Tangerang, 23 November 2022, With the rapid development of the industrial world marked by the start of the Industrial 4.0 era, predictive maintenance has become an important topic for improving industrial performance in Indonesia. In order to increase awareness of the implementation and benefits of predictive maintenance, the Swiss German University Industrial Engineering Study Program, collaborating with the management of PIDI 4.0, PT. Andal Wahana Sinergi (AWASIN) and Techsource Systems held a “Predictive Maintenance” workshop on Monday, November 23, 2022. The event was held at the Indonesia Digital Industry 4.0 Center Building (PIDI4.0), which is a facility owned by the Indonesian Ministry of Industry, on Jl. Raya Kby Lama, No. 41, Permata Hijau, West Jakarta.
The “Predictive Maintenance” workshop was opened with remarks from Mr. Muhammad Mukhlis Afriyanto, ST., ME., MSE, Account Representative from PIDI 4.0. This event was attended by around 30 practitioners from various leading industries such as Pertamina, Toyota Motor Manufacturing Indonesia, Suzuki Indomobil Indonesia, East Kalimantan Methanol, United Tractor Pandu Engineering (PATRIA) and others.
In this activity there were 6 speakers, both from SGU and from practitioners, namely from the Industrial Engineering program – Swiss German University, Dr. Eng. Aditya T Pratama, Ir. Triarti Saraswati, M.Eng, and Dr. Tanika D Sofianti. From Techsource Systems, Bambang Nugroho and Ms Rasyiqah Annani, and PT AWASIN Livano Yudhistira.
The first session was started by Dr. Aditya T Pratama which discusses maintenance management starting from basic theory to the latest developments in industrial equipment maintenance management technology. This session explains the meaning of maintenance, the importance of maintenance management, and various methods for equipment maintenance or maintenance, and types of maintenance.
In session 2, the explanation was continued with a hands-on predictive analysis session using MATLAB for implementation on predictive maintenance which was directed by Ms. Rasyiqah and Mr. Bambang from TechSource. In this session, the use of calculation applications for predictive maintenance is explained and demonstrated by all workshop participants. This session provides an opportunity for workshop participants to try using MATLAB for predictive maintenance using a special license given to workshop participants.
After ISHOMA, the workshop was continued by Ir. Triarti Saraswati, M.Eng with the topic of human factors in maintenance. This session discusses errors that can be caused by the human factor (or human error) in maintenance and their causes. Various causes of human error are explained, starting from outdated instructions or measuring instruments to the level of stress and fatigue experienced by workers.
As the fourth speaker of this Workshop, Dr. Tanika D Sofianti presented material entitled “Maintenance Inventory Control Towards Industry 4.0”. This session discusses the importance of inventory management for maintenance activities in the success of maintenance management. In an inventory management, the right method is needed to minimize costs or costs while still meeting the needs of parts for maintenance management activities. This session also explained the importance of minimizing the impact of the use of equipment on the environment, by carrying out maintenance management activities as best as possible, and supported by a good spare parts inventory management system. In this session, various types of inventory and methods to control inventory levels are explained at a point with minimum cost and still be able to meet customer demands and needs at the right time and in the right amount.
The “Predictive Maintenance” workshop ended with a session by Mr. Livano Yudistira from PT AWASIN. He demonstrated the advantages of implementing predictive maintenance. This session discusses the benefits of predictive maintenance both from an economic and operational point of view where predictive maintenance can reduce costs and losses incurred due to industrial equipment not functioning properly. In this session Mr. Livano also demonstrated several instruments and equipment that had been developed by PT Awasin for predictive maintenance purposes in several industrial and construction facilities.
Swiss German University Industrial Engineering (SGU) together with PT. Andal Wahana Sinergi (AWASIN) and Techsource Systems organized this activity as part of a community service activity, which aims to increase the awareness of the industrial community regarding the importance of Predictive Maintenance. In addition, this workshop also provides ways to implement Predictive Maintenance properly so that it can achieve the main goal of implementing Predictive Maintenance.
With this workshop, it is hoped that the collaboration between SGU Industrial Engineering and PT Awasin, and Techsource System with industrial practitioners, PIDI 4 and the Indonesian Ministry of Industry as part of “government” can continue to develop and contribute to advancing digital technology innovation in Indonesia, especially with the implementation of the program Industry 4.0 in Indonesia is “Making Indonesia 4.0” so that it can strengthen the nation’s competitiveness.
The “Predictive Maintenance” workshop event was able to run successfully thanks to the full support of various parties such as PT AWASIN and Techsource Systems, as well as the Digital Industry Center
4.0 (PIDI4.0). In addition, SGU Industrial Engineering lecturers and students who became speakers and organized the committee and the involvement of the workshop participants also played an important role in the success of this event.
This workshop has also published in:
- https://sgu.ac.id/awareness-terhadap-kehandalan-peralatan-industri-program-teknik-industri-swiss-german-university-gelar-workshop-predictive-maintenance/
- https://banten.antaranews.com/berita/232673/program-teknik-industri-sgu-gelar-workshop-pemeliharaan-prediktif
- https://edukasi.sindonews.com/read/957253/211/teknik-industri-swiss-german-university-gelar-workshop-predictive-maintenance-1669889558