Controlling and enhancing performance using QM-window in queuing models
Author(s): AI Eldesokey and AM Ben Aros
Abstract: The Queuing phenomenon is considered as one of the most frequently observed occurrences in different service industries. It has experienced a significant development in recent years as a result of economic development and population growth, which has increased the pressure on these sectors to produce high-quality services that meet customer requirements, satisfy consumers, and maximize available resources. All previous challenges and variables surrounding service sectors have necessitated the search for a scientific technique that contributes to enhancing performance and overcoming challenges and obstacles related to service supply. Queuing models are regarded as one of the most significant scientific tools for resolving various waiting phenomena related with actual service delivery. Especially in the sector of health care services in Libya where the main challenge that almost every major hospital faces is waiting in line. It may be time to wait long reflection for incompetence in hospital operations. In this regard, this study provided an overview of queuing models, emphasizing their role and significance in monitoring and improving performance using QM-Window software, which is one of the specialised programs in data science that facilitates obtaining performance indicators and recognizing through them the representative model of the service and its acceptability or proposing an alternative model.
AI Eldesokey, AM Ben Aros. Controlling and enhancing performance using QM-window in queuing models. Int J Stat Appl Math 2023;8(2):101-108. DOI: 10.22271/maths.2023.v8.i2b.959