PROJECT DURATION FORECASTING METHODS USING EVM AND ESM FOR A DOUBLE-TRACK RAILWAY PROJECT IN COMPARISON

Elok Dewi Widowati; Andyska Maya Resita

doi:10.21009/jpensil.v14i3.59154

Authors

Elok Dewi Widowati Study Program of Civil Engineering, Faculty of Engineering, Universitas Pembangunan Nasional “Veteran” Jawa Timur
Andyska Maya Resita PT. Modern Surya Jaya

DOI:

https://doi.org/10.21009/jpensil.v14i3.59154

Keywords:

Earned Value, Earned Schedule, Forecasting Duration

Abstract

The growing complexity of infrastructure projects, such as railway construction, necessitates precise tools to monitor progress and accurately predict completion times. Traditional methods often fail to capture real-time schedule dynamics, resulting in ineffective project management. This study employs earned value management (EVM) and earned schedule (ES) to predict the project duration for a double-track railway initiative. Performance metrics for scheduling, such as SPI and SPI(t), as well as forecasting tools, including EAC(t), IEAC, and IEAC(t), were analyzed over 28 weeks. The results demonstrate that SPI(t)-based methods offer more stable and realistic duration forecasts than conventional SPI-based approaches, particularly during periods of poor performance. IEAC values fluctuated sharply during the project's early and middle stages, exceeding 800 days, while IEAC(t) remained consistent, aligning closely with actual progress. After the implementation of contract addenda in Weeks 21 and 27, both indicators improved significantly. SPI and SPI(t) exceeded 1.0, and the forecasted completion date aligned closely with the original plan. The study concludes that the ES method improves schedule forecasting accuracy and provides better insight into project performance trends.

References

Andreas, A., Tinumbia, N., & Anggraini, E. (2013). Construction Project Control Analysis Using Earned Value Management, Earned Schedule Management, Earned Duration Management (Case Study: Highrise Building Project in Jakarta). Jurnal Infrastruktur, 87-98. https://doi.org/10.35814/infrastruktur.v9i2.4943

Ballesteros-Pérez, P., Sanz-Ablanedo, E., Mora-Melià, D., González-Cruz, M. C., Fuentes-Bargues, J. L., & Pellicer, E. (2019). Earned Schedule min-max: Two new EVM metrics for Monitoring and Controlling Projects. Automation in Construction, 279-290. https://doi.org/10.1016/j.autcon.2019.03.016

Batselier, J., & Vanhoucke, M. (2015). Evaluation of Deterministic State-of-the-art Forecasting Approaches for Project Duration Based on Earned Value Management. International Journal of Project Management, 1588-1596. https://doi.org/10.1016/j.ijproman.2015.04.003

Batselier, J., & Vanhoucke, M. (2017). Improving project forecast accuracy by integrating earned value management with exponential smoothing and reference class forecasting. International Journal of Project Management, 28-43. https://doi.org/10.1016/j.ijproman.2016.10.003

Bryde, D., Unterhitzenberger, C., & Joby, R. (2018). Conditions of Success for Earned Value Analysis in Projects. International Journal of Project Management, 474-484. https://doi.org/10.1016/j.ijproman.2017.12.002

Chen, H., Chen, W., & Lin, Y. (2016). Earned Value Project Management: Improving the Predictive Power of Planned Value. International Journal ofProject Management, 22-29. https://doi.org/10.1016/j.ijproman.2015.09.008

Cheng, M. Y., Cao, M. T., & Jaya, A. Y. (2021). Dynamic feature selection for accurately predicting construction productivity using symbiotic organisms search-optimized least square support vector machine. Journal of Building Engineering. https://doi.org/10.1016/j.jobe.2020.101973

de Andrade, P. A., Martens, A., & Vanhoucke, M. (2019). Using real project schedule data to compare earned schedule and earned duration management project time forecasting capabilities. Automation in Construction, 68-78. https://doi.org/10.1016/j.autcon.2018.11.030

Ghanbari, A., Taghizadeh, H., & Iranzadeh, S. (2017). Project Duration Performance Measurement By Fuzzy Approach Under Uncertainty. EUROPEAN JOURNAL OF PURE AND APPLIED MATHEMATICS, 1135-1147.

