(2025-b)
Suryadarma, Engelbert Harsandi Erik, et al. “The Effect of Eye Shape and the Use of Corrective Glasses on the Spatial Accuracy of Eye-Gaze-Based Robot Control with a Static Head Pose.” Journal of Robotics and Control (JRC) 6.4 (2025): 2005-2020.
https://www.scopus.com/pages/publications/105014214304?origin=resultslist
Abstract: The integration of eye-gaze technology into robotic control systems has shown considerable promise in enhancing human–robot interaction, particularly for individuals with physical disabilities. This study investigates the influence of eye morphology and the use of corrective eyewear on the spatial accuracy of gaze-based robot control under static head pose conditions. Experiments were conducted using advanced eye-tracking systems and multiple machine learning algorithms—decision tree, support vector machine, discriminant analysis, naïve bayes, and K-nearest neighbor—on a participant pool with varied eye shapes and eyewear usage. The experimental design accounted for potential sources of bias, including lighting variability, participant fatigue, and calibration procedures. Statistical analyses revealed no significant differences in gaze estimation accuracy across eye shapes or eyewear status. However, a consistent pattern emerged: participants with non-monolid eye shapes achieved, on average, approximately 1% higher accuracy than those with monolid eye shapes—a difference that, while statistically insignificant, warrants further exploration. The findings suggest that gaze-based robotic control systems can operate reliably across diverse user groups and hold strong potential for use in assistive technologies targeting individuals with limited mobility, including those with severe motor impairments such as head paralysis. To further enhance the inclusiveness and robustness of such systems, future research should explore additional anatomical variations and environmental conditions that may influence gaze estimation accuracy.
(2025-a)
Suryadarma, Engelbert Harsandi Erik, et al. “Human Cyber Physical System in Manufacturing 4.0: An Application for Intelligent SCADA-Based Manufacturing.” Lecture Notes in Mechanical Engineering Springer Science and Business Media Deutschland GmbH (2025) 103-114.
https://www.scopus.com/pages/publications/105007970360?origin=resultslist
Abstract: The Human Cyber Physical System (HCPS) in Manufacturing 4.0 represents the integration of human intelligence with cyber-physical systems to create smarter, more efficient production processes. This synergy enhances decision-making, real-time monitoring, and adaptability in manufacturing environments. However, the current implementation and research on HCPS are still limited, particularly when applied to Supervisory Control and Data Acquisition (SCADA)-based manufacturing. When searching the Scopus database, during the last 10 years there were only 7 conference proceedings, 6 journals and 3 book series. The aim is to provide the application of HCPS in SCADA-based manufacturing and provide an overview of the architecture of both SCADA and HCPS when applied to real-world systems. The SCADA software AVEVA InTouch HMI, utilized in combination with Schneider Electric’s Programmable Logic Controller (PLCs) hardware, was employed to develop a SCADA-based manufacturing system. This research resulted in a prototype HCPS for predictive maintenance of water-cooling systems. The system successfully reduced potential downtime to zero hours. Additionally, it effectively prevented unplanned machine breakdowns.
(2024-b)
Suryadarma, Engelbert Harsandi Erik, Pringgo Widyo Laksono, and Ilham Priadythama. “Optimal PLA+ 3D Printing Parameters through Charpy Impact Testing: A Response Surface Methodology.” Jurnal Optimasi Sistem Industri 23.1 (2024): 76-91.
https://www.scopus.com/pages/publications/85199262276?origin=resultslist
Abstract: Additive manufacturing (AM) has revolutionized the manufacturing sector, particularly with the advent of 3D printing technology, which allows for the creation of customized, cost-effective, and waste-free products. However, concerns about the strength and reliability of 3D-printed products persist. this study focuses on the impact of three crucial variables—infill density, printing speed, and infill pattern—on the strength of PLA+ 3D-printed products. Our goal is to optimize these parameters to enhance product strength without compromising efficiency. We employed Charpy impact testing and Response Surface Methodology (RSM) to analyze the effects of these variables in combination. Charpy impact testing provides a measure of material toughness, while RSM allows for the optimization of multiple interacting factors. Our experimental design included varying the infill density from low to high values, adjusting printing speeds from 70mm/s to 100mm/s, and using different infill patterns such as cubic and others. Our results show that increasing infill density significantly boosts product strength but also requires more material and longer processing times. Notably, we found that when the infill density exceeds 50%, the printing speed can be increased to 100mm/s without a notable reduction in strength, offering a balance between durability and production efficiency. Additionally, specific infill patterns like cubic provided better strength outcomes compared to others. these findings provide valuable insights for developing stronger and more efficient 3D-printed products using PLA+ materials. By optimizing these parameters, manufacturers can produce high-strength items more efficiently, thereby advancing the capabilities and applications of 3D printing technology in various industries.
