Work-related musculoskeletal disorders (WMSD) are one of the main occupational health problems. The best strategy to prevent them lies on ergonomic interventions. The variety of industrial processes and environments, however, makes it difficult to define an all-purpose framework to guide these ergonomic interventions. This undefinition is exacerbated by recurrent introduction of new technologies, e.g., collaborative robots. In this paper, we propose a framework to guide ergonomics and human factors practitioners through all stages of assessment and redesign of workstations. This framework was applied in a case study at an assembly workstation of a large furniture enterprise. Direct observation of work activity and questionnaires were applied to characterize the workstations, the process, and the workers’ profiles and perceptions. An ergonomic multi-method approach, based on well-known and validated methods (such as the Finnish Institute of Occupational Health and Rapid Upper Limb Assessment), was applied to identify the most critical risk factors. We concluded that this approach supports the process redesign and tasks’ allocation of the future workstation. From these conclusions, we distill a list of requirements for the creation of a collaborative robot cell, specifying which tasks are performed by whom, as well as the scheduling of the human-robot collaboration (HRC).

Lean Manufacturing (LM), Ergonomics and Human Factors (E&HF), and Human–Robot Collaboration (HRC) are vibrant topics for researchers and companies. Among other emergent technologies, collaborative robotics is an innovative solution to reduce ergonomic concerns and improve manufacturing productivity. However, there is a lack of studies providing empirical evidence about the implementation of these technologies, with little or no consideration for E&HF. This study analyzes an industrial implementation of a collaborative robotic workstation for assembly tasks performed by workers with musculoskeletal complaints through a synergistic integration of E&HF and LM principles. We assessed the workstation before and after the implementation of robotic technology and measured different key performance indicators (e.g., production rate) through a time study and direct observation. We considered 40 postures adopted during the assembly tasks and applied three assessment methods: Rapid Upper Limb Assessment, Revised Strain Index, and Key Indicator Method. Furthermore, we conducted a questionnaire to collect more indicators of workers’ wellbeing. This multi-method approach demonstrated that the hybrid workstation achieved: (i) a reduction of production times; (ii) an improvement of ergonomic conditions; and (iii) an enhancement of workers’ wellbeing. This ergonomic lean study based on human-centered principles proved to be a valid and efficient method to implement and assess collaborative workstations, foreseeing the continuous improvement of the involved processes.

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One of the key interesting features of collaborative robotic applications is the potential to lighten the worker workload and potentiate better working conditions. Moreover, developing robotics applications that meets ergonomic criteria is not always a straightforward endeavor. We propose a framework to guide the safe design and conceptualization of ergonomic-driven collaborative robotics workstations. A multi-disciplinary approach involving robotics and ergonomics and human factors shaped this methodology that leads future engineers through the digital transformation of a manual assembly (with repetitive and hazardous operations) to a hybrid workstation, focusing on the physical ergonomic improvement. The framework follows four main steps, (i) the characterization of the initial condition, (ii) the risk assessment, (iii) the definition of requirements for a safe design, and (iv) the conceptualization of the hybrid workstation with all the normative implications it entails. We applied this methodology to a case study in an assembly workstation of a furniture manufacturing company. Results show that the methodology adopted sets an adequate foundation to accelerate the design and development of new human-centered collaborative robotic workstations.

The ergonomic assessment of adopted working postures is essential for avoiding musculoskeletal risk factors in manufacturing contexts. Several observational methods based on external analyst observations are available; however, they are relatively subjective and suffer low repeatability. Over the past decade, the digitalization of this assessment has received high research interest. Robotic applications have the potential to lighten workers’ workload and improve working conditions. Therefore, this work presents a musculoskeletal risk assessment before and after robotic implementation in an assembly workstation. We also emphasize the importance of using novel and non-intrusive technologies for musculoskeletal risk assessment. A kinematic study was conducted using inertial motion units (IMU) in a convenience sample of two workers during their normal performance of assembly work cycles. The musculoskeletal risk was estimated according to a semi-automated solution, called the Rapid Upper Limb Assessment (RULA) report. Based on previous musculoskeletal problems reported by the company, the assessment centered on the kinematic analysis of functional wrist movements (flexion/extension, ulnar/radial deviation, and pronation/supination). The results of the RULA report showed a reduction in musculoskeletal risk using robotic-assisted assembly. Regarding the kinematic analysis of the wrist during robotic-assisted tasks, a significant posture improvement of 20–45% was registered (considering the angular deviations relative to the neutral wrist position). The results obtained by direct measurements simultaneously reflect the workload and individual characteristics. The current study highlights the importance of an in-field instrumented assessment of musculoskeletal risk and the limitations of the system applied (e.g., unsuitable for tracking the motion of small joints, such as the fingers).

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.

Human-Robot Collaboration (HRC) systems are often implemented seeking for reducing risk of Work-related Musculoskeletal Disorders (WMSD) development and increasing productivity. The challenge is to successfully implement an industrial HRC to manage those factors, considering that non-linear behaviors of complex systems can produce counterintuitive effects. Therefore, the aim of this study was to design a decision-making framework considering the key ergonomic methods and using a computational model for simulations. It considered the main systemic influences when implementing a collaborative robot (cobot) into a production system and simulated scenarios of productivity and WMSD risk. In order to verify whether the computational model for simulating scenarios would be useful in the framework, a case study in a manual assembly workstation was conducted. The results show that both cycle time and WMSD risk depend on the Level of Collaboration (LoC). The proposed framework helps deciding which cobot to implement in a context of industrial assembly process. System dynamics were used to understand the actual behavior of all factors and to predict scenarios. Finally, the framework presented a clear roadmap for the future development of an industrial HRC system, drastically reducing risk management in decision-making.

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