EMBEDDED SYSTEMS DESIGN FOR SMART PRODUCTS IN INDUSTRY FOUR POINT ZERO MANUFACTURING

Nana Sujana (1), Jaden Tan (2), Sofia Lim (3)
(1) Politeknik Pajajaran ICB Bandung, Indonesia,
(2) Singapore Institute of Technology, Singapore,
(3) Singapore University of Technology and Design, Singapore

Abstract

Industry Four Point Zero manufacturing has transformed conventional production systems into intelligent, interconnected environments in which smart products play a central role. These smart products rely heavily on embedded systems to enable sensing, real-time control, communication, and autonomous decision-making under strict industrial constraints. This study aims to examine how embedded systems design influences the performance of smart products in Industry Four Point Zero manufacturing contexts, with particular attention to design attributes that support efficiency, adaptability, and reliability. A mixed-methods research design was employed, combining quantitative analysis of survey data collected from industrial practitioners with qualitative insights derived from case-based observations in manufacturing settings. The instruments focused on key embedded system design dimensions, including modularity, real-time responsiveness, communication efficiency, and system reliability, as well as corresponding smart product performance indicators. The results reveal that embedded systems design has a significant and positive effect on smart product performance, with communication efficiency and system reliability emerging as the strongest predictors of operational efficiency and fault tolerance. The findings demonstrate that smart manufacturing effectiveness is strongly determined by device-level design decisions rather than by higher-level digital infrastructures alone. In conclusion, the study highlights embedded systems design as a strategic foundation for smart products and underscores its critical role in achieving sustainable and resilient Industry Four Point Zero manufacturing.

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References

Alghamdi, W., & Gul, T. (2025). Darcy–Forchheimer hybrid nanofluid flow in a squeezing inclined channel for drug delivery applications by means of artificial neural network. Multidiscipline Modeling in Materials and Structures, 21(2), 387–404. https://doi.org/10.1108/MMMS-07-2024-0202

Attiogbe, E. J. K., Oheneba-Sakyi, Y., Kwapong, O. A. T. F., & Boateng, J. (2025). Assessing the relationship between feedback strategies and learning improvement from a distance learning perspective. Journal of Research in Innovative Teaching & Learning, 18(1), 165–186. https://doi.org/10.1108/JRIT-10-2022-0061

Bertão, R. A., Yeoun, M.-H., & Joo, J. (2025). A blind spot in AI-powered logo makers: Visual design principles. Visual Communication, 24(1), 222–250. https://doi.org/10.1177/14703572231155593

Bhattacharjee, J., & Roy, S. (2025). A comprehensive review on integrated photo rechargeable batteries- supercapacitors, and their techno-economic feasibility. Journal of Photochemistry and Photobiology, 25, 100257. https://doi.org/10.1016/j.jpap.2024.100257

Chang, T.-Y. J., Chen, Y.-H., Reddy, K. V., Puri, N., Masina, T., Lin, K.-C., Wang, P.-S., Lin, Y., Lin, C.-Y., Nien, Y.-H., Fujiwara, H., Lin, K.-F., Chang, M.-H., Wu, C. W., Lee, R., Wang, Y., Liao, H.-J., Li, Q., Wang, P. W., & Yeap, G. (2025). A 38.1Mb/mm2 SRAM in a 2nm-CMOS-Nanosheet Technology for High-Density and Energy-Efficient Compute. 2025 IEEE International Solid-State Circuits Conference (ISSCC), 492–494. https://doi.org/10.1109/ISSCC49661.2025.10904759

Deng, J., Yu, X., Pang, D., Fei, B., & Mo, J. (2025). Cutting-edge gas sensor design for monitoring thermal runaway in lithium-ion batteries: A critical review. Journal of Energy Chemistry, 109, 769–785. https://doi.org/10.1016/j.jechem.2025.06.025

Dhanka, S., Sharma, A., Kumar, A., Maini, S., & Vundavilli, H. (2026). Advancements in Hybrid Machine Learning Models for Biomedical Disease Classification Using Integration of Hyperparameter-Tuning and Feature Selection Methodologies: A Comprehensive Review. Archives of Computational Methods in Engineering, 33(1), 289–324. https://doi.org/10.1007/s11831-025-10309-5

Fan, Y., Lei, L., Cao, J., Wang, W., & Fan, H. (2025). Benzene Ring Engineering of Graphitic Carbon Nitride for Enhanced Photocatalytic Dye Degradation and Hydrogen Production from Water Splitting. ChemSusChem, 18(12), e202500462. https://doi.org/10.1002/cssc.202500462

