he VIKOR (Vlse Kriterijumska Optimizacija Kompromisno Resenje which means multi-criteria optimization and compromise solution, in Serbian) method has already become a quite popular multi-criteria decision making tool for its computational simplicity and solution accuracy. This method focuses on selecting and ranking from a set of feasible alternatives, and determines compromise solution for a problem with conflicting criteria to help the decision maker in reaching a final course of action. It determines the compromise ranking list based on the particular measure of closeness to the ideal solution. Depending upon the type of decision problem and necessity of the decision maker, apart from VIKOR method, different variants of it, like comprehensive VIKOR, fuzzy VIKOR, regret theory-based VIKOR, modified VIKOR and interval VIKOR methods have also been subsequently developed. In this paper, the ranking performance of original VIKOR method and its five variants is analyzed based on two demonstrative examples. It is observed that interval VIKOR method performs unsatisfactorily and when the information in a decision problem is imprecise, fuzzy VIKOR method should always be preferred. But, for any decision problem, original VIKOR is the best method for solution without unnecessarily complicating the related mathematical computations.

In the present work, a multi-response optimization method is used to optimize the machining parameters in turning of glass fiber reinforced polymer (GFRP) composites. Parameters like spindle speed (N), feed rate (f) and depth of cut (d) are taken to obtain the responses such as surface roughness (Ra) and material removal rate (MRR). Taguchi’s L9 orthogonal array has been used for machining the work-piece. Analysis of variance (ANOVA) has been carried out to check the significant process parameter in a single objective performance characteristic. The multiple performance characteristics have been analysed using Grey relational analysis and an appreciable result has been reported with this approach.

The objective of this paper is to develop an integrated production inventory model for reworkable items with exponential demand rate. This is a three-layer supply chain model with perspectives of supplier, producer and retailer. Supplier delivers raw material to the producer and finished goods to the retailer. We consider perfect and imperfect quality products, product reliability and reworking of imperfect items. After screening, defective items reworked at a cost just after the regular manufacturing schedule. At the beginning, the manufacturing system starts produce perfect items, after some time the manufacturing system can undergo into “out-of-control” situation from “in-control” situation, which is controlled by reverse logistic technique. This paper deliberates the effects of business strategies like optimum order size of raw material, exponential demand rate, production rate is demand dependent, idle times and reverse logistics for an integrated marketing system. Mathematica is used to develop the optimal solution of production rate and raw material order for maximum expected average profit. A numerical example and sensitivity analysis is illustrated to validate the model.

This paper derives a production inventory model over infinite planning horizon with flexible but unreliable manufacturing process and the stochastic repair time. Demand is stock dependent and during the period of sale it depends on reduction on selling price. Production rate is a function of demand and reliability of the production equipment is assumed to be exponentially decreasing function of time. Repair time is estimated using uniform probability density function. The objective of the study is to determine the optimal policy for production system, which maximizes the total profit subject to some constraints under consideration. The results are discussed with a numerical example to illustrate the theory.

Machining of hardened work materials with appropriate levels of process parameters is still a burning issue in manufacturing sectors and challenging. It is because of pressing demand of surface quality which adversely affected by evolution of tool wear. Therefore the present investigation is undertaken to make a decision on parametric optimization of multi-responses such as flank wear and surface roughness during machining hardened AISI 52100 steel (55±1) steel using mixed ceramic insert under dry environment through grey relational analysis combined with Taguchi approach. Also predicted mathematical models of 1st and 2nd order have been developed for responses and checked for its accuracy. Second order mathematical model presented higher R2 value and represents best fit of the model and adequate compared to first order model. Model indicates good correlations between the experimental and predicted results. The proposed grey-based Taguchi methodology has been proved to be efficient for solving multi-attribute decision making problem as a case study in hard machining environment.

