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Challenges of implementing Industry 4.0 in developed and developing countries: A comparative review Surindra, Mochamad Denny; Caesarendra, Wahyu; Krolczyk, Grzegorz; Gupta, Munish Kumar
Mechanical Engineering for Society and Industry Vol 4 No 3 (2024): Special Issue on Technology Update 2024
Publisher : Universitas Muhammadiyah Magelang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31603/mesi.12177

Abstract

Indonesia could transform the manufacturing industry by making Indonesia 4.0, despite the many uncertainties of implementing Industry 4.0 due to high investment costs and unclear returns. Therefore, looking at neighboring countries such as Germany, the country that initiated Industry 4.0, and China, the country taking the lead in implementing Industry 4.0, it is considered essential for the manufacturing industry in Indonesia to understand how towards the revolution and identify the development of the Industry 4.0 program. Germany is confident in its capabilities in the field of manufacturing technology. It makes the main challenge in carrying out Industry 4.0 'Investment Capital, Employee Qualifications, and Security of Data Transfer and Legislation'. On the other hand, China faces significant challenges in Manufacturing Capabilities, Research and Development (R&D), and Human Capital. To adopt the transformation technology and self-assess the internal resources, Indonesia created a tool, namely the Indonesia Industry 4.0 Readiness Index (INDI 4.0). This article presents a comparative review of the Industry 4.0 readiness index from the perspective of Germany and Singapore as a developed country compared to developing countries such as China, Malaysia, and Indonesia. This study aims to provide awareness related to the readiness index, which can be used to inform industries whether they are suitable for applying Industry 4.0 and how to measure whether their employees are capable of it. In general, the INDI 4.0 measuring instrument shows the readiness of companies in Indonesia, and according to the recent assessment, the industries in Indonesia are at a moderate level, especially in the field of technology application and operation.
Remaining useful life prognosis of low-speed slew bearing using random vector functional link Caesarendra, Wahyu; Rahardja, Dimas Revindra; Abdillah, Muhammad; Darmanto, Seno; Handayani, Sri Utami; Lestari, Wahyu Dwi; Krolczyk, Grzegorz
Mechanical Engineering for Society and Industry Vol 5 No 1 (2025)
Publisher : Universitas Muhammadiyah Magelang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31603/mesi.12965

Abstract

Bearings have a very important role in an industry. However, the cost of maintenance and replacement of bearings are very expensive especially for slew-bearing which operated in a very low speed. If the low-speed slew bearing shutdown suddenly, it will also cause a financial issue to the certain industries with rely on the rotating machines because the entire machine will be shut down and the production will be stop Therefore, monitoring of the low-speed slew bearing condition at all times is necessary to predict the bearing failure. There has been advance monitoring devices and systems related to the vibration condition monitoring for bearing and rotating machines, however, in certain cases those monitoring devices and systems are not sufficient. Machine learning is offered to complement and contribute in this case which aims to determine the prediction and Remaining Useful Life (RUL) of the bearing before the bearing experiences more damage. In this paper, the Random Vector Functional Link (RVFL) is used to predict RUL using low speed slew bearing data from University of Wollongong, Australia. The main evaluation matrix such as RMSE is used as an evaluation of the performance of the model used. According to the prediction results, the best modeling results are obtained using a data ratio of 80:20 and a SELU activation function that produces the best average RMSE value. The prediction value of Remaining Useful Life (RUL) of the bearing is 94.24%.