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The explicit finite element method (FEM) is one of the most popular approaches in quasi-static contact analysis which involves highly nonlinear friction and large deformation. Usually, a high loading rate is expected to improve computation efficiency in FEM. However, a higher loading rate often results in significant dynamic effects in the simulations. This study aims to propose a new criterion to achieve a good balance between a high loading rate and minimal dynamic effects.

The proposed criterion is based on the fluctuation of total strain energy as well as the smoothness of its first derivative to determine the proper loading time with an acceptable level of dynamic effect.

Asperities’ sliding contact and Hertz contact problems have been solved with the proposed criterion to verify its validity. The simulations show that the computation efficiency with the proposed criterion can be improved by up to 80 per cent compared to the regular energy ratio criterion.

This criterion will provide a valuable tool in determining the proper loading time to improve the computation efficiency for quasi-static analysis of asperities’ contacts.

Expert systems are computer-based systems that mimic the logical processes of human experts or organizations to give advice in a specific domain of knowledge. Fuzzy expert systems use fuzzy logic to handle uncertainties generated by imprecise, incomplete and/or vague information. The purpose of this paper is to present a comprehensive review of the methods and applications in fuzzy expert systems.

The authors have carefully reviewed 281 journal publications and 149 conference proceedings published over the past 37 years since 1982. The authors grouped the journal publications and conference proceedings separately accordingly to the methods, application domains, tools and inference systems.

The authors have synthesized the findings and proposed useful suggestions for future research directions. The authors show that the most common use of fuzzy expert systems is in the medical field.

Fuzzy logic can be used to manage uncertainty in expert systems and solve problems that cannot be solved effectively with conventional methods. In this study, the authors present a comprehensive review of the methods and applications in fuzzy expert systems which could be useful for practicing managers developing expert systems under uncertainty.