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Technicians' performance is a major driver in maintenance and each process can be prone to time and quality variances as well as errors due to factors such as experience, complexity and environment. Augmented Reality (AR) is an emerging technology that has been applied in a wide variety of disciplines and has been demonstrated to have a role with improving efficiency, effectiveness and decision-making within industrial maintenance. AR has not reached its full potential yet and its implementation in Industry is slowed down by three main limitations: hardware restricted capabilities, object recognition robustness and contents-related issues. This PhD project focuses on easing the implementation of AR by overcoming the AR technology selection challenges and the AR contents-related issues. In order to reach the aim, the student has provided three main contributions to knowledge: 1) a process to select AR technology for maintenance (IPSAR), 2) a method for creating AR step-by-step procedures (FARP) and 3) a method for providing remote assistance (ARRA). FARP and ARRA methods have been developed and tested. The first allows recording procedures in an ad-hoc designed "AR-format" and is able to show "step-by-step" procedures. It aims to support deskilling the maintenance process and reducing the error rate by simplifying the delivery of maintenance with efficient and effective guidance. The second overcomes current remote video-call assistance limitations by improving spatial referencing. ARRA module allows to provide AR-assistance by overlaying virtual objects on the real environment of a remote maintainer. The methods proposed by the student could boost the implementation of AR and open the doors for a bright future in which AR supports technicians thus reducing operational costs and training and improving human performances.