BUS606: Operations and Supply Chain Management

Different factors and teams are involved in the execution of large sustainable projects that should be managed correctly and rapidly to prevent inconsistency. This problem has led to the emergence of project control science. The aim of creating this knowledge is to manage a large team of engineers, workers, and employers to complete a project in the shortest period possible. In addition to time, other factors are also effective. Budget, pre-determined purposes, and project risks are problems that should be considered in the execution of each project. The main purpose of project management and control is to adopt an optimal method to direct the triangle of time, budget, and purposes with regard to different risks. However, according to previous studies, this knowledge was not successful in fulfilling its purposes and did not progress after the invention of Gant's diagram in 1910 until the modern techniques of EVM/ES and CCM/BM were introduced for the better management of projects. Using these techniques, different researchers have attempted to find solutions for project control problems using modern management theories. The following articles feature these solutions.

In sustainable projects, the focus is directed towards three main parameters; namely, economic development, preserve of environment, and increasing social welfare. To develop sustainable projects, a methodology is needed to concurrently control both quantitative parameters (time and cost) and risks (e.g., environmental and social risks). In the majority of techniques in the scope of control projects, such as CCM/BM and EVM/ES, it is impossible to provide such a concurrent control and, therefore, they are not sufficiently conclusive to be used for sustainable projects. Owning to the fact that the proposed methodology meets the above needs, it turns out to be an appropriate technique for the control of sustainable projects. Obviously, if a technique works well for sustainable projects, it can be applied to other economic and investment projects as well.

Vanhoucke and Vandevoorde reviewed earned value project management as a method that employs scope, cost, and schedule to measure and communicate the real physical process of a project; it is the most commonly used project performance forecasting approach. According to a study on the usefulness of earned value project management for monitoring and predicting project performance, earned value project management is an important component of successful project management, and considerable research on its extensions and applications has been published. Chou et al. developed earned value project management into a Web-based visualized implementation system that enables managers to monitor, evaluate, and estimate a project's financial and scheduling performance by converting project data into manageable information clusters.

In another study, a new forecasting method was developed based on the Kalman filter (known as linear quadratic estimation, which is an algorithm that uses a series of measurements observed over time, contains statistical noise and other inaccuracies, and produces estimates of unknown variables that tend to be more precise than those based on a single measurement alone) and the earned schedule method. Probabilistic forecasting of project duration was conducted using the Kalman filter and the earned value method. In one study, software development projects for resource-constrained problems were analyzed and given solutions; an improved root square error was suggested; the setting method of buffer sizes, which is suitable for software development projects, was adopted; and the preemptive scheduling method based on a heuristic algorithm and priority rules was used to plan the scheduling. Czarnigowska et al. outlined the basic principles of the method and discussed its recent modifications to improve reliability in describing the project status. Naeni et al. presented a new fuzzy-based earned value model with the advantage of developing and analyzing the earned value indices and the time and cost estimates at completion under uncertainty. Hanna presented a case study to illustrate the use and applicability of earned value project management in the electrical construction industry. He concluded that the early determination of probable project outcomes is possible with reasonable forecasting accuracy using earned value project management. Acebes et al. proposed an innovative and simple graphical framework for project control and monitoring to integrate the dimensions of project cost and schedule with risk management, thereby extending the earned value methodology. Elshaer refined the earned value project management and earned schedule methods by integrating activity-based sensitivity information into the earned value calculations to remove and/or decrease false warning effects caused by non-critical activities, thus improving the forecasting accuracy of project durations during project execution.

Vanhoucke and Colin assessed four multivariate regression methods for monitoring the activity level performance of an ongoing project from earned value project management/earned schedule observations. One method was proposed to provide considerable capability to project managers to analyze schedule performance. The public's first view of earned schedule was with the publication of Schedule is Different. In determining whether a relationship exists among the schedule, cost, quality, and scope of a project, the use of cost to control duration proved to be confusing. Khamooshi and Golafshani developed the earned duration management (EDM) in contrast to the earned value and earned schedule. This method separates the schedule and cost performance measures, and introduces a number of indices to measure the progress, schedule and cost performance, and efficiency of the plan at any level of the project. The newly-developed duration performance measures are schedule-based and can be used for forecasting the completion date of the project. Chen proposed a linear data transformation formula and used data from 131 sample projects to demonstrate that the formula significantly improves the correlations between planned value and earned value and between planned value and actual cost. Colin and Vanhoucke proposed a new statistical project control procedure to set tolerance limits to improve the discriminative power in progress situations that are either statistically likely or less likely to occur under the project baseline schedule. In this research, the tolerance limits are derived from subjective estimates for the activity durations of the project. Tolerance limits are set for statistical project control using EVM.