In this study, we develop a three echelon supply chain model for items to determine the optimal reliability and production rate, which achieves the biggest total integrated profit for an imperfect manufacturing process. Here, we have taken a supplier, a manufacturer and a retailer in which supplier supplies raw materials to manufacturer, manufacturer produces perfect and imperfect quality items because practically it happens and manufacturer supplies perfect quality items to the retailers. In production system, production facility may shift from an in-control state to an out-of-control state at any random time. The basic assumption of classical economic manufacturing quantity model is that all manufacturing items are of perfect quality but the assumption is not true in practice. The proposed study is formulated assuming that a certain percent of total product is defective. This percentage also varies with production rate and production run time. The defective items are restored in original quality by reworked at some costs to maintain the quality of products in a competitive market. Finally, numerical example and its graphical representation are given to illustrate the proposed model. Sensitivity analysis is also provided to test feasibility of the model.

A series of semicarbazones, thiosemicarbazones, 1,3,4-oxadiazoles/thiadiazoles bearing pyrazole scaffold were designed and synthesized. All the synthesized new compounds were characterized by 1H NMR, 13C NMR, MS and elemental analysis. The synthesized compounds were screened to probe their in vitro antimicrobial activity against bacteria and fungi species. The structure-activity relationship of the synthesized compounds was studied. The compounds displayed good to excellent potency against tested microorganisms. The in vitro antioxidant activities of the 1,3,4-oxadiazoles/thiadiazoles were evaluated by DPPH, hydroxyl and nitric oxide radical scavenging assay. Among the tested compounds, compound with chloro substitution showed good antioxidant potential.

A simple, efficient protocol for one pot synthesis of bis(indolyl)methanes from primary alcohols is investigated with N-bromosuccinimde as a catalyst under ultrasound irradiation. Alcohols can be converted into carbonyl compounds by removal of hydrogen in presence of N-bromosuccinimde as an oxidant and can react in situ with indole to give desired bis(indolyl)methanes. In the reported one pot multicomponent condensation reaction N-bromosuccinimde promotes the oxidation of alcohol to aldehyde, facilitating the subsequent condensation with indole to afford bis(indolyl) methanes in good to excellent yields. The inexpensiveness and easy handling are some of important feature of N-bromosuccinimde. The by-product N-succinimide can be easily recovered and recycled to N-bromosuccinimide.

The advent of Industry 4.0 has revolutionized manufacturing, integrating advanced technologies to enhance efficiency and sustainability. However, the transition to sustainable green manufacturing presents numerous challenges. This paper analyzes these challenges using the Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (Fuzzy TOPSIS). By incorporating expert opinions and fuzzy logic, various obstacles are evaluated and prioritized in the implementation of green manufacturing practices in the context of Industry 4.0. The analysis reveals that market uncertainty in the economic landscape ranks as the top challenge, followed by high costs of implementation, maintenance, security, and integration. Uncertain benefits and trade-offs are also found as significant barriers. Key factors include the need for substantial investments, cybersecurity concerns, integration difficulties, and the complexities of predicting returns on investment. From the study, it is also evident that the impact of Industry 4.0 on supply chains and emissions from Electronics manufacturing is also a critical issue. The study provides actionable insights and strategic recommendations for policymakers and industry leaders to facilitate the adoption of sustainable green manufacturing practices in the era of Industry 4.0.

Many entrepreneurs use different ways to offer credit to enhance long term profit as well as relations with their customers. Order-size dependent credit period is one of them that encourage customers to order large lots to grab more credits in payments. Since display of items play positive role in boosting demand, stock dependent demand is assumed in the proposed model. Ordering large lots can create space issue so the proposed model presents a rented warehouse along with owned one. Rented warehouse is used only when owned warehouse is utilized, completely. Here we propose an integrated inventory model with capacity utilization dependent holding cost to optimize joint profit of supplier and retailer. An algorithm is developed to determine the optimal replenishment policies in order to enhance total profit of supply chain under different ordering schemes. Total joint profit for supplier and retailer is optimized using MATLAB 2015. Numerical examples are presented to illustrate the solution procedure and the results. Sensitivity analysis for some key parameters is carried out to demonstrate the influence of different parameters on over-all profit and cycle time. The proposed model is applicable to fast moving consumer goods (FMCG) and home textile industry.