Khan, O., El Mistiri, M., Banerjee, S., Hekler, E., & Rivera, D. E. (2025). 3DoF-KF HMPC: A Kalman filter-based Hybrid Model Predictive Control Algorithm for Mixed Logical Dynamical Systems. Control Engineering Practice, 154, 106171. https://doi.org/10.1016/j.conengprac.2024.106171

Leon, V., Hanif, M. A., Armeniakos, G., Jiao, X., Shafique, M., Pekmestzi, K., & Soudris, D. (2025). Approximate Computing Survey, Part I: Terminology and Software & Hardware Approximation Techniques. ACM Computing Surveys, 57(7), 1–36. https://doi.org/10.1145/3716845

Li, S., Tian, T., Zhang, T., Lin, Y., & Cai, X. (2025). A bioswitchable delivery system for microRNA therapeutics based on a tetrahedral DNA nanostructure. Nature Protocols, 20(2), 336–362. https://doi.org/10.1038/s41596-024-01050-7

Lin, C., Cao, Z., & Zhou, M. (2025). Autoencoder-Embedded Iterated Local Search for Energy-Minimized Task Schedules of Human–Cyber–Physical Systems. IEEE Transactions on Automation Science and Engineering, 22, 512–522. https://doi.org/10.1109/TASE.2023.3267714

Lin, Y., Huang, S., Deng, R., Wang, M., Zou, Z., Gu, F., & Ball, A. D. (2025). A metamaterials-augmented drone monitor for acoustics-based remote fault detection and diagnosis. Mechanical Systems and Signal Processing, 226, 112346. https://doi.org/10.1016/j.ymssp.2025.112346

Liu, Q., Long, Y., Li, T., & Chen, C. L. P. (2025). Attack Tolerant Fault Detection for CPSs: An Unknown Input Interval Observer Approach. IEEE Transactions on Automation Science and Engineering, 22, 1163–1172. https://doi.org/10.1109/TASE.2024.3360967

Ma, C., Yang, L., Li, M., He, J., Hua, C., Wang, L., Li, G., Liu, J., Yang, J., Liu, K., Zhou, Y., Zhou, J., Deng, X., & Weng, S. (2025). Closed-loop two-phase pulsating heat pipe towards heat export and thermal error control for spindle-bearing system of large-size vertical machining center. Applied Thermal Engineering, 269, 125993. https://doi.org/10.1016/j.applthermaleng.2025.125993

Mohsin, M. E. A., Siddiqa, A. J., Mousa, S., & Shrivastava, N. K. (2025). Design, Characterization, and Release Kinetics of a Hybrid Hydrogel Drug Delivery System for Sustained Hormone Therapy. Polymers, 17(8), 999. https://doi.org/10.3390/polym17080999

Ning, F., Li, Z., Lu, J., Wang, Y., Niu, Y., & Shi, Y. (2025). 3D CAD model dynamic clustering based on inertial feature encoder. Applied Soft Computing, 182, 113627. https://doi.org/10.1016/j.asoc.2025.113627

Nopas, D. (2025). Algorithmic learning or learner autonomy? Rethinking AI’s role in digital education. Qualitative Research Journal. https://doi.org/10.1108/QRJ-11-2024-0282

Qing, C., Liu, Z., Ling, G., Hu, W., & Du, P. (2025). Channel Estimation in OTFS Systems by Leveraging Differential Modulation. IEEE Transactions on Vehicular Technology, 74(5), 6907–6918. https://doi.org/10.1109/TVT.2024.3522940

Rabenu, E., & Baruch, Y. (2025). Cyborging HRM theory: From evolution to revolution – the challenges and trajectories of AI for the future role of HRM. Personnel Review, 54(1), 174–198. https://doi.org/10.1108/PR-02-2024-0111

Ragonis, N., Rosenberg-Kima, R. B., & Hazzan, O. (2025). A computational thinking course for all preservice K-12 teachers: Implementing the four pedagogies for developing computational thinking (4P4CT) framework. Educational Technology Research and Development, 73(1), 301–329. https://doi.org/10.1007/s11423-024-10406-5

Rui, S., Jostad, H. P., Zhou, Z., Bachynski-Poli?, E., Sævik, S., Wang, L., & Guo, Z. (2025). Analysis of mooring system for floating wind turbine based on macro-model of chain-seabed interaction. Marine Structures, 104, 103877. https://doi.org/10.1016/j.marstruc.2025.103877

