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This paper aims to solve the nonlinear problem in the uncertainty evaluation of the measurement of the positioning repeatability (RP) of industrial robots and provide guidance to restrict the uncertainty of measurement of RP (u_RP).

Firstly, some uncertain sources existing in the measurement procedure of RP are identified. Secondly, the probability distribution function (PDF) of every source is established on the basis of its measurements. Some spatial combined normal distributions are adopted. Then, a method, based on Monte Carlo method (MCM) and established measurement model, is developed for the estimation of u_RP. Thirdly, some tests are developed for the identification and validation of the selected PDFs of uncertain sources. Afterwards, the proposed method is applied for the evaluation and validation of the u_RP. Finally, influence analyses of some key factors are proposed for the quantification of their relative contributions to u_RP.

Results show that the proposed method can reasonably and objectively estimate the u_RP of the selected industrial robot, and changes of the industrial robots’ position and the laser trackers measurement are correlated. Additionally, the u_RP of the selected industrial robot can be restricted by using the results of its key factors on u_RP.

This paper proposes the spatial combined normal distribution to model the uncertainty of the repeatability of the laser tracker and industrial robot. Meanwhile, the proposed method and influence analyses can be used in estimating and restricting the u_RP and thus useful in determining whether the RP of a tested industrial robot meets its requirements.

In the past four decades, substantial air traffic growth has triggered enthusiasm in the aviation sector. At the same time, this growth has posed challenges to its financial and environmental sustainability commitments. A buzz has been centered on introducing and supporting aviation sustainability initiatives. These challenges have led to acknowledging the need to reduce aviation fuel consumption, a function of multiple factors. The different stakeholders having a diverse type of interplay govern the effective implementation of the factors at different decision levels (strategic, tactical and operational). Thus, the present study aims to critically examine various decision levels involved to understand opportunities and requirements related to aviation sustainability.

In this study, the best–worst method is used to quantify different decision levels’ role on various factors affecting aviation fuel consumption.

The results of this study signify that tactical-level decisions are most influential in reducing aviation fuel consumption with the highest impact (0.41) followed by operational-level decisions (0.30) and strategic-level decisions (0.29), respectively.

The results point toward the critical role of middle-level hierarchy, i.e. aircraft manufacturers, airlines and others in the aviation industry’s sustainable growth. Thus, middle-level stakeholders must be inspired and empowered to act, being at the center they link the other two levels.

This study has added to the body of knowledge by exploring the decision-making competencies needed by different aviation sector stakeholders. It also presents the possible options available in the sector and the role of stakeholders at different levels in exploiting and implementing the sustainable aviation sector changes.