Currently, Engineer-To-Order manufacturing companies are under high pressure from global competition and turbulent market excitations, resulting in increasing product variety, individualisation and shortened time frames. Additionally, manufacturing companies are faced with the increasing complexity of products, production structures and processes. It is obvious that manufacturing companies with ... [Show full abstract] structural rigidity, a deterministic approach to decision-making in a stochastic environment, hierarchical allocation of competencies and insufficient communication and exploitation of expertise cannot achieve these requirements at an appropriate level. This paper presents the conceptual framework for a ubiquitous autonomous work system in the Engineer-To-Order environment by applying ubiquitous computing technology and cloud computing to the manufacturing system. This approach aims to improve the performance of manufacturing systems by increasing their productivity, availability, responsiveness and agility as well as support to decision-making and real-time operations management. This paper is structured in two sections. The first section presents the derivation procedure for the u-AWS framework in the project-oriented Engineer-To-Order manufacturing. The second section describes a case study based on online diagnostics and prognostics for asset conditions. This study is conducted in a workshop of a manufacturing system in an Engineer-To-Order company to provide a demonstration of the concepts.