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The COVID-19 pandemic compelled the education system to switch over to emergency learning-teaching that is organised remotely. The present study investigated the experience of emergency remote learning (ERL) provided to higher-education learners. The study explores learners' perceived experience regarding the quality of learning resources, the effectiveness of teaching in a virtual climate and the scope of interaction in ERL.

Utilising a snowball sampling method, data were obtained from 470 Indian students of higher education through a cross-sectional online survey using a questionnaire through social media platforms. Data were analysed with relevant statistics.

The majority of students agreed that they had benefited from ERL. The overall impression of the ERL is positive; nevertheless, the students are perplexed and lack confidence in many aspects of the ERL. The Quality of ERL Resources, Teaching Effectiveness, Peer Interaction and Workloads were found to be significant factors in determining the quality of ERL.

Learning from the crisis of a pandemic is paramount for the education system. The education system could not go back to what was considered normal before the pandemic; rather it is time to assess and finalise strategies from the experience during this pandemic that could be taken by the higher-education institutions to make the ecosystem better equipped to create 21st-century learning climate. Accommodating the components of remote learning-teaching and engaging technology towards hybridisation are the needs of the time. Hence, assessing the quality of ERL from the learner's perspective might contribute to redesigning future remote learning.

The modern helicopters are designed with maximum serviceability and long life expectancy to ensure minimum life cycle cost. The purpose of this paper is to present a framework to incorporate the customer requirements on reliability and maintainability (R&M) parameters into the design and development phase of a contemporary helicopter, and to discuss the way to capture operational data to establish and improve the R&M parameters to reduce life cycle cost.

From the analysis, it is established that the reliability and maintainability cost is the major contributor to the life cost. The significant reliability and maintainability parameters which influence R&M cost are identified from analysis. The operational and design data of a contemporary helicopter are collected, compiled and analyzed to establish and improve the reliability and maintainability parameters.

The process depicted in the paper is followed for a contemporary helicopter and substantial amount of life cycle cost reduction is observed with improvement of R&M parameters.

The benefits of this methodology not only reduce life cycle cost but also improve the availability/serviceability through less failure and less time for scheduled maintenance. The methodologies also provide the reliability trends indicating potential area for design improvement.

The proposed approach assists asset managers to reduce the life cycle costs through improvement of R&M parameters.

The purpose of this paper is to construct a fuzzy logic model that acts as a decision support system to minimize inventory-related costs in the field of industrial maintenance. Achieving a balance between the unavailability and over-storage of spare parts is a problem with potentially significant consequences. That significance increases proportionally with the ever-increasing challenge of reducing overall cost. Either scenario can result in substantial financial losses because of the interruption of production or the costs of tied-up capital, also called the “solidification of capital.” Moreover, there is that additional problem of the expiry of parts on the shelf.

The proposed approach relies on inputs from experts with consideration for incompleteness and inaccuracy. Two levels of decision are considered simultaneously. The first is whether a part should be stored or ordered when needed. The second involves comparing suppliers with their batch-size offers based on user-determined criteria. A mathematical model is developed in parallel for validation.

The results indicate that the fuzzy logic approach is accurate and satisfactory for this application and that it is advantageous because of its limited sensitivity to the inaccuracy and/or incompleteness of data. In addition, the approach is practical because it requires minimal user effort.

To the best of the authors’ knowledge, the exploitation of fuzzy-logic altogether with limited sensitivity experts' inputs were never combined for the solution of this particular problem; however, this approach's positive impact is expected to be highly significant in solving a chronic problem in industry.