Sustainable Thermoplastic Material Selection for Hybrid Vehicle Battery Packs in the Automotive Industry: A Comparative Multi-Criteria Decision-Making Approach.

This research study employs a comparative Multi-Criteria Decision-Making (MCDM) approach to select optimal thermoplastic materials for hybrid vehicle battery packs in the automotive industry, addressing the challenges posed by high-temperature environments. Through a detailed evaluation of materials based on criteria such as thermal stability, mechanical strength, chemical resistance, and environmental impact, the research identifies materials that enhance battery efficiency, longevity, and vehicle performance. Utilizing SWARA-ARAS, SWARA-EDAS, and SWARA-TOPSIS methods, the study systematically assesses and ranks various polymers, providing recommendations that prioritize safety, performance, and sustainability.

Polymeric Materials Selection for Flexible Pulsating Heat Pipe Manufacturing Using a Comparative Hybrid MCDM Approach.

The right choice of polymeric materials plays a vital role in the successful design and manufacture of flexible fluidic systems, as well as heat transfer devices such as pulsating heat pipes. The decision to choose an acceptable polymeric material entails a variety of evaluation criteria because there are numerous competing materials available today, each with its own properties, applications, benefits, and drawbacks. In this study, a comparative hybrid multi-criteria decision-making (MCDM) model is proposed for evaluating suitable polymeric materials for the fabrication of flexible pulsating heat pipes.

A hybrid analytical model for an entire hospital resource optimisation.

Given the escalating healthcare costs around the world (more than 10% of the world's GDP) and increasing demand hospitals are under constant scrutiny in terms of managing services with limited resources and tighter budgets. Hospitals endeavour to find sustainable solutions for a variety of challenges ranging from productivity enhancements to resource allocation. For instance, in the UK, evidence suggests that hospitals are struggling due to increased delayed transfers of care, bed-occupancy rates well above the recommended levels of 85% and unmet A&E performance targets.

Healthcare systems and Covid19: Lessons to be learnt from efficient countries.

Background: The novel coronavirus is rapidly spreading over the world and puts the health systems of countries under intense pressure. High hospitalization levels due to the pandemic outbreak have caused the intensive care units to work above capacity.

Purpose: A data envelopment analysis (DEA) based modelling approach was developed to evaluate the effectiveness of regions (i.

A comprehensive modelling framework to forecast the demand for all hospital services.

Background: Because of increasing demand, hospitals in England are currently under intense pressure resulting in shortages of beds, nurses, clinicians, and equipment. To be able to effectively cope with this demand, the management needs to accurately find out how many patients are expected to use their services in the future. This applies not just to one service but for all hospital services.

A decision support system for demand and capacity modelling of an accident and emergency department.

Accident and emergency (A&E) departments in England have been struggling against severe capacity constraints. In addition, A&E demands have been increasing year on year. In this study, our aim was to develop a decision support system combining discrete event simulation and comparative forecasting techniques for the better management of the Princess Alexandra Hospital in England.