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The purpose of this paper is to present the multi-objective optimization of the dynamic response of isotropic and laminated composite folded plates. The dynamic analysis has been carried out using the finite element method based on the first-order shear deformation theory.

Hamilton’s principle has been employed for the derivation of the governing equations. Natural frequencies are obtained using the eigenvalue extraction method. The optimal combination of the crank angle, lamination scheme and boundary conditions on the natural frequencies of folded plates for their safe and optimal dynamic design has been obtained. The analysis has been carried out using finite element approach based on FSDT to obtain the dynamic equation of single- and double-fold laminated plates. In total, 15 experiments as per Taguchi’s standard L₁₅ orthogonal array have been performed. Further, standard deviation (SD) based TOPSIS method is used to perform multi-response optimization of folded plates in order to rank the combination of the input parameters.

SD integrated with TOPSIS reveals that Experiment No. 8 (crank angle=90° and anti-symmetric lamination scheme=0°/90°/0°/90°), Experiment No. 14 (crank angle=150° and anti-symmetric lamination scheme=0^o/90^o/0^o/90^o), Experiment No. 2 (crank angle=30° and anti-symmetric lamination scheme=0°/90°/0°/90°) and Experiment No. 3 (crank angle=30° and symmetric lamination scheme=0°/90°/0°/90°) occupy rank 1 for one fold, one end clamped, one fold, two ends clamped, two folds, one end clamped and two folds, two ends clamped conditions, respectively, in order to maximize the modal response corresponding to the fundamental mode.

SD-based technique for order of preference by similarity to ideal solution (TOPSIS) method is used to rank the process parameters. The optimum combination of the input parameters on the multi-response optimization of dynamics of the folded plates has also been evaluated using the analysis of mean (ANOM).

The purpose of this study is to analyze the titanium alloy under heat treated condition. Titanium alloy heat treatment, particularly Ti‐6Al‐4V alloy, has been an important field of study due to its wide variety of uses in the aerospace, automotive, and biomedical sectors. The mechanical characteristics of titanium alloys are heavily influenced by their microstructure. Cold‐rolled Ti‐alloys have strong bending and tensile strength due to extensive β‐phase precipitation on the α matrix. However, various heat treatment (HT) methods can affect the mechanical characteristics. The current study seeks to investigate the effects of various heat treatment procedures on the microstructural and mechanical changes of Ti‐6Al‐4V alloy, in order to achieve an optimal balance of strength, hardness, and ductility for a variety of real-world applications.

Three plates of Ti‐6Al‐4V alloy were heated above the β‐transus temperature for a certain period and then cooled via furnace, air, and sand. One extra plate was kept in ‘untreated’ condition and given name ‘as received’ plate. The three heat treated plates were evaluated and compared with ‘as received’ plate based on tensile strength, bending strength, hardness, and microstructural changes.

A considerable change in orientation of α and β was noted through optical microscopy upon heat treatment. The mechanical testing revealed that all the cooling methods adopted in the study have reduced the UTS and increased the YS of the plates. The ductility of the alloy was primarily enhanced by 'air cooling' and 'sand cooling' methods.

Notably, the hardness test findings indicated a significant drop in hardness for the ‘sand‐cooled’ sample. Furthermore, the ‘air cooled’ sample showed the maximum hardness due to the production of acicular α regions.

The transition to omnichannel retail is the recognized future of retail, which uses digital technologies (e.g. augmented reality shopping assistants) to enhance the customer shopping experience. However, retailers struggle with the implementation of such technologies in brick-and-mortar stores. Against this background, the present study investigates the impact of a smartphone-based augmented reality shopping assistant application, which uses personalized recommendations and explainable artificial intelligence features on customer shopping experiences.

The authors follow a design science research approach to develop a shopping assistant application artifact, evaluated by means of an online experiment (n = 252), providing both qualitative and quantitative data.

Results indicate a positive impact of the augmented reality shopping assistant application on customers' perception of brick-and-mortar shopping experiences. Based on the empirical insights this study also identifies possible improvements of the artifact.

This study's assessment is limited to an online evaluation approach. Therefore, future studies should test actual usage of the technology in brick-and-mortar stores. Contrary to the suggestions of established theories (i.e. technology acceptance model, uses and gratification theory), this study shows that an increase of shopping experience does not always convert into an increase in the intention to purchase or to visit a brick-and-mortar store. Additionally, this study provides novel design principles and ideas for crafting augmented reality shopping assistant applications that can be used by future researchers to create advanced versions of such applications.

This paper demonstrates that a shopping assistant artifact provides a good opportunity to enhance users' shopping experience on their path-to-purchase, as it can support customers by providing rich information (e.g. explainable recommendations) for decision-making along the customer shopping journey.

This paper shows that smartphone-based augmented reality shopping assistant applications have the potential to increase the competitive power of brick-and-mortar retailers.