Human-automation collaboration in manufacturing: identifying key implementation factors

Human-automation collaboration refers to the concept of human operators and intelligent automation working together interactively within the same workspace without conventional physical separation. This concept has commanded significant attention in manufacturing because of the potential applications, such as the installation of large sub-assemblies. However, the key human factors relevant to human-automation collaboration have not yet been fully investigated. To maximise effective implementation and reduce development costs for future projects these factors need to be examined. In this paper, a collection of human factors likely to influence human-automation collaboration are identified from current literature. To test the validity of these and explore further factors associated with implementation success, different types of production processes in terms of stage of maturity are being explored via industrial case studies from the project’s stakeholders. Data was collected through a series of semi-structured interviews with shop floor operators, engineers, system designers and management personnel

Ergonomics and human factors as a requirement to implement safer collaborative robotic workstations: a literature review

There is a worldwide interest in implementing collaborative robots (Cobots) to reduce work-related Musculoskeletal Disorders (WMSD) risk. While prior work in this field has recognized the importance of considering Ergonomics & Human Factors (E&HF) in the design phase, most works tend to highlight workstations’ improvements due to Human-Robot Collaboration (HRC). Based on a literature review, the current study summarises studies where E&HF was considered a requirement rather than an output. In this article, the authors are interested in understanding the existing studies focused on Cobots’ implementation with ergonomic requirements, and the methods applied to design safer collaborative workstations. This review was performed in four prominent publications databases: Scopus, Web of Science, Pubmed, and Google Scholar, searching for the keywords ‘Collaborative robots’ or ‘Cobots’ or ‘HRC’ and ‘Ergonomics’ or ‘Human factors’. Based on the inclusion criterion, 20 articles were reviewed, and the main conclusions of each are provided. Additionally, the focus was given to the segmentation between studies considering E&HF during the design phase of HRC systems and studies applying E&HF in real-time on HRC systems. The results demonstrate the novelty of this topic, especially of the real-time applications of ergonomics as a requirement. Globally, the results of the reviewed studies showed the potential of E&HF requirements integrated into HRC systems as a relevant input for reducing WMSD risk.This work has been supported by FCT–Fundação para a Ciência e Tecnologia and MIT Portugal Program under the doctoral Grant SFRH/BD/151365/2021. This work has been also supported by NORTE-06-3559-FSE-000018, integrated in the invitation NORTE-59-2018-41, aiming the Hiring of Highly Qualified Human Resources, co-financed by the Regional Operational Programme of the North 2020, thematic area of Competitiveness and Employment, through the European Social Fund. Additionally, has been also supported by FCT within the Project “I-CATER–Intelligent robotic Coworker Assistant for industrial Tasks with an Ergonomics Rationale”, Ref. PTDC/EEIROB/3488/2021, and within R&D Units Project Scope: UIDB/00319/2020

Human centric collaborative workplace: the human robot interaction system perspective