(2024-a)
Suryadarma, Engelbert Harsandi Erik, et al. “Controlling Robots Using Gaze Estimation: A Systematic Bibliometric and Research Trend Analysis.” Journal of Robotics and Control (JRC) 5.3 (2024): 786-803.
https://www.scopus.com/pages/publications/85193811415?origin=resultslist#
Abstract: The rapid progression of technology and robotics has brought about a transformative revolution in various fields. From industrial automation to healthcare and beyond, robots have become integral parts of our society, such as using them to move laparoscopic cameras. Eye-gaze-based control in robotics is a cutting-edge innovation, providing enhanced human–robot interaction and control. However, current research is in the underexplored area of gaze-based control for robotics. This paper presents a systematic bibliometric analysis review of controlling robots using gaze estimation. The aim is to provide a research map overview of the use of eye gaze to control robots by clustering application areas based on ISIC-UN and several data acquisition technologies. Over the past 10 years, the number of publications in this field has been relatively stable, averaging 21.5 papers per year, with minimal fluctuations in annual article counts (σ = 4.9). This differs from research on robotics, which grows by an average of 1376 papers per year. Research on using eye gaze for robot control in the last 10 years in the field of human health and social work has only resulted in 17 articles; transportation and storage resulted in 12 articles; professional, scientific, and technical activities resulted in eight articles; information and communication resulted in five articles; and education and art resulted in two articles. Data acquisition technology for eye gaze research, primarily using a commercial eye tracker. Thus, there is significant potential for future research through the utilization of gaze estimation in various fields, as mentioned above.
(2021)
E.H.E. Suryadarma, T.J. Ai, B. Bawono, A.T. Siswantoro, “Improving Bimetal Bond Quality Between Cast Steel and Aluminum Alloys Using Response Surface Methodology,” International Journal of Metalcasting, 2021, pp. 1-10, Springer International Publishing, doi: 10.1007/s40962-021-00687-4.
https://link.springer.com/article/10.1007/s40962-021-00687-4
Abstract: Currently there is greater interest and an industrial need to create a bond between cast steel and aluminum alloys. The bond quality between these two metals must be considered, since it is affected by several casting techniques and parameters. This research aims to find the right combination of techniques and parameters to make a good bond between cast steel and aluminum alloys. This research systematically used the response surface methodology (RSM). Three important casting techniques and parameters are selected as independent variables, which are preheating temperature of cast steel, pouring temperature of aluminum alloy molten, and surface cleaning of cast steel. The gap between cast steel and aluminum alloy is used as dependent variable, which is defined as the quality measurement of the bond between two metals. The experiments were conducted on 48 samples, in which destructive test was performed in order to measure the gap. From the methodology, it is found that the recommended preheating temperature of cast steel is 491 °C, the recommended pouring temperature of aluminum alloy is 696 °C, and the recommended technique is cleaning the cast steel insert using degreasing. For practical purpose, the preheating temperature of cast steel can be set at 490 ± 10 °C and the pouring temperature of aluminum alloy can be set at 695 ± 10°C. This research limits on bimetal casting between cast steel and aluminum alloys,
and the casting process is gravity die casting process. This paper is able to find the best casting techniques and parameters for cast steel and aluminum alloy bond using RSM. This paper also proposes gap bond between two metals as bond quality measurement.
(2020-c)
E.H.E. Suryadarma, T.J. Ai, B. Bawono, P.W. Anggoro, “Value Analysis of Predictive Maintenance in Cooling System of a Die Casting Process by Data SCADA,” IEEE 2020 6th International Conference on Science and Technology (ICST), 2020, doi: 10.1109/ICST50505.2020.9732888
https://ieeexplore.ieee.org/abstract/document/9732888
Abstract: The cooling system is vital for the die casting process. The problematic cooling system will make the process of solidification uncontrolled. So that maintenance (especially predictive maintenance) is needed to keep the cooling system in good condition. However, the application of predictive maintenance requires complex resources. This research will simplify the predictive maintenance procedure on the cooling system in the casting process by reducing the number of sensors and calculations. This research uses SCADA technology and Machine Learning to keep getting accurate predictions. Based on the test results, the level of complexity of the proposed predictive maintenance system is more straightforward than before the value analysis was carried out, but has an accuracy level equivalent to before the value analysis applied.
(2020-b)
E.H.E. Suryadarma, T.J. Ai, “Predictive Maintenance in SCADA-Based Industries: A literature review, ” International Journal of Industrial Engineering and Engineering Management, Vol 2 No 1, pp. 57-70, 2020.
https://ojs.uajy.ac.id/index.php/IJIEEM/article/view/4368
Abstract: The purpose of this paper is to mapping and review what has been done on the topic of research on predictive maintenance in SCADA (Supervisory Control and Data Acquisition) based industries. In the research area of predictive maintenance, various methods for predicting damage or time to failure of a machine have been proposed and applied in various industries. This paper systematically categorizes predictive maintenance in SCADA-based industries research based on industry classifications according to ISIC (International Standard Industrial Classification of All Economic Activities). Furthermore, the research scope is explored its connection to the topics of Internet of Things (IoT), Artificial Intelligence (AI), Machine Learning (ML), and Supervisory Control and Data Acquisition (SCADA). It is found that 81.5% of the research was conducted on the electricity, gas, steam, and air conditioning supply industries, 11.1% of research was conducted on the
mining and quarrying industry, and 7.4% of the research conducted in the manufacturing industry. It is also found that 85.2% of studies used AI and ML, 18.5% of the studies used IoT, and 18.5% of research used AI/ML and IoT technology together.