Hindami, G. G., Suroso, A., & Amin, M. (2014). Analysis of The Influence of Order Variation Factors on The Costs and Time of Implementing Channel Diverction Infrastructure Construction Projects in Residential Areas. Jurnal PenSil, 130-144. https://doi.org/10.21009/jpensil.v13i2.43872

Institute, P. M. (2021). Guide to the project management body of knowledge (PMBOK guide) - 7th Edition. Project Management Institute, Inc.

Jaber, F. K., Jasim, N. A., & Al-Zwainy, F. M. (2020). Forecasting techniques in construction industry: earned value indicators and performance models. Engineering and Environmental Sciences, 29(2), 234–243. https://doi.org/10.22630/PNIKS.2020.29.2.20

Journal, P. W. (2023). Earned Schedule: Forecasting Project Duration Increase from Rework. PM World Journal, 1-18.

Khamooshi, H., & Abdi, A. (2017). Project Duration Forecasting Using Earned Duration Management with Exponential Smoothing Techniques. Journal of Management in Engineering. https://doi.org/10.1061/(ASCE)ME.1943-5479.0000475

Khamooshi, H., I, M. M., & Kwak, Y. H. (2021). Project Duration Forecasting. Journal Modern PM, 09(27), 7-19. http://doi.org/10.1061/(ASCE)ME.1943-5479.0000475

Khesal, T., Saghaei, A., Galankashi, M. R., & Soltani, R. (2019). Integrated cost, quality, risk and schedule control through earned value management (EVM). Journal of Engineering, Design and Technology. https://doi.org/10.1108/JEDT-07-2018-0119

Kurniawan, H. A., Susilowati, F., & Jannah, R. M. (2024). Study on Implementation of Construction Waste Management in Minimizing Construction Material Waste. Jurnal PenSil, 1-12. https://doi.org/10.21009/jpensil.v13i1.37863

Lipke, W. (2015). Applying Statistical Forecasting of Project Duration To Earned Schedule-Longest Path. PM World Journal, 1-13.

Lipke, W. (2016). Examination of the Threshold for the To Complete Indexes 1. PM World Journal, 1-12.

Lipke, W. (2017). Assessing Earned Value Management and Earned Schedule Forecasting. PM World Journal, 1-15.

Lipke, W. (2017). Forecasting Schedule Variance Using Earned Schedule. PM World Journal, 1-9.

Lipke, W. (2020). Project Duration Increase from Rework. PM World Journal, IX(VI), 1-17.

Lipke, W. (2023). Earned Schedule: Forecasting Project Duration Increase from Rework. PM World Journal, 1-18.

Mahmoudi, A., Javed, S. A., & Deng, X. (2021). Earned Duration Management Under Uncertainty. Soft Computing, 8921-8940.

Martens, A., & Vanhoucke, M. (2019). The impact of applying effort to reduce activity variability on the project time and cost performance. European Journal of Operational Research. 277(2). 422-453. http://doi.org/10.1016/j.ejor.2019.03.020

Mayo-Alvarez, L., Alvarez-Risco, A., Del-Aguila-Arcentales, S., Sekar, M. C., & Yáñez, J. A. (2022). A Systematic Review of Earned Value Management Methods for Monitoring and Control of Project Schedule Performance: An AHP Approach. Sustainability. 14(22), 15259. https://doi.org/10.3390/su142215259

Miguel, A., Madria, W., & Polacos, R. (2019). Project Management Model: Integrating Earned Schedule, Quality, and Risk in Earned Value Management. IEEE 6th International Conference on Industrial Engineering and Applications, 38(3), 622-628. https://doi.org/10.1061/(ASCE)ME.1943-5479.0001019

Nadafi, S., Moosavirad, S. H., & Ariafar, S. (2019). Predicting the project time and costs using EVM based on gray numbers. Engineering, Construction and Architectural Management, 26(9), 2107-2119.