The implementation of smart technologies and physical collaboration with robots in manufacturing can provide competitive advantages in production, performance and quality, as well as improve working conditions for operators. Due to the rapid advancement of smart technologies and robot capabilities, operators face complex task processes, decline in competences due to robots overtaking tasks, and reduced learning opportunities, as the range of tasks that they are asked to perform is narrower. The Industry 5.0 framework introduced, among others, the human-centric workplace, promoting operators wellbeing and use of smart technologies and robots to support them. This new human centric framework enables operators to learn new skills and improve their competencies. However, the need to understand the effects of the workplace changes remain, especially in the case of human robot collaboration, due to the dynamic nature of human robot interaction. A literature review was performed, initially, to map the effects of workplace changes on operators and their capabilities. Operators need to perform tasks in a complex environment in collaboration with robots, receive information from sensors or other means (e.g. through augmented reality glasses) and decide whether to act upon them. Meanwhile, operators need to maintain their productivity and performance. This affects cognitive load and fatigue, which increases safety risks and probability of human-system error. A model for error probability was formulated and tested in collaborative scenarios, which regards the operators as natural systems in the workplace environment, taking into account their condition based on four macro states; behavioural, mental, physical and psychosocial. A scoping review was then performed to investigate the robot design features effects on operators in the human robot interaction system. Here, the outcomes of robot design features effects on operators were mapped and potential guidelines for design purposes were identified. The results of the scoping review showed that, apart from cognitive load, operators perception on robots reliability and their safety, along with comfort can influence team cohesion and quality in the human robot interaction system. From the findings of the reviews, an experimental study was designed with the support of the industrial partner. The main hypothesis was that cognitive load, due to collaboration, is correlated with quality of product, process and human work. In this experimental study, participants had to perform two tasks; a collaborative assembly and a secondary manual assembly. Perceived task complexity and cognitive load were measured through questionnaires, and quality was measured through errors participants made during the experiment. Evaluation results showed that while collaboration had positive influence in performing the tasks, cognitive load increased and the temporal factor was the main reason behind the issues participants faced, as it slowed task management and decision making of participants. Potential solutions were identified that can be applied to industrial settings, such as involving participants/operators in the task and workplace design phase, sufficient training with their robot co-worker to learn the task procedures and implement direct communication methods between operator and robot for efficient collaboration

Comfort, Acceptance, and Preferences: The Designing of a Human-Robot Workstation that Puts the Human First

The purely manual versions of manufacturing are becoming less common, and automation is increasing. With mass production moving towards mass customization this change is inevitable. However, a future of automation does not mean that operators are going to be replaced. In fact, it means that operators’ jobs are about to become more meaningful and value adding for themselves and the company. Soon majority of the jobs where operators do the repetitive mindless task of a robot will be gone. It is time for Human-Robot Collaboration (HRC) to advance the assembly process to the next level. Human-robot teams will be formed to combine their individual strengths and compensate for their individual weaknesses. The success of human-robot collaboration heavily depends on the operator’s acceptance of the robot. Unfortunately, operators are worried about robots taking their jobs, diminishing their self-worth, and putting them in danger. To mitigate these concerns the objective of this thesis is to model the design requirements of a human-robot collaborative assembly station that appeals to operator comfort and acceptance while still supporting the needs of production. A combination of fulfilling requirements, providing the operator with a better understanding of the robot’s capabilities, and providing the operator with limited control could lead to an improved interaction between operators and robots. Operator feedback was obtained from professionals in industry through surveys and structured interviews. Then the Quality Function Deployment (QFD) tool was used to translate the vague operator requirements captured in the survey responses and interviews into product-relevant parameters that designers and engineers can apply. The nine operator requirements derived for working with robots are safety, dependability, value-adding, controllability, helpfulness, easy to communicate with, teachable, easy to fix, and enjoyable to work with

Safety Assessment Strategy for Collaborative Robot Installations

Industrial resource efficiency can be improved if the safety barrier between humans and robots is removed, as this enables operators and robots to work side by side or in direct collaboration to solve a task, usually referred to as a collaborative robot installation. Even though technology development makes the barrier removal ever more feasible from a safety perspective, this still produces a possible hazardous working environment, and safety assessment strategies are crucial. A wide area of knowledge is required to assess all fields that can help ensure safe human-machine interaction. Here the focus is primarily on providing a description of the key fields identified, including how operators psychologically accept working with robots, and providing a cursory description of the research front for each individual field. In addition to covering a large number of parameters, the assessment strategy also needs to be cost-effective. A significant part of all parameters that can be considered when attempting to produce optimized and cost-effective collaborative robot installations will also have a direct impact on operator safety. Hence, assessments for safety, and assessments for cost-effectiveness, cannot be separated, and are treated as two objectives that need to be viewed in sync

Smart operators: How Industry 4.0 is affecting the worker's performance in manufacturing contexts

