Augmented reality (AR) is a novel human–machine interaction that overlays virtual computer-generated information on a real world environment. It has found good potential applications in many fields, such as military training, surgery, entertainment, maintenance, assembly, product design and other manufacturing operations in the last ten years. This paper provides a comprehensive survey of developed and demonstrated AR applications in manufacturing activities. The intention of this survey is to provide researchers, students, and engineers, who use or plan to use AR as a tool in manufacturing research, a useful insight on the state-of-the-art AR applications and developments.

For a CAPP system in a dynamic workshop environment, the activities of selecting machining resources, determining set-up plans and sequencing machining operations should be considered simultaneously to achieve the global lowest machining cost. Optimizing process plans for a prismatic part usually suffer from complex technological requirements and geometric relationships between features in the part. Here, process planning is modelled as a combinatorial optimization problem with constraints, and a hybrid genetic algorithm (GA) and simulated annealing (SA) approach has been developed to solve it. The evaluation criterion of machining cost comes from the combined strengths of machine costs, cutting tool costs, machine changes, tool changes and set-ups. The GA is carried out in the first stage to generate some initially good process plans. Based on a few selective plans with Hamming distances between each other, the SA algorithm is employed to search for alternative optimal or near-optimal process plans. In the GA and SA algorithms, some preliminarily defined precedence constraints between features and operations are manipulated. A case study and the comparisons with the single GA and SA approaches show that this hybrid approach can achieve highly satisfactory results.