An integrated ergonomic risk assessment model based on fuzzy logic for assembly line balancing problem

In the contemporary industrial context, the growing demand for products can primarily be met through mass production. Despite the increasing use of automation, manual assembly stations remain prevalent and, in some cases, unavoidable. Current practices in manual assembly lines involve balancing tasks based on takt time to synchronize them. However, this approach often neglects ergonomic aspects, potentially leading to work-related musculoskeletal disorders (WMSDs) and loss of motivation among workers. Assembly line activities encompass several risk factors, including repetitive motions, awkward postures, heavy lifting, and stress. Ignoring human factors and prioritizing higher efficiency can amplify these risk factors, leading to an increase in WMSDs. Therefore, it is crucial to integrate ergonomics into assembly line balancing. Incorporating ergonomics into assembly line balancing is expected to reduce WMSDs, decrease costs associated with absenteeism, medical treatments, and worker rehabilitation, improve working conditions, and reduce errors in manual operations. Considering ergonomic factors in assembly line balancing problems can significantly improve ergonomic conditions. This study aims to develop a systematic approach to balance circular mixed-model assembly lines by incorporating ergonomic risk considerations, ultimately enhancing both worker safety and line efficiency. The primary objective of this research is to create a two-stage framework for the mixed-model assembly line balancing problem with ergonomic considerations (Ergo-MMALBP). The first stage involves determining the weights of ergonomic risk assessment methods using the interval-valued spherical fuzzy analytic hierarchy process (IVSF-AHP). Based on these weights, an integrated ergonomic risk assessment fuzzy logic model was constructed. This stage calculates the integrated ergonomic risk value using the fuzzy logic model based on REBA, OCRA, QEC, and COPSOQ risk scores, identifying risk classes. The second stage involves formulating mathematical models for the Ergo-MMALBP. These models aim to minimize cycle time while balancing the integrated ergonomic risk value and the tasks of each risk class across the stations. To validate the applicability and evaluate the performance of the proposed approach, an application was conducted in a cable harness production facility. The results indicated that ergonomic risks could be more evenly distributed, and higher ergonomic performance could be achieved with the same cycle time. Improvements in the sub-assembly line resulted in a 10-11% increase in line efficiency and a 12-25% improvement in ergonomic risk balancing performance. In the main assembly line, a 2-3% increase in line efficiency and a 6-12% improvement in ergonomic risk balancing performance were observed. The effects of ergonomic factors on assembly line balancing were further evaluated using multivariate analysis of variance (MANOVA). The multiple comparison results indicated that incorporating ergonomic factors into the model did not significantly affect cycle time, but it made the distribution of ergonomic risks among stations more balanced. The study demonstrates that the proposed approach can significantly benefit occupational safety and performance. Ergonomics, when integrated with assembly line balancing, offers numerous advantages. It reduces the risk of WMSDs, thereby decreasing absenteeism and associated costs while improving overall worker health and safety. Moreover, ergonomic interventions can enhance production efficiency by minimizing errors and increasing worker satisfaction and motivation. Despite these benefits, traditional assembly line balancing approaches often overlook ergonomic considerations, leading to suboptimal working conditions. The ergonomic risk assessment methods used in this study, such as REBA, OCRA, QEC, and COPSOQ, are well-established in the literature. Each method evaluates different aspects of ergonomic risk, providing a comprehensive assessment when used together. The IVSF-AHP technique was employed to determine the relative importance of each method, reflecting their specific strengths and relevance to different risk factors. The integrated ergonomic risk assessment fuzzy logic model developed in this study combines these methods' strengths, offering a holistic evaluation of ergonomic risks. By calculating an integrated ergonomic risk value, this model provides a more nuanced understanding of the overall ergonomic conditions in the assembly line. This integrated approach ensures that all relevant risk factors are considered, leading to more effective ergonomic interventions. The mathematical models formulated for the Ergo-MMALBP aim to balance ergonomic risks across workstations while minimizing cycle time. This dual objective ensures that ergonomic improvements do not come at the cost of production efficiency. The application of these models in a real-world setting, such as the cable harness production facility, demonstrates their practical relevance and effectiveness. The results of this application highlight the significant improvements in ergonomic risk distribution and line efficiency that can be achieved with the proposed approach. These findings underscore the importance of incorporating ergonomic considerations into assembly line balancing. They also provide a compelling case for the wider adoption of ergonomic risk assessment methods in industrial settings. In addition to practical applications, this study contributes to the academic literature by developing a novel framework for ergonomic risk assessment and assembly line balancing. The use of IVSF-AHP and fuzzy logic models represents an innovative approach to integrating ergonomic considerations into production planning. This framework can be adapted to various industrial contexts, offering a versatile tool for improving workplace ergonomics and efficiency. The limitations of this study primarily relate to the complexity and computational demands of the proposed models. Evaluating each task's ergonomic risk using multiple methods can be time-consuming, especially in large-scale assembly lines. However, this detailed assessment is essential for accurately identifying and mitigating ergonomic risks. Future research could explore the use of metaheuristic algorithms, such as genetic algorithms or bee colony algorithms, to address these computational challenges and enhance the scalability of the proposed models. Furthermore, the study's scope and significance extend beyond the immediate application in the cable harness production facility. The methodology developed can be tailored to different types of assembly lines, accommodating the specific ergonomic risks and production requirements of various industries. This adaptability makes the framework highly valuable for organizations aiming to improve their ergonomic standards while maintaining or even enhancing their production efficiency. Another notable contribution of this study is the empirical validation of the proposed models through real-world application and statistical analysis. The use of MANOVA provided robust evidence of the models' effectiveness in balancing ergonomic risks without compromising cycle time. These statistical insights are crucial for demonstrating the practical benefits of integrating ergonomics into assembly line balancing, offering a solid foundation for further research and implementation in diverse industrial settings. The study's contributions to the literature include the development of a fuzzy logic-based integrated ergonomic risk assessment model, the incorporation of physical, environmental, and psychosocial risk factors, and the creation of mathematical models for ergonomic assembly line balancing. Additionally, the use of IVSF-AHP to determine the weights of different ergonomic risk assessment methods represents a novel approach in this research area. Overall, this study demonstrates that integrating ergonomic considerations into assembly line balancing can significantly improve working conditions and production efficiency. The proposed two-stage framework offers a comprehensive approach to assessing and balancing ergonomic risks, providing valuable insights for both researchers and practitioners in industrial engineering. As ergonomic risk assessment continues to gain importance in the workplace, the methods and models developed in this study will play a crucial role in advancing ergonomic practices and promoting occupational health and safety.