Management towards control of risk issues appeared as an important area in E-supply chain for researchers in the present fast growing market. Extensive research has been accomplished in this area, but still there are several risks and uncertainties. The present research aims to identify and consolidate various e-supply risk factors for developing a constructive measurement model. The study also assesses the influence of risk factors over e-supply chain operation in Indian mechanical industries. Thus, after a thorough research and detailed discussion, 38 Risks factors are identified through literature to prepare the questionnaire. A questionnaire based survey is carried out for collecting the primary data from 148 experts of mechanical manufacturing industries located in the national capital region of India. The research methodology is combined with descriptive statistics and factor analysis. SPSS 21 software tools is used for investigating the reliability and Amos Graphics 21 software is used for the fitment validation of the theoretical construct. The results suggest that all risk issues create significant negative influence e-supply chain process. The results also show negative effects of risks over e-supply chain performance. The current research outcome develops a stochastic model based on the e-supply chain risk factors used for reducing risks in e-supply chain operation.

In the present work, a recently developed advanced optimization algorithm named as teaching–learning-based optimization (TLBO) is used for the parameters optimization of fabric finishing system of a textile industry. Fabric Finishing System has four main subsystems, arranged in hybrid configuration. For performance modeling and analysis of availability, a performance evaluating model of fabric finishing system has been developed with the help of mathematical formulation based on Markov-Birth-Death process using Probabilistic Approach. Then, the overall performance of the concerned system has first analyzed and then, optimized by using teaching–learning-based optimization (TLBO). The results of optimization using the proposed algorithm are validated by comparing with those obtained by using the genetic algorithm (GA) on the same system. Improvement in the results is obtained by the proposed algorithm. The results of effect of variation of the algorithm parameters on fitness values of the objective function are reported.

In the present scenario, the Six Sigma tools and techniques are used by various manufacturing industries, exporting industries and even service organizations. It focuses on improving the quality of the products, cutting down the extra costs, reducing the variations and satisfying the customers. This case study follows the Six Sigma tools called DMAIC methodology to identify and analyze various root causes of the capacitors rejection problems, which influence the performance of the company and suggests solutions to counter with it. The issue not only causes financial loss to the company but also hinders future growth in form of customer dissatisfaction. The results of the implementation indicate significant improvement in the quality of the product and cost reduction.

The purpose of this study is to identify the types of halal food supply risks, types of mitigation strategies for the upstream supply chain and to examine the relationship between halal supply risk and mitigation strategy efforts using the lens of the agency theory. Exploratory factor analysis (EFA) is used to validate the variables of the study and regression is performed to analyze the relationship of halal food supply risk and mitigation strategy. It is identified that halal food supply risk (agency uncertainties) consists of quality risk, delivery risk, and price/cost risk. The mitigation strategy efforts consist of behavior-based management, buffer-based management, and traceability-based management. Results indicate that halal food supply risk significantly increase mitigation strategy efforts of firms. However, price & cost risk does not significantly increase behavior-based management. Practical implications include suggesting the firms to invest more in buffer-oriented so as to mitigate the agency uncertainties.

A series of novel 10-phenylsulfonyl-2-substituted-4,10 dihydrobenzo[4,5]imidazo[1,2-a]pyrimidin-4-one derivatives obtained from N-sulfonation of 2-substituted-pyrimido[1,2-a]benzimidazol-4(10H)-ones and screened for for their in vitro anti-tuberculosis activities against Mycobacterium tuberculosis H37Rv by Microplate Alamar Blue Assay (MABA) method. The structures were established on the basis of their IR, ¹H-NMR, ¹³C-NMR, ESI-MS data and also the compound with 3f were crystallized and analysed by single crystal X-ray diffraction studies.

