A new personalized environment control system for hospital beds with design optimization by Taguchi-based grey relational analysis

Abstract

The current ward environments consume excessive energy and fail to meet the personal comfort and health needs of patients. A promising solution is to create a personalized bed micro-environment and then extend the ward set-point temperature range. However, there is currently no suitable bed environment control system. This study proposes a novel bedside integrated system with three perforated panels that supplies conditioned air from different directions and prevents direct airflow towards the patient's head region. The system design was optimized using Taguchi-based grey relational analysis (GRA), with predicted mean vote (PMV), draft risk (DR), and personal exposure effectiveness (PEE) considered as response variables. The design variables included supply air temperature, airflow rate, and supply air angles. Taguchi's L₁₆ (4⁴) orthogonal array was employed for the experimental design. The results demonstrate that a low-velocity cold air lake can form above the bed, with the maximum velocity near the patient's head at only 0.2 m/s. In a 28 °C ward, the PMV, maximum DR, and PEE at the bed micro-environment are 0.13, 14.1 %, and 0.67, respectively. This implies that the proposed bed environment control system has the potential to provide both comfort and health benefits while reducing energy consumption. After optimization, the optimal supply air temperature, airflow rate, angles of top panel and side panels are 22 °C, 25 L/s, 0° and 45°, respectively, with an improvement of 5.8 % in the grey relational grade. This study provides a new solution for creating a comfortable and healthy ward environment in an energy-efficient manner.