Nguyen, L. D., Le-Hoai, L., Tran, D. Q., Dang, C. N., & Nguyen, C. V. (2019). Effect of project complexity on cost and schedule performance in transportation projects. Construction Management and Economics, 384-399. https://doi.org/ 10.1080/01446193.2018.1532592

Nizam, A., & Elshannaway, A. (2019). Review of Earned Value Management (EVM) Methodology, its Limitations, and Applicable Extensions. The Journal of Management and Engineering Integration, 59-70.

Nkiwane, N. H., Meyer, W. G., & Steyn, H. (2016). The use of earned value management for initiating directive project control decisions: A case study. South African Journal of Industrial Engineering, 192-203. https://doi.org/10.7166/27-1-1260

Nurevita, M., & Anondho, D. B. (2020). Validasi Prediksi Durasi Dengan Metode Earned Schedule untuk Gedung Bertingkat di Jakarta. JMTS:, 3(2), 237-244. https://doi.org/10.24912/jmts.v3i2.7072

PMI. (2021). Guide to the project management body of knowledge (PMBOK guide). Project Management Institute, Inc.

Rachmawati, F., Mudjahidin, & Widowati, E. D. (2024). Work rate modeling of building construction projects using system dynamic to optimize project cost and time performance. International Journal of Construction Management, 24(2), 213-225. https://doi.org/10.1080/15623599.2022.2122265

Sackey, S., Lee, D. E., & Kim, B. S. (2020). Duration Estimate at Completion: Improving Earned Value Management Forecasting Accuracy. KSCE Journal of Civil Engineering, 24, 693-702. https://doi.org/10.1007/s12205-020-0407-5

Saputra, E. O., Muhammadun, H., & Marleno, R. (2024). Analysis of Remaining Project Cost Estimate Temporary Schedule (ETS) & Final Project Time Estimate All Schedule (EAS). International Journal of Social Science and Community Service, 2(3), 157-165. https://doi.org/10.70865/ijsscs.v2i3.18

Sheikhalishahi, M., Zadeh, S. A., Sardarabadi, A., & Naeimi, S. (2022). Improving Earned Value Management and Earned Schedule by Statistical Quality Control Charts Considering the Dependence between Cost and Schedule. Journal of Quality Engineering and Production Optimization, 7(1), 1-22. https://doi.org/10.22070/jqepo.2022.15415.1215

Tangtobing, R. F., & Waty, M. (2023). Penerapan Metode Earned Value dan Earned Schedule Pelaksanaan Proyek Rumah Sakit X di Bandung. JMTS: Jurnal Mitra Teknik Sipil, 6(2), 237-248. https://doi.org/10.24912/jmts.v6i2.22251

Urgilés, P., Claver, J., & Sebastián, M. A. (2019). Analysis of the earned value management and earned schedule techniques in complex hydroelectric power production projects: Cost and time forecast. Complexity, 1-10. https://doi.org/10.1155/2019/3190830

Vaibhava, S., Rao, B. P., Shetty, D. V., & Prakash, C. (2020). Application of earned value method and earned schedule method for a residential apartment. Journal of Physics: Conference Series. 25(1), 1469-1479. https://doi.org/10.69980/redvet.v25i1.929

Vanhoucke, M., Andrade, P., Salvaterra, F., & Batselier, J. (2015). INTRODUCTION TO EARNED DURATION. The Quarterly Magazine of the College of Performance Management, 15-27.

Votto, R., Lee Ho, L., & Berssaneti, F. (2020). Applying and Assessing Performance of Earned Duration Management Control Charts for EPC Project Duration Monitoring. Journal of Construction Engineering and Management. 146(3). https://doi.org/10.1061/(ASCE)CO.1943-7862.0001765

Wauters, M., & Vanhoucke, M. (2016). A comparative study of Artificial Intelligence methods for project duration forecasting. Expert Systems with Applications, 249-261. https://doi.org/10.1016/j.eswa.2015.10.008