User-Oriented Augmented Reality Content Delivery and Management for Ubiquitous Manufacturing

Ubiquitous manufacturing provides users with advanced control over the physical manufacturing environment. Ubiquitous augmented reality (UAR) interface enables direct manipulation in an environment containing smart objects. This paper describes a framework for implementing augmented reality (AR) in a ubiquitous manufacturing environment. The proposed system makes use of real-time data captured from client machines to update and manage AR contents. Ubiquitous augmented reality is utilized as a user interface for the client users to receive instructions and guidance from the system and to update the system on task parameters. A review of related work, and the framework, methodology, and implementation of the proposed system, and a case study are presented in this paper to demonstrate the UAR content delivery and update.

Fuzzy approach for production planning by using a three-dimensional printing-based ubiquitous manufacturing system

A ubiquitous manufacturing (UM) system is used in manufacturing for obtaining the Internet of things solutions and provides location-based manufacturing services. Human-induced uncertainty and early termination are two complications that hamper the effectiveness of an UM system based on three-dimensional (3D) printing. To resolve these complications, several solutions were considered in this study. First, fuzzy-valued parameters were defined to determine uncertainty. Subsequently, slack was derived to determine whether to restart an early terminated 3D printing process in the same 3D printing facility. Consequently, two optimization models – a fuzzy mixed-integer linear programming model and a fuzzy mixed-integer quadratic programming model – were developed in this study. Based on the two optimization models, a fuzzy 3D printing-based UM system that considers uncertainty and early termination was developed. The effectiveness of the proposed methodology was tested by conducting a regional experiment. The experimental results revealed that the proposed methodology could shorten the average cycle time by 9% and could enable 3D printing facilities to make real-time, online reprinting decisions.