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The purpose of this paper is to improve the productivity and quality of the wire arc additive manufacturing process by benchmarking the strategies from the selected six strategies, namely, heat treatment process, inter pass cooling process, inter pass cold rolling process, peening process, friction stir processing and oscillation process.

To overcome the lack of certainty associated with correlations and relationships in quality functional deployment, fuzzy numbers have been integrated with the quality functional deployment framework. Twenty performance measures have been identified from the literature under five groups, namely, mechanical properties, physical properties, geometrical properties, cost and material properties. Using house of quality weights are allocated to performance measures and groups, relationships are established between performance measures and strategies, and correlations are assigned between strategies. Finally, for each strategy, relative importance, score and crisp values are calculated.

Inter pass cold rolling process strategy is computed with the highest crisp value of 15.80 which is followed by peening process, heat treatment process, friction stir processing, inter pass cooling process,] and oscillation process strategy.

To the best of the authors’ knowledge, there has been no research in the literature that analyzes the strategies to improve the quality and productivity of the wire arc additive manufacturing process.

Today the research area on technology acceptance is mainly dependent on the theory of technology acceptance model (TAM). The TAM was used in this study primarily for the purpose of providing a basis for determining the impact of various external variables on the adoption of edtech platforms. The TAM is a theory of information systems that suggests steps for learners to take as they adopt and use new technologies. The primary TAM variables for adoption of edtech platforms are evaluated in this study: perceived usefulness (PU) and perceived ease of use (PEOU) by using the factors – perceived enjoyment (PE), information quality, electronic-word of mouth (e-WOM), perceived compatibility, computer self-efficacy and objective usability. By analyzing and defining the relationship between the external variables with respect to the adoption of edtech platform among students, we hope to contextualize the TAM model. The end result provides a clearer understanding of TAM and its growth as a useful model for technology adoption studies and for clarifying the relationship between the uptake of edtech platforms and technological acceptability. The study employed a qualitative methodology and selected publications and research papers about the adoption of technology. These were then carefully assessed, analyzed and scrutinized for the terms of how students adopted edtech platforms. It was proposed that the adoption of an edtech platform may result from proper training in technology usage and its application to real-world scenarios.