Revolutionizing Highway Waste Management with New Calculator

By Nidhi DhullReviewed by Susha Cheriyedath, M.Sc.Nov 19 2024

A recent study published in Scientific Reports introduces a novel Construction Waste Management Performance Assessment Method (CWMPAM) designed specifically for highway construction. Building on the foundation of the Site Waste Management Plan (SWMP), the research addresses a critical gap in real-time construction waste monitoring by incorporating the principles of Earned Value Management (EVM).

Background

CWM has emerged as a new core task in construction management, impacting overall project performance measurement. The SWMP has proven to be an effective measure to enhance CWM performance in construction activities.

However, SWMP focuses solely on general CWM guidelines, with limited attention to CWM’s dynamic achievements during construction. For instance, SWMP can quantify the CWM results during tasks like cleaning road base layers and excavating tunnel shafts, but it does not measure the excavation process.

A lack of standardized assessments of each activity during highway construction can compromise the accurate implementation of CWM, resulting in severe environmental pollution and economic losses. Moreover, this hinders continuous improvement in CWM.

By using EVM as a basis, this study aims to extend SWMP’s functionality, introducing a system capable of tracking and improving CWM performance during active construction phases.

Methods

To manage CW more effectively during highway projects, the researchers developed a computational tool as an extension of EVM using a deductive reasoning approach.

They began by breaking down benchmark projects into smaller components using the Work Breakdown Structure (WBS). Sub-projects were assigned weights based on their duration and CW production, calculated using the Least Absolute Shrinkage and Selection Operator (LASSO). These weights served as standard references for evaluating CWM practices.

The CWMPAM was then integrated with Construction Inspection Requests (RFI) in highway engineering, making it practical for real-world use. To account for variability in performance, Gray Linguistic Terms were used to define best-case and worst-case scenarios for CWM performance (CWMP). Specific calculation rules were also established to ensure consistency.

For inspections, each sub-project was assessed at 10 checkpoints, with results graded from “VL” (Very Low) to “VH” (Very High). A score of “MH” (Moderate-High) or above was considered satisfactory; otherwise, a second inspection was required following corrective actions. Additionally, a new metric called Construction Waste Consumption (CWC) was introduced to EVM, combining the executed CWM and its associated costs.

To validate the model, the researchers conducted a pilot run and a scenario analysis to test the CWMPAM and its integration with EVM. Following validation, the model was computerized into a calculator using Microsoft Excel and Matlab 2021a, enabling automatic performance monitoring for CWM. The calculator’s accuracy and practicality were confirmed by applying it to three randomly selected completed highway construction projects.

Discussion

The CWM-embedded EVM system provides a powerful tool for highway construction projects, offering several key benefits. It integrates the three critical project constraints—cost, schedule, and CWM—into a single, unified monitoring framework. This holistic approach introduces new metrics that enable project managers to track CWM performance based on specific project goals.

Unlike traditional post-project evaluation methods like lifecycle assessments, the CWMP calculator offers real-time monitoring and feedback. By incorporating SWMP and other industry standards, project managers can input cost and schedule data into the calculator to generate performance indices in real-time, enabling more proactive management.

The calculator balances flexibility and standardization, catering to the unique characteristics of highway construction while accommodating the diverse responsibilities of stakeholders. The use of grey numbers further enhances the system’s accuracy, mitigating issues like hidden tasks and potential data manipulation by construction personnel when calculating CWC.

The researchers successfully utilized SWMP as the foundation for developing the CWMPAM, introducing innovative values to enhance its application. By integrating grey processing into the CWM-embedded EVM, the model effectively reduces subjective biases. The potential of the CWMPAM to improve CWM practices in highway construction was validated through pilot runs and scenario analyses.

The CWMPAM supports continuous improvement during project implementation and facilitates cross-project comparisons by providing performance measurements for unit projects. Its newly introduced values and indicators complement traditional EVM, broadening its applicability in construction management.

However, this study is limited to highway engineering and does not encompass other types of infrastructure projects. Adjustments to construction tasks and management plans would be necessary to apply this approach to different engineering contexts. The researchers recommend incorporating blockchain technology into the model’s calculator to ensure accurate data reporting and further expand its application potential.

Journal Reference

Zheng, Z., Su, Y., Wang, X., & Zhou, Z. (2024). Developing a construction waste management performance calculator for highway construction. Scientific Reports, 14(1). DOI: 10.1038/s41598-024-79522-9, https://www.nature.com/articles/s41598-024-79522-9

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