Augmented reality smart glasses (ARSG) are an emerging technology that has the potential to revolutionize how operators interact with information in cyber-physical systems. However, augmented reality is currently not widespread in industrial assembly. The aim of this paper is to investigate and map ARSG in manufacturing from the perspectives of the operator, of manufacturing engineering, and of its technological maturity. This mapping provides an overview of topics relevant to enabling the implementation of ARSG in a manufacturing system, thus facilitating future exploration of the three perspectives. This investigation was done using a meta-analysis of literature reviews of applications of augmented reality in industrial manufacturing. The meta-analysis categorized previously identified topics within augmented reality in industrial manufacturing and mapped those to the scope of the three perspectives.

Augmented Reality (AR) has shown its potential in supporting operators in manufacturing. AR-glasses as a platform both in industrial use are emerging markets, thereby making portable and hands-free AR more and more feasible. An important aspect of integrating AR as a support tool for operators is their acceptance of the technology. This paper presents the results of interviewing operators regarding their view on AR technology in their field and observing them working in automotive engine assembly and how they interact with current instructions. The observations and follow-up questions identified three main aspects of the information that the operators looked at: validating screw torque, their current assembly time, and if something went wrong. The interviews showed that a large amount of the operators were positive towards using AR in assembly. This has given an insight in both the current information interaction the operators do and their view on the potential in using AR. Based on these insights we suggest a mock-up design of an AR-interface for engine assembly to serve as a base for future prototype designs.

This paper presents a novel system using Augmented Reality and Expert Systems to enhance the quality and efficiency of shop-floor operators. The novel system proposed provides an adaptive tool that facilitates and enhances support on the shop-floor, due to its ability to dynamically customize the instructions displayed, dependent upon the competence of the user. A comparative study has been made between an existing method of quality control instructions at a machining line in an automotive engine plant and this novel system. It has been shown that the new approach outcompetes the existing system, not only in terms of perceived usability but also with respect to two other important shop-floor variables: quality and productivity. Along with previous research, the outcomes of these test cases indicate the value of using Augmented Reality technology to enhance shop-floor operators’ ability to learn and master new tasks.

Robots are becoming more adaptive and aware of their surroundings. This has opened up the research area of tight human-robot collaboration,where humans and robots work directly interconnected rather than in separate cells. The manufacturing industry is in constant need ofdeveloping new products. This means that operators are in constant need of learning new ways of manufacturing. If instructions to operatorsand interaction between operators and robots can be virtualized this has the potential of being more modifiable and available to the operators.Augmented Reality has previously shown to be effective in giving operators instructions in assembly, but there are still knowledge gapsregarding evaluation and general design guidelines. This paper has two aims. Firstly it aims to assess if demonstrators can be used to simulatehuman-robot collaboration. Secondly it aims to assess if Augmented Reality-based interfaces can be used to guide test-persons through apreviously unknown assembly procedure. The long-term goal of the demonstrator is to function as a test-module for how to efficiently instructoperators collaborating with a robot. Pilot-tests have shown that Augmented Reality instructions can give enough information for untrainedworkers to perform simple assembly-tasks where parts of the steps are done with direct collaboration with a robot. Misunderstandings of theinstructions from the test-persons led to multiple errors during assembly so future research is needed in how to efficiently design instructions.

Augmented reality smart glasses (ARSG) are increasingly popular and have been identified as a vital technology supporting shop-floor operators in the smart factories of the future. By improving our knowledge of how to efficiently evaluate and select ARSG for the shop-floor context, this paper aims to facilitate and accelerate the adoption of ARSG by the manufacturing industry. The market for ARSG has exploded in recent years, and the large variety of products to select from makes it not only difficult but also time consuming to identify the best alternative. To address this problem, this paper presents an efficient step-by-step process for evaluating ARSG, including concrete guidelines as to what parameters to consider and their recommended minimum values. Using the suggested evaluation process, manufacturing companies can quickly make optimal decisions about what products to implement on their shop floors. The paper demonstrates the evaluation process in practice, presenting a comprehensive review of currently available products along with a recommended best buy. The paper also identifies and discusses topics meriting research attention to ensure that ARSG are successfully implemented on the industrial shop floor.

Customers are becoming more and more individualistic, products are getting more variation and the global market drives for shorter lifecycles for products. The industry is introducing more robots but even though they become more flexible there is still a need for human workers. Fenceless robots and new standards in robotics have made it possible for humans and robots to directly collaborate, allowing them to complement each other with their respective strengths. But how can humans keep up with the increased need for learning new products while collaborating with robots?Studies in using Augmented Reality (AR) show that it might help workers to perform complex operations more efficiently.AR can spatially orient information and thereby present it in context to reality. But AR in actual industrial assembly is still in its infancy, there is a lack of general AR implementations as most AR is done for specific cases and there is still little knowledge about how to generally design AR-based interfaces efficiently.This project aims to explore how AR is most efficiently used in industrial engine assembly. It focuses on cases with Human-Robot Collaboration since the current trend is clear that this will be very common in the future. The goal is to find basic design guidelines for how to best present information to workers; when to present it, what to present and how to present it.Industry representatives will help in creating an evaluation-framework that is relevant for real situations. The guidelines will be iteratively evaluated with this evaluation-framework and designed through the methodology of design science. The goal of this research project is to contribute with a framework for how to evaluate AR-based operator instructions and design guidelines that creates generally more efficient instructions for operators.

Augmented reality is currently a hot research topic within manufacturing and a great potential of the technique is seen. In this study, we aim to increase the knowledge of the adaptation and usability of augmented reality for the training of operators. We propose an approach of using dynamic information content that is automatically adjusted to the individual operator and his/her learning progress for increased efficiency and shorter learning times. The approach make use of the concept of expert systems from the field of artificial intelligence for determine the information content on-line. We develop a framework called "Augmented Reality Expert System" (ARES) that combines AR and expert systems. A proof-of-concept evaluation of the framework is presented in the paper and possible future extensions are discussed.

With augmented reality, virtual information can be overlaid on the real world in order to enhance a human’s perception of reality. In this study, we aim to deepen the knowledge of augmented reality in the shop-floor context and analyze its role within smart factories of the future. The study evaluates a number of approaches for realizing augmented reality and discusses advantages and disadvantages of different solutions from a shop-floor operator’s perspective. The evaluation is done in collaboration with industrial companies, including Volvo Cars and Volvo GTO amongst others. The study also identifies important future research directions for utilizing the full potential of the technology and successfully implement it on industrial shop-floors.

This paper describes a study of using the concept of augmented reality for supporting assembly line workers in carrying out their task optimally. By overlaying virtual information on real world objects – and thereby enhance the human’s perception of reality – augmented reality makes it possible to improve the visual guidance to the workers.  In the study, a prototype system is developed based on the Oculus Rift platform and evaluated using a simulated assembling task. The main aim is to investigate user acceptance and how this can possible be improved.