PVD process as a thin film coating method is highly applicable for both metallic and ceramic materials, which is faced with the necessity of choosing the correct parameters to achieve optimal results. In the present study, a GEP-based model for the first time was proposed as a safe and accurate method to predict the adhesion strength and hardness of the Nb PVD coated aimed at growing the mixed oxide nanotubular arrays on Ti67. Here, the training and testing analysis were executed for both adhesion strength and hardness. The optimum parameter combination for the scratch adhesion strength and micro hardness was determined by the maximum mean S/N ratio, which was 350W, 20 sccm, and a DC bias of 90V. Results showed that the values calculated in the training and testing in GEP model were very close to the actual experiments designed by Taguchi. The as-sputtered Nb coating with highest adhesion strength and microhardness was electrochemically anodized at 20V for 4h. From the FESEM images and EDS results of the annealed sample, a thick layer of bone-like apatite was formed on the sample surface after soaking in SBF for 10 days, which can be connected to the development of a highly ordered nanotube arrays. This novel approach provides an outline for the future design of nanostructured coatings for a wide range of applications.
One of the major challenges of the supply chain managers is to select the best suppliers among all possible ones for their business. Although the research on the supplier selection with regards to green, sustainability or resiliency criteria has been contributed by many papers, simultaneous consideration of these criteria in a fuzzy environment is rarely studied. Hence, this study proposes a fuzzy decision framework to investigate the sustainable-resilient supplier selection problem for a real case study of palm oil industry in Malaysia. Firstly, the resilient-based sustainable criteria are localized for the suppliers' performance evaluation in palm oil industry of Malaysia. Accordingly, 30 criteria in three different aspects (i.e. general, sustainable and resilient) are determined by statistical tests. Moreover, a hyper-hybrid model with the use of FDEMATEL (fuzzy decision-making trial and evaluation laboratory), FBWM (fuzzy best worst method), FANP (fuzzy analytical network process) and FIS (fuzzy inference system), simultaneously is developed to employ their merits in an efficient way. In this framework, regarding the outset, the relationships among the criteria/sub-criteria are obtained by FDEMATEL method. Then, initial weights of the criteria/sub-criteria are measured by FBWM method. Next, the final weights of criteria/sub-criteria considering the interrelationships are calculated by FANP. Finally, the performance of the suppliers is evaluated by FIS method. To show the applicability of this hybrid decision-making framework, an industrial case of palm oil in Malaysia is presented. The findings indicate the high performance of the proposed framework in this concept and identify the most important criteria including the cost in general aspects, resource consumption as the most crucial sustainable criterion and agility as the most important resilient criterion.
The recent advances in sustainable supply chain management are integrated with Industry 4.0 concepts. This study develops a new integrated model to consider the sustainability and Industry 4.0 criteria for the supplier selection management. The proposed approach consists of the fuzzy best worst method (FBWM) and the two-stage fuzzy inference system (FIS) to assess the selection of suppliers. Firstly, this study determines a comprehensive list of Industry 4.0 and sustainability criteria along with their definitions. Then, the importance weight of each criterion is computed by the FBWM. Subsequently, a two-stage FIS is devoted to nominate the suppliers' performance with regard to the sustainability and Industry 4.0 criteria. To show the applicability of our integrated model, a case study for a textile company in Iran is provided. Finally, some sensitivity analyses are done to assess the efficiency of the proposed integrated approach. One finding is to establish a decision-making framework to evaluate suppliers separately, rather than relatively in a fuzzy environment using Industry 4.0 and sustainability criteria.