Abstract The fourth industrial revolution is affecting the workforce at strategical, tactical, and operational levels and it is leading to the development of new careers with precise and specific skills and competence. The implementation of enabling technologies in the industrial context involves new types of interactions between operators and machines, interactions that transform the industrial workforce and have significant implications for the nature of the work. The incoming generation of Smart Operators 4.0 is characterised by intelligent and qualified operators who perform the work with the support of machines, interact with collaborative robots and advanced systems, use technologies such as wearable devices and augmented and virtual reality. The correct interaction between the workforce and the various enabling technologies of the 4.0 paradigm represents a crucial aspect of the success of the smart factory. However, this interaction is affected by the variability of human behaviour and its reliability, which can strongly influence the quality, safety, and productivity standards. For this reason, this paper aims to provide a clear and complete analysis of the different types of smart operators and the impact of 4.0 enabling technologies on the performance of operators, evaluating the stakeholders involved, the type of interaction, the changes required for operators in terms of added and removed work, and the new performance achieved by workers

Comparing quality profiles in Human-Robot Collaboration: empirical evidence in the automotive sector

Purpose: Human-Robot Collaboration (HRC) is a paradigm that is gradually consolidating in the industrial field. The goal of this paradigm is to combine human and robot skills to make production more flexible. An effective implementation of HRC requires a careful analysis of its different aspects, related to both robots and humans. For this reason, the development of a tool able to consider all HRC aspects to evaluate the collaboration quality is a real practical need. Design/methodology/approach: In a previous work, Gervasi et al. (2020) proposed a multidimensional framework to evaluate HRC quality. This framework has been tested on a real industrial HRC application in the automotive sector. Two different alternatives of the same assembly task were analyzed and compared on the quality reference framework. Findings: The comparison between the two alternatives of the same assembly task highlighted the framework's ability to detect the effects of different configurations on the various HRC dimensions. This ability can be useful in decision making processes and in improving the collaboration quality. Social implications: The framework considers the human aspects related to the interaction with robots, allowing to effectively monitor and improve the collaboration quality and operator satisfaction. Originality/value: This paper extends and shows the use of the HRC evaluation framework proposed by Gervasi et al. (2020) on real industrial applications. In addition, an HRC application implemented in an important automotive company is described and analyzed in detail

The development of a human-robot interface for industrial collaborative system

Industrial robots have been identified as one of the most effective solutions for optimising output and quality within many industries. However, there are a number of manufacturing applications involving complex tasks and inconstant components which prohibit the use of fully automated solutions in the foreseeable future. A breakthrough in robotic technologies and changes in safety legislations have supported the creation of robots that coexist and assist humans in industrial applications. It has been broadly recognised that human-robot collaborative systems would be a realistic solution as an advanced production system with wide range of applications and high economic impact. This type of system can utilise the best of both worlds, where the robot can perform simple tasks that require high repeatability while the human performs tasks that require judgement and dexterity of the human hands. Robots in such system will operate as “intelligent assistants”. In a collaborative working environment, robot and human share the same working area, and interact with each other. This level of interface will require effective ways of communication and collaboration to avoid unwanted conflicts. This project aims to create a user interface for industrial collaborative robot system through integration of current robotic technologies. The robotic system is designed for seamless collaboration with a human in close proximity. The system is capable to communicate with the human via the exchange of gestures, as well as visual signal which operators can observe and comprehend at a glance. The main objective of this PhD is to develop a Human-Robot Interface (HRI) for communication with an industrial collaborative robot during collaboration in proximity. The system is developed in conjunction with a small scale collaborative robot system which has been integrated using off-the-shelf components. The system should be capable of receiving input from the human user via an intuitive method as well as indicating its status to the user ii effectively. The HRI will be developed using a combination of hardware integrations and software developments. The software and the control framework were developed in a way that is applicable to other industrial robots in the future. The developed gesture command system is demonstrated on a heavy duty industrial robot