Due to the increased competitiveness and the diversity of requirements in today’s markets, manufacturing companies need to join their competencies and resources to propose innovative solutions for each specific market, with the possibility to transpose these solutions to another market, by means of slight adaptations. Thus, manufacturing firms must constantly conduct new collaborations with known partners in most cases, but also with new partners. The critical question for managers in this latter case is how to define the best collaborative strategy according to the goals of the project and the specificity of the target market. This paper tackles the problem by proposing a conceptual framework for supporting the management of collaborative situations in the case of Original equipment manufacturers (OEMs). Based on the concept of trust level, the framework proposes a classification of different collaboration modes to be adopted in various contexts of inter-enterprise relationships, in manufacturing sector. The aim is to support the flexible navigation between different collaborative situations by taking into account all decision-making levels from the strategy to the implementation of the information technologies (IT) systems at the operational level.

This article showcases the adaptability of existing mobility devices for the Algerian disabled population. It aims to develop a behavior model of disabled Algerian persons through (1) development o...

One of the most recent and popular tourism application is the virtual visits (virtual tour guide) which are based on Augmented/Virtual Reality technology (AR/VR). Such systems suffer from the lack of precise indoor geolocation of visitors within the cultural heritage site. This issue can be resolved by using smartphone (and tablets) embedded sensors, which can catch a huge number of data on visitor behaviour (acceleration, orientation, etc.). This data can be fused using dedicated methods (Extended Kalman Filter (EKF), Particle Filter, etc.) in order to estimate visitor position. However, such algorithms are highly dependent on: sampling time, sensors technologie, number of used sensors, etc. With this kind of solution the error in position estimation growth with the covered distance. In this paper, we present an hybrid solution for reducing error in time without additional infrastructure such Wifi, etc. For this, we present an indoor geolocation solution based on smartphone inertial sensors and earth magnetic field. The proposed method is divided into three phases: heading estimation using 3 sensors (accelerometer, compass and gyroscope) with an Extended Kalman Filter, steps detection and step length estimation, error correction using fingerprinting. The proposed solution is implemented on a smartphone (Samsung-Galaxy S7 based on Android OS) and maintain the error under of 1.5m.