Sharifi, H., & Wick, C. D. (2025). Developing interatomic potentials for complex concentrated alloys of Cu, Ti, Ni, Cr, Co, Al, Fe, and Mn. Computational Materials Science, 248, 113595. https://doi.org/10.1016/j.commatsci.2024.113595

Shen, L., Yang, Q., Zheng, Y., & Li, M. (2025). AutoIOT: LLM-Driven Automated Natural Language Programming for AIoT Applications. Proceedings of the 31st Annual International Conference on Mobile Computing and Networking, 468–482. https://doi.org/10.1145/3680207.3723486

Shen, Y., Tang, L., Le, H., Tan, S., Zhao, Y., Shen, K., Li, X., Juelich, T., Wang, Q., Gaševi?, D., & Fan, Y. (2025). Aligning and comparing values of CHATGPT and human as learning facilitators: A value?sensitive design approach. British Journal of Educational Technology, 56(4), 1391–1414. https://doi.org/10.1111/bjet.13562

Sun, Z.-H., Zhang, Y.-Q., Gu, Z.-Y., Qu, D.-Y., Guan, H.-Y., & Wu, X.-L. (2025). CoPSe nanoparticles confined in nitrogen-doped dual carbon network towards high-performance lithium/potassium ion batteries. Chinese Chemical Letters, 36(1), 109590. https://doi.org/10.1016/j.cclet.2024.109590

Turabi, Y. U. U. B., & Munir, S. (2025). CFD simulations of MHD effects on mixed convectional flow in a lid-driven square cavity with square cylinder using Casson fluid. Numerical Heat Transfer, Part B: Fundamentals, 86(11), 3742–3757. https://doi.org/10.1080/10407790.2024.2365890

Villani, V., Picone, M., Mamei, M., & Sabattini, L. (2025). A Digital Twin Driven Human-Centric Ecosystem for Industry 5.0. IEEE Transactions on Automation Science and Engineering, 22, 11291–11303. https://doi.org/10.1109/TASE.2024.3410703

Wang, J., Zhou, J., & Zhang, S. (2025). Applying shape grammar and BIM for generating the mass modular housing design in ShanLiChenJia village, ZhaoYuan, China. Journal of Asian Architecture and Building Engineering, 24(1), 178–198. https://doi.org/10.1080/13467581.2023.2292081

Wang, L. (2025). Co-design of magnetic soft robots with large deformation and contacts via material point method and topology optimization. Computer Methods in Applied Mechanics and Engineering, 445, 118205. https://doi.org/10.1016/j.cma.2025.118205

Xi, J., Liu, J., Bai, W., Wang, T., Zheng, P., Li, P., & Zhai, J. (2025). Design of lead-free high-entropy quasi-linear dielectrics with giant comprehensive electrostatic energy storage. Acta Materialia, 289, 120931. https://doi.org/10.1016/j.actamat.2025.120931

Zhang, Y., Zhang, H., Ma, H., Sun, W., Xu, K., & Li, H. (2025). Composite-airfoil-plate with embedded macro-fiber-composites: Aero-thermo-electro vibration analysis and active control. International Journal of Mechanical Sciences, 290, 110143. https://doi.org/10.1016/j.ijmecsci.2025.110143

Zhao, Q., Wang, Q., Zhang, H., Xia, Y., & Ye, Y. (2025). A Novel RC-ESO-ADRC for Harmonics Suppression and Robustness Improvement of Grid-Tied Inverters in a Weak and Distorted Grid. IEEE Transactions on Power Electronics, 40(9), 12581–12593. https://doi.org/10.1109/TPEL.2025.3563178

Zheng, X., Li, Yuanlong, Zhou, Q., Yu, Z., Liu, X., Xu, R., Sung, H.-K., Chernogor, L., Sun, T., Yao, Z., Li, Yang, & Li, Yuanyue. (2025). Biocompatible, biodegradable, and high-performance flexible pressure sensors for severity grading and rehabilitation assessment in Parkinson’s disease management. Nano Energy, 140, 111030. https://doi.org/10.1016/j.nanoen.2025.111030

Authors

Nana Sujana
nana.sujana@poljan.ac.id (Primary Contact)
Jaden Tan
Sofia Lim
Sujana, N., Tan, J. ., & Lim, S. . (2026). EMBEDDED SYSTEMS DESIGN FOR SMART PRODUCTS IN INDUSTRY FOUR POINT ZERO MANUFACTURING. Journal of Computer Science Advancements, 4(1), 13–26. https://doi.org/10.70177/jsca.v4i1.3391

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