Digital Monitoring and its Effects on Organizational Performance

Faridullah Lalzai; Jahan; Kahir Mohammad

doi:10.55544/ijrah.3.5.22

Authors

Faridullah Lalzai Department of Applied Agriculture, Central University of Punjab, Bathinda, Punjab, INDIA. https://orcid.org/0009-0001-2911-8163
Jahan Department of HR and Finance, Chandigarh University, Mohali, Chandigarh, INDIA. https://orcid.org/0009-0005-8327-8861
Khair Mohammad Department of Economics, South Asian University, Akbar Bhawan, Satya Marg, Chanakyapuri, New Delhi, INDIA.

DOI:

https://doi.org/10.55544/ijrah.3.5.22

Keywords:

Internet of Things, Monitor, Organizational Resources, Optimal Utilization, Waste

Abstract

In every successful organization, the critical factors of time, cost, and quality preservation are paramount. Effectively managing and controlling these factors necessitates the implementation of strategic measures. Specifically, the reduction of wastage emerges as a key approach to conserving time, cost, and quality. Achieving this goal hinges on the optimal utilization of organizational resources, which entails precise planning, allocation, monitoring, and control.

While various methods for planning and resource tracking exist across organizations, this study focuses on strategies employed within the manufacturing industry. These strategies have demonstrated greater efficiency compared to traditional methods. Moreover, the study proposes the integration of Internet of Things (IoT) technology to address this challenge effectively.

The research recommends the use of IoT technology as a comprehensive solution. Prior studies have often utilized the JIT method solely for resource utilization or TPM method solely for resource management. In contrast, this research advocates for the individual application of these methods to plan each resource meticulously. Specifically, the JIT method is proposed for material utilization, the TPM method for equipment utilization, and the Kaizen method for labor allocation. Furthermore, it emphasizes the integration of IoT with these lean methods. While some researchers have explored IoT, they have not fully integrated it with lean methods and techniques. The synergy of lean production methods and IoT technology offers an ideal opportunity for optimizing the utilization of organizational resources.

Through these techniques, organizational resources can be efficiently planned and allocated to the production process. IoT provides valuable tools such as sensors, which can be installed at various resources, facilitating real-time data transmission to managers. This enables remote monitoring from office settings and timely data acquisition, thus addressing the challenge of optimal organizational resource utilization effectively.

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References

Alavipour, S. M. R., & Arditi, D. (2019). Time-cost tradeoff analysis with minimized project financing cost. Automation in Construction, 98, 110–121. Https://doi.org/10.1016/j.autcon.2018.09.009

Atan, T., & Eren, E. (2018). Optimal project duration for resource leveling. European Journal of Operational Research, 266(2), 508–520. Https://doi.org/10.1016/j.ejor.2017.10.022

Bahga, A., & Madisetti, V. M. (2017). Internet of Things: A Hands-On Approach. Google Books.

Bakchan, A., & Faust, K. M. (2019). Construction waste generation estimates of institutional building projects: Leveraging waste hauling tickets. Waste Management, 87, 301–312. Https://doi.org/10.1016/j.wasman.2019.02.024

Casado-Vara, R., Martin-del Rey, A., Affes, S., Prieto, J., & Corchado, J. M. (2020). Iot network slicing on virtual layers of homogeneous data for improved algorithm operation in smart buildings. Future Generation Computer Systems, 102, 965–977. Https://doi.org/10.1016/j.future.2019.09.042

De Magalhães, R. F., Danilevicz, Â. De M. F., & Saurin, T. A. (2017). Reducing construction waste: A study of urban infrastructure projects. Waste Management, 67, 265–277. Https://doi.org/10.101

Guide, C. T., & College, M. D. (2015). Construction Labor Productivity and its Improvement. International Research Journal of Engineering and Technology, 02(08), 824–832.

Jaśkowski, P., Sobotka, A., & Czarnigowska, A. (2018). Decision model for planning material supply channels in construction. Automation in Construction, 90, 235–242. Https://doi.org/10.1016/j.autcon.2018.02.026

Kanan, R., Elhassan, O., & Bensalem, R. (2018). An iot-based autonomous system for workers’ safety in construction sites with real-time alarming, monitoring, and positioning strategies. Automation in Construction, 88, 73–86. Https://doi.org/10.1016/j.autcon.2017.12.033

Khodeir, L. M., & El Ghandour, A. (2019). Examining the role of value management in controlling cost overrun [application on residential construction projects in Egypt]. Ain Shams Engineering Journal, 10(3), 471–479. Https://doi.org/10.1016/j.asej.2018.11.008

Lee, I. (2019). The Internet of Things for enterprises: An ecosystem, architecture, and iot service business model. Internet of Things, 7, 100078. Https://doi.org/10.1016/j.iot.2019.100078

Patil, A. R., & Pataskar, S. V. (2013). Analyzing Material Management Techniques on Construction Project. International Journal of Engineering Innovation and Technology, 3(4), 96–100.

Project Management Institute. (2017). The Standard for Project Management, 53(9).

Rashid, K. M., & Louis, J. (2019). Time-series data augmentation and deep learning for construction equipment activity recognition. Advances in Engineering Informatics, 42, 100944. Https://doi.org/10.1016/j.aei.2019.100944

Shao, S., Xu, G., & Li, M. (2019). The design of an iot-based route optimization system: A smart product-service system (SPSS) approach. Advances in Engineering Informatics, 42, 101006. Https://doi.org/10.1016/j.aei.2019.101006

Tang, S., Shelden, D. R., Eastman, C. M., Pishdad-Bozorgi, P., & Gao, X. (2019). A review of building information modeling (BIM) and the internet of things (iot) devices integration: Present status and future trends. Automation in Construction, 101, 127–139. Https://doi.org/10.1016/j.autcon.2019.01.020

Waris, M., Liew, M. S., Khamidi, M. F., & Idrus, A. (2014). Criteria for the selection of sustainable onsite construction equipment. International Journal of Sustainable Built Environment, 3(1), 96–110.

Woodhead, R., Stephenson, P., & Morrey, D. (2018). Digital construction: From point solutions to iot ecosystem. Automation in Construction, 93, 35–46. Https://doi.org/10.1016/j.autcon.2018.05.004

Xu, G., Li, M., Chen, C. H., & Wei, Y. (2018). Cloud asset-enabled integrated iot platform for lean prefabricated construction. Automation in Construction, 93, 123–134. Https://doi.org/10.1016/j.autcon.2018.05.012

Xu, Y., & Chen, M. (2016). Improving Just-in-Time manufacturing operations by using Internet of Things based solutions. Procedia CIRP, 56, 326–331. Https://doi.org/10.1016/j.procir.2016.10.030

Zhao, J., Seppänen, O., Peltokorpi, A., Badihi, B., & Olivieri, H. (2019). Real-time resource tracking for analyzing value-adding time in construction. Automation in Construction, 104, 52–65. Https://doi.org/10.1016/j.autcon.2019.04.003

Zhao, Z., Lin, P., Shen, L., Zhang, M., & Huang, G. Q. (2020). Iot edge computing-enabled collaborative tracking system for manufacturing resources in industrial park. Advances in Engineering Informatics, 43, 101044. Https://doi.org/10.1016/j.aei.2020.101044