the maturity model published in several reputable and relevant sources. It focuses on the manufacturing and logistics sectors since the processes in both sectors can be highly improved through the introduction of technologies such as cyber-physical systems, internet of things, and artificial intelligence.

In general, the primary purpose of the review is to address the following questions: (1) Based on what dimensions do researchers develop Industry 4.0 maturity models, and what are the most used and influencing parameters in those dimensions? (2) How do those maturity models compare to each other in terms of dimension complexity, techniques, maturity leveling, and kind of application sectors of the model? In conclusion, the maturity model in the context of Industry 4.0 is promising to guide the adoption of industry 4.0 technologies at the organization level. However, just having a maturity model is not enough. More efforts are needed to facilitate the application of it.},
keywords = {industry 4.0, industry 4.0 maturity assessment, manufacturing, systematic literature review},
pubstate = {published},
tppubtype = {article}
}

@misc{Wicaksono2018c,
title = {Preparing Indonesia and Germany for Industry 4.0: A Reflection and Inspirations from both countries },
author = {Wicaksono, Hendro},
year = {2018},
date = {2018-08-22},
keywords = {health 4.0, industry 4.0, industry 4.0 maturity assessment},
pubstate = {published},
tppubtype = {presentation}
}

@workshop{Wicaksono2018d,
title = {Preparing IT Industry and Organizations Towards industry 4.0},
author = {Wicaksono, Hendro },
editor = {The Government of East Java Province, Indonesia},
year = {2018},
date = {2018-08-14},
publisher = {The Government of East Java Province, Indonesia},
address = {Surabaya, Indonesia},
keywords = {education 4.0, industry 4.0, industry 4.0 maturity assessment, innovation management, innovation network},
pubstate = {published},
tppubtype = {workshop}
}