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The low resistance against penetration of water, oxygen and the other corrosive ions through the paths of coating is one the most important problems. So, protective properties of coating such as polyester must be promoted. Recently, the use of nanoparticles in the matrix of polymer coating to increase their protection and mechanical properties has been prospering greatly. The purpose of this study is to improve the corrosion resistance of the polyester powder coating with ZnO nanoparticles. The ZnO nanoparticles have been synthesized by hydrothermal method in a microwave. Using polyester – ZnO nanocomposite coating as powder – combining them by ball milling process and coating them by electrostatic process are innovative ideas and have not been used before it.

Polyester powder as the matrix and ZnO nanoparticles as reinforcing were combined in three different weight percentage (0.5, 1, 2 Wt.%), and they formed polymer nanocomposite by ball milling process. Then, the fabricated nanocomposite powder was applied to the surface of carbon steel using an electrostatic device, and then the coatings were cured in the furnace. The morphology of synthesized zinc oxide nanoparticles was investigated by transmission electron microscope. Also, the morphology of polyester powder and fabricated coatings was studied by scanning electron microscope. The effects of zinc oxide nanoparticles on the corrosion resistance of coated samples were studied by electrochemical impedance spectroscopy (EIS) test at various times (1-90 days) of immersion in 3.5 per cent NaCl electrolyte.

Scanning electron microscopy (SEM) results reveal that there are no obvious crack and defects in the nanocomposite coatings. In contrast, the pure polyester coatings having many cracks and pores in their structure. According to the EIS results, the corrosion resistance of nanocomposite coating compared to pure coating is higher. The value obtained from EIS test show that corrosion resistance for coating that contains 1 Wt.% nanoparticle was 32,150,000 (Ωcm²), which was six times bigger than that of pure coating. In addition to providing a barrier against diffusion of electrolyte, ZnO nanoparticles act as a corrosion inhibitor and, thus, increases the corrosion resistance. The corrosion resistance of coating containing 0.5 Wt.% nanoparticles was lower as compared to that of 1 Wt.% nanoparticles. The low content of nanoparticles caused partial covering of the porosity of coating which in turn leads to provide weaker barrier properties. The increase in quantity of nanoparticles from 1 to 2 Wt.% also caused a decrease in corrosion resistance which is attributed to the agglomeration of nanoparticles.

The results of this study indicated the significant effect of ZnO nanoparticles on the protective performance and corrosion resistance of the polyester powder coating. Evaluation of coating surface and interface with SEM technique revealed that nanocomposite coating compared with pure polyester coating provided a coating with lower number of pores and with higher quality. The EIS measurements represented that polymeric coating that contains nanoparticles compared to pure coating provides a better corrosion resistance. In addition to providing a barrier against diffusion of electrolyte, ZnO nanoparticles act as a corrosion inhibitor and thus increase the corrosion resistance. The corrosion resistance of coating containing 0.5 Wt.% nanoparticles was lower as compared to that containing 1Wt.% nanoparticles. The low content of nanoparticles caused partial covering of the porosity of coating which in turn leads to provide weaker barrier properties. The increase in quantity of nanoparticles from 1 to 2 Wt.% also caused a decrease in corrosion resistance which is attributed to the agglomeration of nanoparticles.

The purpose of this paper is to develop a fuzzy analytic network process (FANP) model to select the maintenance policy of an acid manufacturing company.

Four maintenance strategies of Corrective Maintenance (CM), Time-Based Maintenance (TBM), Condition-Based Maintenance (CBM) and Shutdown Maintenance (SM) are investigated to be considered for seven equipment of the case study. These equipment are almost new and include boiler, molten sulfur ponds, cooling towers, absorption tower, converter, sulfur fuel furnace and heat exchanger. Chang’s extended analysis has been employed to deal with fuzzy data and analyze the fuzzy decision matrices. The proposed approach is applied to a sulfuric acid production plant and the suitable maintenance policy is found for all seven equipment of the company.

Based on the obtained results, the CBM policy is appropriate for high-risk (cooling tower) and high added value equipment (absorption tower). In addition, TBM is selected for boiler and converters while SM is selected for molten sulfur ponds. Finally, high-cost, low-risk and low added value equipment (sulfur fuel furnace and heat exchanger) are more appropriate with CM policy.

This research presents a novel idea to consider cost, risk and added value in the context of maintenance policy selection. From the methodological and theoretical features, this research offers new insights in this area since, to the best of the authors’ knowledge, no comparable study has been conducted before.

This paper aims to simulate the nanofluid forced convection in a microchannel. According to the results, at high Reynolds numbers and higher nanofluid volume fractions, an increase in the rib height and slip coefficient further improved the heat transfer rate. The ribs also affect the flow physics depending on the Reynolds number so that the slip velocity decreases with increasing the nanofluid volume fraction and rib height.

