Wastewater management is increasingly emphasizing economic and environmental sustainability. Traditional methods in sewage treatment plants have significant implications for the environment and the economy due to power and chemical consumption, and sludge generation. To address these challenges, a study was conducted to develop the Intermittent Cycle Extended Aeration System (ICEAS). This approach was implemented as the primary technique in a full-scale wastewater treatment facility, utilizing key operational factors within the standard Sequencing Batch Reactor (SBR) process. The optimal operational approach, identified in this study, was put into practice at the research facility from January 2020 to December 2022. By implementing management strategies within the biological reactor, it was shown that maintaining and reducing chemical quantities, sludge generation, power consumption, and related costs could yield economic benefits. Moreover, adapting operations to influent characteristics and seasonal conditions allowed for efficient blower operation, reducing unnecessary electricity consumption and ensuring proper dissolved oxygen levels. Despite annual increases in influent flow rate and concentration, this study demonstrated the ability to maintain and reduce sludge production, electricity consumption, and chemical usage. Additionally, systematic responses to emergencies and abnormal situations significantly contributed to economic, technical, and environmental benefits.

In this paper, we present a new way to derive the mean cycle time of the G/G/m failure prone queue when the loading of the system approaches to zero. The loading is the relative ratio of the arrival rate to the service rate multiplied by the number of servers. The system with low loading means the busy fraction of the system is low. The queueing system with low loading can be found in the semiconductor manufacturing process. Cluster tools in semiconductor manufacturing need a setup whenever the types of two successive lots are different. To setup a cluster tool, all wafers of preceding lot should be removed. Then, the waiting time of the next lot is zero excluding the setup time. This kind of situation can be regarded as the system with low loading. By employing absorbing Markov chain model and renewal theory, we propose a new way to derive the exact mean cycle time. In addition, using the proposed method, we present the cycle times of other types of queueing systems. For a queueing model with phase type service time distribution, we can obtain a two dimensional Markov chain model, which leads us to calculate the exact cycle time. The results also can be applied to a queueing model with batch arrivals. Our results can be employed to test the accuracy of existing or newly developed approximation methods. Furthermore, we provide intuitive interpretations to the results regarding the expected waiting time. The intuitive interpretations can be used to understand logically the characteristics of systems with low loading.