(2020-a)
E.H.E. Suryadarma, T.J. Ai, “Predictive Maintenance of Cooling System with Sensor Combination and SCADA,” 10th International Conference on Operations and Supply Chain Management, New Zealand, 2020.
Abstract: The cooling system has a fundamental role in the die casting process because the cooling system will directly affect the quality of the casting results. However, to ensure the cooling system works well from time to time is not easy. More frequent and regularly checking the cooling system is one possible way to ensure it. Nevertheless, this way is disrupting the casting process. In this paper, a predictive maintenance technique is proposed with autonomous analysis based on machine learning and sensor data. A SCADA system collects real-time data from several sensor combinations. This data is then passed to a machine learning algorithm for predicting cooling system conditions, i.e., predicting future system failure. The proposed predictive maintenance system is expected to be able to predict the damage better. Therefore, it will reduce the possibility of unplanned system failure.
Also, it is increasing the maintenance process. The maintenance is carried out according to the cooling system conditions and without the need periodically check the cooling system.
(2018)
B. Kristyanto, B. B. Nugraha, S. Suyoto, A. K. Pamosoaji and K. A. Nugroho, “Therbligh Motions as a Basic of Movement Therapy for Stroke Patients,” International Conference on Human Systems Engineering and Design: Future Trends and Applications, 2018, pp. 1018-1024, Springer, Cham doi: 10.1007/978-3-030-02053-8_155.
https://link.springer.com/chapter/10.1007/978-3-030-02053-8_155
Abstract: Analysis of human arms’ movements using Therbligh principles is now used to study the movement therapy for stroke patients. The study aims to design robot arm as a preliminary result to design artificial shoulder-attached-dual-arm robot to imitate human arms’ movements that will help stroke patients for movement therapy. For modeling the dual human arm movements, a DH-parameter based on forward-kinematics of the arms is used. Human hands hold objects with various weights and volumes. We take into account the unpredictability center of mass of the entire arms as uncertainty. The model must follow human’s base behavior. Therefore, human arms anthropometry is required to determine the movement’s parameters. Movement limitation of stroke patients must also be considered as the limitation. Result simulations are presented and will be used as the model for movement controller. Synchronized and symmetrical arms’ movement is expected to improve
the balance of the brain’s control system.
(2017)
B. Kristyanto, B. B. Nugraha, A. K. Pamosoaji and K. A. Nugroho, “Analysis of human arm motions at assembly work as a basic of designing dual robot arm system,” 2017 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM), 2017, pp. 1316-1320, doi: 10.1109/IEEM.2017.8290106.
https://ieeexplore.ieee.org/stamp/stamp.jsptp=&arnumber=8290106&isnumber=8289834
Abstract: An analysis of human arm motions has been studied as a preliminary result prior to the design of an artificial shoulder-attached double-arm robot to imitate human arms’ motions. For modeling the dual arm robot, a DH-parameter’s based forward-kinematics of the arms are analyzed. Since in the real world human hands hold various types of objects with distinct weights and volumes, we take into account unpredictably center of mass of the entire arms as uncertainty. For this purpose, the model to follow must be based on human’s behavior. Therefore, human anthropomorphic is required to be applied for determining the robot’s parameters. In addition, human motion limitations must be considered as the limitation of the robot’s motions as well. Simulations of the results are presented to verify the performance of the model and will be used as model for adaptive controller design.
(2015)
B. Kristyanto, B. B. Nugraha, A. K. Pamosoaji and K. A. Nugroho, “Head and Neck Movement: Simulation and Kinematics Analysis,” Procedia Manufacturing, 2015, pp. 359-372, doi: 110.1016/j.promfg.2015.11.052.
https://www.sciencedirect.com/science/article/pii/S2351978915011683
Abstract: In Ergonomics, interaction system between human with some object or machine starts from the stimulation of the object to the head through the eyes. Therefore, the eyes position on the head when receiving the stimulation is very important. The eyes’ ability in receiving stimulation from the object depends on a person’s head and neck movement. Measuring the ability of the head and neck movement is very important, however explaining this matter to the students is complicated. In consequently, to make a simple way in explaining to the students, a head and neck anthropometry model or Head Mannequin design that can be moved in simulation of the visual design is needed. This research is aimed to assess the behavior and limitation movement of the human head and neck. A head model of mannequin is made and developed to make a simulation for ergonomic movement learning using Solid work software. The components of construction movement are analyzed by kinematic analysis using MATLAB to convince the simulation of human head movement. The results of the study show that head mannequin is able to simulate the human head movement. The kinematic models of head movement based on limitations are generated and the analysis is presented in the full paper.