BUS606: Operations and Supply Chain Management

Construction projects are being implemented with diversified contents and shortened plant construction time due to the rapid growth of the competitive modern market and the need for quickly profitable investments. Projects often fail to meet the original target schedule because of uncertainties. According to CoppendaIe and ChatzogIou and Macaulay, on the average, only 10% to 15% of large projects are completed on time, and the rest are delayed. Yang and Teng reported that construction projects are naturally uncertain in terms of activity duration and thus cause an indeterminate project completion schedule. Scheduling is possibly the most common issue in project planning and control because delays cause many problems between project owners and contractors. Delays in project completion aggravate the cost burden of projects. Delay claims for equitable adjustments can amount to millions of dollars. Thus, scheduling and cost risk analysis are crucial. Project managers must design and implement mitigating strategies to overcome the growing uncertainty faced by projects. Project risk management, a systematic risk assessment method for project implementation, provides a platform for owners and contractors to manage risks and communicate. The scope of actual project risk management includes environment safety and health, schedules, and costs. Project managers must formulate strategies for overcoming or avoiding the occurrence of uncertainties so that projects remain on track.

Schedule and cost are the two most important indicators in project practice. When project resources are limited, an alternative relationship exists between schedule and cost. Necessary crashing schedules must be planned in advance to complete projects on time. However, the completion times of projects are typically random variables due to numerous activities and unfixed project execution times. The first problem to be solved in the randomness of projects is estimating the project completion time. All issues, including project scheduling, project resource investment optimization, project cost, and project risk assessment, should be based on the expected project completion time. Most studies on project deadlines are limited to the development of a project crashing strategy rather than comprehensively evaluating project risk and crashing strategy simultaneously. Bromilow's log-log time-cost (BTC) model was proposed in the 1970s to estimate project duration, but different parameter estimates are required for different project types. The parameters of the BTC model have no guarantee and are invariant over time. Given this background, this study explores the probability of a potential project risk affecting the project completion schedule and the practical consideration of the time-cost trade-off. The probability of the project completion schedule by contract under risks is discussed through risk analysis, and the activities located on the critical path are identified through schedule sensitivity analysis. The relationship between activity time and crash cost is transformed into a mathematical model. The model is solved through linear programming to calculate the optimal crash cost. A set of project evaluation models considering risk and project crash plan and the relationship between crash cost and delay penalty is developed by using risk, cost, and schedule as indicators for assessing project feasibility. This study provides project managers a reference for management and strategy building in the bidding stage and increases the probability of projects being completed within the target time. To protect their interests, owners generally specify the required delay penalties in their contracts. If a project fails to meet the deadline, the project manager shall use proper management skills to implement schedule and cost control while considering the cost incurred by project crash plan and delay penalties. Balance between these two aspects should be achieved to complete a project successfully in accordance with the objectives and quality set by the plan.

This study applies the methods of Monte Carlo simulation using Primavera Risk Analysis software and integer linear programming coded using IBM ILOG CPLEX. These methods combine probabilistic activity duration with systematic delay analysis procedures to predict the overall project delay and estimate the additional cost brought about by a crash plan under risk consideration. This paper is structured as follows. Section 2 describes relevant studies and research issues. Section 3 provides the framework of the schedule risk analysis methodology and the formulation of the mathematical linear programming model. Section 4 focuses on the models proposed in Section 3 and presents an actual case study to illustrate the applications of the proposed models for evaluating project strategies. Section 5 presents the conclusions and discussions.