Water absorption characteristics of composites are crucial to robust composite design with integrity and long service lives. In the literature, scholars have evaluated the water absorption properties of cocoa pod husk composites but reports regarding their uncertainty and imprecision are missing. In this article, cocoa pod husk particulate reinforced composite material was analyzed for uncertainty and imprecision using the fuzzy analytic process to rank and select the important parameters of the water absorption process. Experimental data from a project were collected and analyzed considering particulate loading, initial weight, particulate weight, the weight of the matrix, weight gained after 150 days and rate of water absorption as parameters.The parameters were sensitive and active and the findings provide new procedures to analyze thermoset composites under the circumstances of uncertainty and imprecision. This work aids to effectively produce composites of integrity, long lifespan and retain customers in the competitive composite market.

In boring E250 B0 steel material, the selection of process parameters is one of the most challenging tasks to achieve. The boring literature lacks understanding and fails to reveal how to select the important boring parameters for utmost resource distribution to the most important parameters. This article proposes a novel method to analyse the importance of parameters in boring to produce utmost surface roughness using the entropy-decision tree-VIKOR approach as a multi-criteria decision-making solution to the choice of process materials for superior surface roughness. The choice parameters include speed, depth of cut, feed and nose radius. The entropy approach was instituted to attain the weight of the diverse parameters. The decision tree approach is deployed through the classification of the parameters as beneficial and non-beneficial and the expected values at each mode evaluated. The desirable weightage is then established and serves as the input to the VIKOR approach. This converts the desirable weightage into unit measures through the best/worst value and weightage evaluation. The individual regrets are then analyzed and the final ranking obtained. Results revealed that the depth of cut is the most important parameter, then nose radius (0.98), feed (0.307) and speed (0), respectively. Therefore, a plan to assign more measures to the depth of cut may be developed and the least resources may be assigned to speed. This detail may be helpful to prepare the annual budgets for the boring operation on the factory floor.

This paper establishes how the process engineer in a machine shop could capture the uncertainty and the transition of process parameters to improve the surfaced finish of bored work material (carbon steel IS 2062 GR E250 plates) and select the best parameters to achieve the aim. The fuzzy analytic hierarchy process method incorporating geometric mean and a novel Markov chain oriented weightage scheme were used as inputs into three multicriteria methods of weighted sum model (WSM), weighted product model (WPM) and weighted product model and weighted aggregated sum-product, assessment (WASPAS) model. Published literature data were used to validate the methods and their integrations. The novel Markov chain model borrows ideas from the orthogonal array, random number generation and the transition states of parameters. Finally, the optimal parametric setting idea is used to interprete the final results based on an initial response table determination, which are the averages of the signal-to-noise ratios summarized. The most important results are obtained from the fuzzy AHP-Markov WASPAS method. These are the feed parameter (preference score of 1.624) as the best parameter and the depth of cut with the preference score of 1.188 as the worst parameter. The findings indicate that process engineers should attach the most important interest to the feed rate as it is the most effective controlling parameter of surface finish during the boring operation of carbon steel IS 2062 GR E250 plates. Machining shops can employ the framework to evaluate and predict system performance before financial resource commitment to operations.

Polymer composites are expanding in scope and applications to water-based structures such as the ship's hull in ship vessels due to their resistance to water and satisfactory mechanical properties. Unforunately, few studies have tackled their water absorption properties. In this paper, a novel method, DEMATEL, is used to analyse the conflicting water absorption process parameters of cocoa pod husk composite using the cause and effect associations of the parameters. The parameters considered are particulate loading, initial weight, particulate weight, the weight of the matrix, and weight after 150 days and rate of water absorption. A comparison scale explains the extent of influence of a criterion on the other. The direct relationship matrix is normalized and the total relation matrix generated to procedure a causal diagram. The most fascinating findings of the study are the differences between the sum of row and columns, which places particulate weights as the most appealing, 1.0798, while the rate of water absorption as the least appealing criterion. Besides, the sum of the row and column that yields the most attractive results is the particulate weight (5.4982) while the least attractive result is the rate of water absorption (3.5436). The novelty of this work lies in the application of DEMATEL structure to examine contextual associations between the essential pointers of water absorption process parameters, for cocoa pod husk composites in the water environment. To our knowledge, it is the first type of work in this area on the selected agro-filler-based composite.

In the industrial transformation of animal feed for chickens, downtime analysis is a crucial part of the plant's operations. Unfortunately, the literature on downtime analysis has a serious shortcoming; it fails to link downtime with Taguchi method’s optimization and ranking. To correct this deficiency, this paper proposes a new method that couples the Taguchi scheme with the weighted sum method (WSM), weighted product method (WPM) and weighted aggregated sum product assessment (WASPAS) method. A new model was developed to contain downtime factors, levels, orthogonal matrix, signal-to-noise proportions, normalisation indices, criteria weights and preference scores. The results of the Taguchi-WSM, Taguchi-WPM and Taguchi-WASPAS show that workstation 2 has the highest rankings of 0.8446, 8.9090 and 4.8770 for the Taguchi-WSM, Taguchi-WPM and Taguchi-WASPAS, respectively. Also, the lowest rankings of 0.1553, 6.7990 and 3.4800 were recorded for workstation 1 using the Taguchi-WSM, Taguchi-WPM and Taguchi-WASPAS methods, respectively. However, from literature reports, WASPAS has been associated with the best results compared to WSM and WPM. Hence, from the various results of prioritizing workstations 1 and 2, the results of the Taguchi-WASPAS method are recommended. This is the first time the downtime problem for animal feed processing equipment will be approached by a joint optimization and ranking with the Taguchi scheme, WSM, WPM and WASPAS multicriteria methods.