Multi-objective transportation problem under type-2 trapezoidal fuzzy numbers with parameters estimation and goodness of fit

The problem of transportation in real-life is an uncertain multi-objective decision-making problem. In particular, by taking into account the conflicting objectives, Decision-Makers (DMs) are looking for the best transport set up to determine the optimum shipping quantity subject to certain capacity constraints on each route. This paper presented a Multi-Objective Transportation Problem (MOTP) where the objective functions are considered as Type-2 trapezoidal fuzzy numbers (T2TpFN), respectively. Demand and supply in constraints are in multi-choice and probabilistic random variables, respectively. Also considered the “rate of increment in Transportation Cost (TC) and rate of decrement in profit on transporting the products from ith sources to jth destinations due to” (or additional cost) of each product due to the damage, late deliveries, weather conditions, and any other issues. Due to the presence of all these uncertainties, it is not possible to obtain the optimum solution directly, so first, we need to convert all these uncertainties from the model into a crisp equivalent form. The two-phase defuzzification technique is used to transform T2TpFN into a crisp equivalent form. Multi-choice and probabilistic random variables are transformed into an equivalent value using Stochastic Programming (SP) approach and the binary variable, respectively. It is assumed that the supply and demand parameter follows various types of probabilistic distributions like Weibull, Extreme value, Cauchy and Pareto, Normal distribution, respectively. The unknown parameters of probabilistic distributions estimated using the maximum likelihood estimation method at the defined probability level. The best fit of the probability distributions is determined using the Akaike Information Criterion (AIC) and the Bayesian Information Criterion (BIC), respectively. Using the Fuzzy Goal Programming (FGP) method, the final problem is solved for the optimal decision. A case study is intended to provide the effectiveness of the proposed work

Effect of different impression techniques on marginal fit of restoration – An In Vitro study

Introduction: Impression making is one such important clinical step, which is critical in the accurate fitting of resulting prostheses. Impression making itself depends on the type of material and the impression technique used to record the details. Various combinations of material and the technique have been described in the literature. Aim: To evaluate the effect of three different impression techniques on the marginal fit of computer-aided designed/computer-aided manufactured (CAD/CAM) single unit composite fixed dental prostheses (FDP), different consistencies of addition silicone impression material and different tray design were utilized. Method: Impression of prepared tooth on typodont was made using Matrix impression system, two-step putty wash technique, and individual tooth tray technique. Prosthesis was fabricated using CAD/CAM technology and marginal accuracy was evaluated using scanning electron microscopy (SEM). Result: In the present study, the matrix impression system resulted in less microgap in both mid-buccal and mid-mesial region, whereas putty wash technique showed very high standard deviation in the interproximal region. Conclusion: Matrix impression system had the best results at both mid-buccal and mid-mesial position with least marginal discrepancy. Clinical Implication: The findings of this study could be used by clinicians to help them choose the viscosity of polyvinylsiloxane material and impression techniques for FDP that will result in high-accuracy impressions and well-fitting prostheses

Improvements in the Engineering Properties of Cementitious Composites Using Nano-Sized Cement and Nano-Sized Additives

The findings of an extensive experimental research study on the usage of nano-sized cement powder and other additives combined to form cement–fine-aggregate matrices are discussed in this work. In the laboratory, dry and wet methods were used to create nano-sized cements. The influence of these nano-sized cements, nano-silica fumes, and nano-fly ash in different proportions was studied to the evaluate the engineering properties of the cement–fine-aggregate matrices concerning normal-sized, commercially available cement. The composites produced with modified cement–fine-aggregate matrices were subjected to microscopic-scale analyses using a petrographic microscope, a Scanning Electron Microscope (SEM), and a Transmission Electron Microscope (TEM). These studies unravelled the placement and behaviour of additives in controlling the engineering properties of the mix. The test results indicated that nano-cement and nano-sized particles improved the engineering properties of the hardened cement matrix. The wet-ground nano-cement showed the best result, 40 MPa 28th-day compressive strength, without mixing any additive compared with ordinary and dry-ground cements. The mix containing 50:50 normal and wet-ground cement exhibited 37.20 MPa 28th-day compressive strength. All other mixes with nano-sized dry cement, silica fume, and fly ash with different permutations and combinations gave better results than the normal-cement–fine-aggregate mix. The petrographic studies and the Scanning Electron Microscope (SEM) and Transmission Electron Microscope (TEM) analyses further validated the above findings. Statistical analyses and techniques such as correlation and stepwise multiple regression analysis were conducted to compose a predictive equation to calculate the 28th-day compressive strength. In addition to these methods, a repeated measures Analysis of Variance (ANOVA) was also implemented to analyse the statistically significant differences among three differently timed strength readings