A multi-objective optimization model, which considers multi-objectives, such as overall duration, financing costs, and whole robustness, was developed for multi-project scheduling in a critical chain. Yang and Fu proposed a multi-project schedule method based on task priority, evidence reasoning, and critical chain approach. As the float time of a non-critical chain is the primary concern for setting feeding buffers, Peng and Huang simplified the procedure of generating a critical chain project plan to remarkable extent. Ma et al. proposed an improved critical chain project management framework to enhance the implementation of critical chain project management in the practice of construction project management. The framework addresses two major challenges in critical chain project management-based construction scheduling: buffer sizing and multiple resources leveling.

Acebes et al. suggested a framework based on earned value project management, Monte Carlo simulation, and statistical learning techniques for project control under uncertainty. Willems and Vanhoucke presented an overview of the existing literature on project control and EVM to fulfill three goals (to discern between high-quality journals and more popular business magazines, collected papers on project control and EVM and classification framework indicating current trends and potential areas for future research). Ghaffari and Emsley covered 140 journal and conference papers on critical chain project management using an "exhaustive with selective citation" approach identified through online and reference searching. One study determined the current status and future potential of the research on critical chain project management. Batselier and Vanhoucke evaluated the accuracy and timeliness of three promising deterministic techniques and their mutual combinations on a real-life project database. Colin et al. showed that these multivariate schedule control metrics lead to performance improvement and practical advantages in comparison with traditional EVM/earned schedule models. A multivariate approach was used for top-down project control using EVM. Chen et al. proposed a straightforward modeling method for improving the predictive power of planned value before executing a project. By using this modeling method, the earned value and actual cost forecasting models were developed for four case projects.

One of the challenges in CCM/BM is the sufficient sizing of the buffers. If the buffers are estimated more than the necessary size, practical consequences immediately occur. Conversely, if the buffers are underestimated, they may increase the probability of duration overruns, which can cause financial penalties and a reliable loss on the part of the customers or market. Sarkar and Babu attempted to apply these concepts and explored the advantages of applying CPM/BM to a complex mega infrastructure project, such as the construction of an elevated corridor for metro rail operations, and to compute the buffer size using some of the available methods. A buffer sizing method based on comprehensive resource tightness was proposed to better reflect the relationship among activities and to improve the accuracy of project buffer determination. Wei et al. incorporated EVM into engineering PM practices. Indices such as the budgeted cost of work scheduled, the budget cost of work performed, and the actual cost of work performed, as well as the correlation between the schedule performance index and cost were also included. In one study, the EVM methodology was explored, and a model to manage the aerospace engineers of a project was proposed based on a real case study.

Although the above mentioned articles and studies are theoretically interesting, the applied projects were difficult to implement because of the lack of simultaneous control of qualitative and quantitative parameters. In the current study, we present a risk–efficiency integrated methodology in project control by combining the EVM/ES and CCM/BM techniques, including time and cost buffers. This model utilizes the unique advantages of the CCM technique, simultaneously controls the time and cost of the project, and verifies all the risks and control measures. In other words, this study addresses the problems and limitations of previous studies and techniques by presenting this integrated technology. Table 1 summarizes the comparison between the project control methods used in previous studies and the proposed model.

Table 1. Research taxonomy of control project methods based on the critical chain method (CCM) and earned value management (EVM).

The efficiency-risk hybrid model combines the EVM/ES and CCM/BM techniques. The rest of this article is organized as follows: the CCM/BM technique is explained in Section 2 and the EVM/ES technique in Section 3. The efficiency–risk methodology is presented to control the sustainable projects in Section 4. This methodology extracts the key point of the combined EVM/ES and CCM/BM techniques, presents new formulas to calculate the time and cost buffers of the project, and estimates the necessary budget and time to complete the project. In Section 5, one case study is presented to explain the proposed algorithm, and the obtained results are given.