# Towards an Ergonomic Assessment Framework for Industrial Assembly Workstations--A Case Study
## 1 Introduction  
Work-related musculoskeletal disorders (WMSD) are one of the main occupational health problems in the European Union and a major cause of occupational absenteeism and decreased productivity [1; 2]. The incidence of WMSD is higher than normal in industrial furniture manufacturing due to the characteristics of the involved tasks [2]. The development of WMSD is mainly attributed to three factors, (i) occupational risk, (ii) individual characteristics, and (iii) social factors [3]. Occupational risk factors include awkward postures, repetitive tasks, frequent and/or excessive tasks involving the handling of heavy loads, and thermal discomfort. The individual characteristics are related to individual limitations or health problems. Finally, social factors such as family and economic problems may interfere with motivation and attention during work. According to the European Agency for Safety and Health at Work, organizational and psychosocial factors such as high demand for work or low autonomy, and low job satisfaction can potentiate the WMSD risk [4]. On top of the detrimental health impact of WMSD, these disorders are also financially harmful to the economy in general, being urgent its prevention and mitigation [5; 6]. Scientific literature shows that ergonomic intervention is the best strategy to prevent WMSD [7]. The ergonomic intervention aims to redesign the workstation and process to improve health, safety, and productivity [8]. Contrary to other occupational diseases that result from exposure to specific hazards, most WMSD have a multifactorial origin. In the prevention domain, several methods were presented and validated for WMSD risk assessment. These methods fall into the following categories: (i) self-reports and checklists; (ii) observational methods; (iii) direct measurements [9; 10]. The self-reports and checklists include the tools more generic according to their field of application (i.e., range of working tasks). At this level, previously validated questionnaires, such as the Nordic Musculoskeletal Questionnaire (NMQ) [11; 12], are conducted to collect the workers' perceptions. Checklists, such as the checklist for \"Ergonomic Hazard Identification\" of National Institute for Occupational Safety and Health [13], are also applied to identify risk factors. The observational methods rely on the direct observation of the work activity to conduct the risk assessment. These methods consider risk factors such as task frequency, task duration, and load handling and assess the impact of these risks based on the external physical workload. Examples of validated observational methods for assembly tasks are the Rapid Upper Limb Assessment (RULA) [14] and the Key Indicator Method for assessing physical workload during Manual Handling Operations (KIM-MHO) [15]. The direct measurements ergonomic methods rely on the sensorization of the workers to directly measure the risk factors' effect on physiological and biomechanical parameters. Examples of these sensors are the surface electromyography (EMG) to assess muscular activity and the electronic goniometers to record the range of joint motion [9]. Assembly workers are exposed to a significant physical workload [16]. The repetitiveness of manual tasks is an important risk factor for upper limbs WMSD (e.g., carpal tunnel syndrome, wrist tendonitis, and lateral epicondylitis) [10]. However, the back is the body region with the most serious work-related health problems indicated among European workers, being a problem transversal to a wide variety of jobs [4]. Human-robot collaborative manufacturing has been proposed as a potential solution to improve workplace conditions. This theory was tested in different studies [17; 18; 19; 20] with promising results in the reduction of the workload and the decrease of the WMSD risk. The industrial collaborative robots, also known as COBOTS, reduce ergonomic concerns that arise from on-the-job physical and cognitive stress, and further improve on workplace safety, quality, and productivity [18].