Occupational musculoskeletal disorders management using Fuzzy TOPSIS Assessment of Repetitive Tasks (ART)

De Quervain's tenosynovitis as an occupational disease in agricultural worker: A case report

BACKGROUND

De Quervain's tenosynovitis is upper-limb disorder, more frequent in women. It is rarely recognized as an occupational disease.

OBJECTIVE

In this paper we reported work related de Quervain's tenosynovitis in cow milker.

METHODS

Ergonomic risk factors were assessed by utilizing assessment of repetitive tasks (ART) of the upper limbs method. Physical examination and imaging exams were used.

RESULTS

We presented a 36-year-old female agricultural worker (workplace cow milker) exposed to work factors (forceful hand/wrist exertions, repetition, extreme postures) for 14 years. She was suffering the pain in the right hand, mainly near the thumb for few years. She was treated conservatively and surgically, however disability was permanent. Clinical examination showed slight edema of the right hand, increased palm's sweating. Patient had reduced range of movements and grip strength.

CONCLUSIONS

Report shows that work-related factors were strongly associated with diagnosed de Quervain's tenosynovitis. Hand function plays an essential role in carrying out activities of daily living and this disorder pose a relevant burden of disease. Exposure to biomechanical factors should be an important initial target for the prevention of De Quervain's tenosynovitis in the working population.

Soft computing applications in the field of human factors and ergonomics: A review of the past decade of research

The main objectives of this study were to 1) review the literature on the applications of soft computing concepts to the field of human factors and ergonomics (HFE) between 2013 and 2022 and 2) highlight future developments and trends. Multiple soft computing methods and techniques have been investigated for their ability to address various applications in HFE effectively. These techniques include fuzzy logic, artificial neural networks, genetic algorithms, and their combinations. Applications of these methods in HFE have been highlighted in one hundred and four articles selected from 406 papers. The results of this study help address the challenges of complexity, vagueness, and imprecision in human factors and ergonomics research through the application of soft computing methodologies.

Assessment of working postures and physical loading in advanced order picking tasks: A case study of human interaction with automated warehouse goods-to-picker systems

BACKGROUND

Order picking activities are the most labor-intensive processes in retail warehouses. Although various automated order picking technologies have been developed recently, human intervention continues to be required. Most advanced order picking systems can be classified into automated storage and retrieval system (AS/RS) and moving robot types. Both types of goods-to-picker systems aim to reduce the picker's travel time required to determine product locations and to move these products to meet customer requests.

OBJECTIVE

Many studies on the efficiency and effectiveness of automated order picking systems have focused solely on system performance. Since human operators play an essential part in order picking systems from both the effectiveness and efficiency point of view, the work-related risk factors for the workers interacting with these systems should also be evaluated. In this paper, we assess the ergonomic design features of two system types, a moving robot (MR) and automated storage and retrieval system (AS/RS), focusing on the assessment of the risk factors for work-related postural stresses.

METHODS

We compare the performance factors of two order picking systems, i.e. MR and AS/RS, by applying a digital human modeling and simulation, and assessing the total average physical activity exhibited by human operators on a given order picking task.

RESULTS

The AS/RS type order picking system exhibited a lower risk for task-related postural stresses for warehouse workers.

CONCLUSIONS

The picking station for moving robot (MR) order picking system requires design changes in order to reduce postural stresses during human operator's interaction with such a system.