Green Operation Strategies in Healthcare for Enhanced Quality of Life.

Healthcare services have now become a fundamental requirement for all individuals owing to rising pollution levels and shifting lifestyles brought on by fast modernization. The hospital is a specialized healthcare facility where doctors, nurses, and other medical professionals offer their services. Academics and professionals have emphasized green operation initiatives such as green design, green purchasing, green supply chain, and green manufacturing to increase public awareness of environmental problems affecting company operations associated with healthcare for the quality of life. The purpose of this research is to use total interpretive structural modeling and MICMAC (matrix cross multiplication applied to a classification) analysis to investigate and analyze the elements impacting green operations strategies in healthcare. The data are gathered using a closed-ended questionnaire together with a scheduled interview. The components' interactions are explored using the total interpretive structural modeling technique, and the MICMAC analysis is used to rank and categorize the green operation strategy variables. The study is a novel effort to address and focus on stakeholders, vision and structure, resources, and capabilities. Green operations strategies have only been the subject of a small number of studies in the past, and those studies were mostly addressed at manufacturing-specific green strategies. Thus, by promoting energy efficiency programs, green building design, alternative sources of energy, low-carbon transportation, local food, waste reduction, and water conservation, the health sector can develop multiple key strategies to become more climate-friendly with significant health, environmental, and social co-benefits for quality of life.

Comparison of Laser Milling Performance against Difficult-To-Cut Alloys: Parametric Significance, Modeling and Optimization for Targeted Material Removal.

During laser milling, the objective is not always to maximize the material removal rate (MRR). Milling of new material with targeted MRR is challenging without prior knowledge and established sets of laser parameters. The laser milling performance has been evaluated for three important aerospace alloys, i.e., titanium alloy, nickel alloy and aluminum alloy using the response surface method experimental plan (54 experiments for each alloy). Parametric effects of five important laser parameters, statistical analysis (main effects, interaction effects, strength and direction of effects), mathematical modeling and optimality search is conducted for the said alloys. Under the non-optimized laser parameters, the actual MRR significantly varies from the targeted MRR. Variation in the aluminum alloy is at the top as compared to the other two alloys. Among other significant terms, three terms have the largest effect on MRR in the case of TiA, two terms in the case of NiA, and five terms in the case of AlA. Under the optimized sets of laser parameters, the actual material removal highly close to the desired level (100%) can be achieved with minimum variation in all the three alloys. Mathematical models proposed here have the capability to well predict material removal prior to the actual machining of Ti6Al4V, Inconel 718 and AA 2024.