Two heterocyclic Schiff bases namely (E)-2-(1-(2-phenylhydrazono)ethyl)pyridine (or 2-acetyl pyridine phenyl hydrazone) (2APPH) and (E)-2-(1-triazylidineethyl)pyridine (or 2-acetyl pyridine semicarbazone) (2APSC) were synthesized, characterized and their corrosion inhibition behaviour as well as mechanism of inhibition were investigated by different techniques. Structural characterization includes NMR, Mass, IR and UV-visible spectroscopy and elemental analysis. Corrosion inhibition behaviour of aforesaid compounds on mild steel in 1M hydrochloric acid was examined by electrochemical methods including potentiodynamic polarization analysis and electrochemical impedance spectroscopic techniques. The mechanism of corrosion inhibition was explored and supplemented by adsorption and surface morphological studies. Quantum mechanical investigations on corrosion behaviour of compounds were also conducted and satisfying correlation was noticed between the results of corrosion measurement methods and quantum mechanical evaluations.

Indolylimidazole compounds that contain both indole and imidazole rings have shown various biological and pharmacological activities. These indolylimidazole compounds have been synthesized and extracted from the plants. In this paper, we have reviewed biological activities of natural and synthesized indolylimidazoles and their various synthetic methods. In recent time, the substituted indolylimidazole derivatives have synthesized and reported in the presence of different kind of the catalysts such as strong protic acid HNO₃@nano SiO₂, Zn²⁺@KSF and acetic acid and Amberlyst A-15. This review paper is divided into two categories bases on bioactivities of natural and synthesized indolylimidazole derivatives.

The usage of Artificial Intelligence (AI) technique under retail industry will bring glorious outcome and flourishing benefits for both the retailers and the distinguished customers. The multiple platforms of AI usage in retail arena are discussed under two different cluster classified as online and offline, based on the terms of execution of retail activity. The present research was conducted with the objectives of evaluating the contribution of quality, customer relationship management and big data in designing futuristic retail model and analyzing the intention of retailers and shoppers in experiencing the emergence of AI. Disproportionate multistage judgement sampling method was em-ployed. A sample of 610 shoppers from four different capital regions of southern part of states in India was considered for the statistical analysis. Data was collected during the first quarter period of 2018. Descriptive research design was used to describe the intention of shoppers towards the emer-gence of AI in the Indian retail sector. The usages of AI technologies in online and offline retail are grouped separately and its effect on building the quality, customer relationship management and big data was evolved. Finally, its impact on the retailers intention and customers delight was studied through Structural Equation Modeling with testing of appropriate hypothesis.

This paper aims a novel and a useful multi-objective optimization approach named Non-Dominated Sorting Ions Motion Algorithm (NSIMO) built on the search procedure of Ions Motion Algorithm (IMO). NSIMO uses selective crowding distance and non-dominated sorting method to obtain various non-domination levels and preserve diversity amongst the best set of solutions. The suggested technique is employed to various multi-objective benchmark functions having different characteristics like convex, concave, multimodal, and discontinuous Pareto fronts. The recommended method is analyzed on different engineering problems having distinct features. The results of the proposed approach are compared with other well-regarded and novel algorithms. Furthermore, we present that the projected method is easy to implement, capable of producing a nearly true Pareto front and algorithmically inexpensive.

The present work deals with some machinability studies on tool wear and surface roughness, in finish hard turning of AISI D2 steel using PCBN, Mixed ceramic and coated carbide inserts. The machining experiments are conducted based on the response surface methodology (RSM). Combined effects of three cutting parameters viz., cutting speed, cutting time and tool hardness on the two performance outputs (i.e. VB and Ra), are explored employing the analysis of variance (ANOVA).The relationship(s) between input variables and the response parameters are determined using a quadratic regression model. The results show that the tool wear was influenced principally by the cutting time and in the second level by the cutting tool hardness. On the other hand, cutting time was the dominant factor affecting workpiece surface roughness followed by cutting speed. Finally, the multiple response optimizations of tool wear and surface roughness were carried out using the desirability function approach (DFA).