Forced heat transfer of the water–copper nanofluid is numerically studied in a two dimensional microchannel. The effects of the slip coefficient, Reynolds number, nanofluid volume fraction and rib height are investigated on the average Nusselt number, slip velocity on the microchannel wall and the performance evaluation criterion.

In contrast, the slip velocity increases with increasing the Reynolds number and slip coefficient. Afterwards, a non-parametric function estimation is performed relying on the artificial neural network.

Finally, the Genetic Algorithm was used to establish a set of optimal decision parameters for the problem

In today's competitive industries, the selection of best suitable maintenance strategy is dependent on large number of quantitative and qualitative factors, and it becomes an extensively difficult problem for maintenance engineers. Over the years, a diverse range of solution methodologies have been developed for solving this multi-criteria decision-making (MCDM) problem. In this paper, the authors have presented a comprehensive review of latest maintenance strategy paradigms and solution approaches proposed for the selection of an appropriate strategy in various industries. It would provide a systematic mapping of developments in this field and identify some research gaps to explore further studies.

A systematic state-of-the-art comprehensive literature review on maintenance strategy paradigms and selection approaches is presented in this study. In this study, 87 research articles published in peer-reviewed journals, since year 2012, are reviewed.

For the selection of a suitable maintenance strategy, a variety of criteria are considered to better evaluate the alternatives. In this study, contemporary strategies are discussed, and their applications in different industries are also depicted. Moreover, through the analysis of extant literature, critical criteria are selected and classified in six major categories (namely, economic, technical, safety, environmental, feasibility and social) and further sub-categorized in quantitative and qualitative classes. These clusters of criteria can be helpful as an initial set of criteria for survey and then case- or industry-specific criteria can be shortlisted for further alternative evaluation.

From the perspective of maintenance managers, maintenance management can be a very difficult task, considering the numerous factors affecting the decision-making process. In order to help in the decision-making process, this study presents the contemporary maintenance strategies in a systematic manner. In a previous study (Kothamasu et al., 2006), these strategies were classified into repair and prevent classes only. With the developments of autonomous maintenance and design out maintenance (DOM), it was fair to include continuous improvement class. It will help managers and practitioners to identify, according to organization policy, appropriate maintenance strategy alternatives for the asset. A benchmark set of state-of-the-art maintenance strategies are laid out with their applications. The industrial case studies discussed in this study summarizes the optimal maintenance strategies for respective industries. Also, most critical criteria are identified from the existing studies for various industries that can help maintenance practitioners in acknowledging the critical factors and making appropriate decisions. Evaluation parameters for the maintenance strategy selection (MSS) generally conflict with each other, and considering the difficulty of quantifying the qualitative measures, it is a challenging task to determine the optimal trade-off. In order to overcome these challenges, popular MCDM approaches, demonstrating effective results across different industries are discussed with their limitations and applications. Decision-makers can refer this study to identify best suitable decision-making technique for the MSS problem in the industry of their choice. Maintenance managers and engineers can refer the case studies illustrated in Tables 1 and 2 to analyse the MSS techniques proposed by previous studies with industry-specific applications.

This study is an attempt to provide a reference point for research scholars interested in the field of maintenance management and/or development of maintenance strategy framework. This study provides a critical state-of-the-art review of efforts made in the field of MSS. The prominent maintenance strategies being implemented in contemporary industries are discussed with respective case studies. Interested researchers and academicians can familiarize themselves with these strategies and their distinct features in this study. In order to guide future studies and provide a reference point for academicians, MSS critical criteria used in extant literature are identified and classified into a comprehensive benchmark framework. Moreover, the industrial case studies are discussed with the most critical criteria of MSS for different industries and which strategy is most suitable for the respective industries based on these criteria. Table 1 presents different MCDM techniques and their hybrid applications for solving MSS problem that can help researchers in identifying research gaps. Future research can be directed at addressing the limitation of MCDM approach employed in existing studies and comparing the differences in results obtained by the proposed approach. Different industrial case studies with considered maintenance strategy alternatives are presented in Table 2, which can help researchers in identifying the industries that have not been studied yet. Moreover, not all of the existing studies are carried out by considering all the presented benchmark strategies, which can be addressed in future studies by interested researchers. More detailed discussion on research gaps is presented in the following section.

From the analysis of the extant literature, the authors could observe that the decision-making process adopted in numerous studies was limited to the classical maintenance strategies and not inclusive of aggressive maintenance strategy alternatives. To overcome these limitations and help maintenance managers in the decision-making, this study depicts the contemporary maintenance strategies, critical evaluation criteria and MCDM frameworks (employed to solve the MSS problem with industrial case studies) in a structured manner.