Martha Roselia Contreras-Valenzuela

This study proposes a decision support system that uses a fuzzy logic model to assess the risk level associated with repetitive upper limb movements during work tasks, which can lead to musculoskeletal disorders. The model considers three main sets: biomechanics, anthropometrics, and productivity. Standardised parameters were utilised to determine the risk level associated with movement. To validate the findings, a fuzzy model was applied to assess 123 female workers across three automatic high-speed production lines as a case study. The model quantifies the risks using 54 membership equations and incorporates nine linguistic variables organised into three sets: biomechanical: this includes applied force, moment force, and angle of the torso from vertical; anthropometric: this includes workers’ age and height and body mass index; and productivity: this includes working area depth, exposure time, and repetitiveness. The resulting fuzzy model, which is based on fuzzy set theory, utilises only four general fuzzy rules and allows for the evaluation of multiple workers simultaneously, providing a competitive advantage over models that rely on a large number of individual fuzzy rules to assess just one worker. The biomechanical set evaluates applied force and moment force based on productivity factors. Consequently, the behaviour of the group of 123 evaluations changed as the productivity risk value was introduced. For instance, in Test 1, which involves a low-risk task, we observed a biomechanical risk pattern that was solely related to the worker’s anthropometry. In Test 2, which presents a medium risk, the pattern of evaluations shifted, revealing behaviours that were more influenced by both anthropometric and biomechanical characteristics. Finally, in Test 3, the impact of anthropometry and biomechanics was clear in the risk assessment patterns, which aligned closely with the anthropometric. The DSS could help improve policies and work conditions.

To assess the ergonomic risk level in work systems involving tasks performed with hands or fingers, it is necessary to know the exerted triaxial forces. To address this need, a prototype of a triaxial load cell based on principles of linear elasticity theory and mechanical problems of torsion, bending and axial load is presented. This work includes an analytical strain model for each instrumented point and its solution regarding the applied force to a triaxial load cell. The proposed load cell was calibrated and validated by performing different static experimental tests. As a case study, the applied force in three directions while the thumb activates a cigarette lighter was measured. Triaxial forces and resultant forces were obtained and compared with the parameter of 10 N established by the ergonomic standards as reference values for pressing down with the thumb, finding that the applied forces in eight tests were 23.73 N, 43.51 N, 12.69 N, 14.50 N 20.35 N, 21.67 N, 39.74 N and 46.02 N, exceeding the reference values and establishing a direct relationship with Quervain syndrome. In conclusion, the developed load cell is a valid and reliable alternative to measure many forces that cannot be obtained with commercial devices, allowing the level of ergonomic risk to be determined with great precision.

The purpose of this study was to propose an interactive computer system that utilises the MATLAB Fuzzy Logic Designer to measure the level of implementation of SDG 8, which focuses on sustainable decent work (SDW) and economic growth. This study used policies and laws as parameters to determine the presence or absence of SDW. The fuzzy method was implemented in car windshield manufacturing in the auto parts industry as a case study to define and quantify work conditions and to determine the level of sustainable decent work (SDWL). The study described environmental conditions, such as noise, lighting, and heat stress; ergonomic factors, such as exposure time, the mass of the object manipulated, and lifting frequency; and organisation at work, such as workplace violence, salary, and workday, as linguistic variables. The level of the presence or absence of SDW was defined as their membership functions. The resulting vectors determined the absence of SDW with a score of 1.5 in two linguistic variables: environmental conditions and ergonomic factors. Some features of SDW in the linguistic variable organisation at work had an SDW score of 5. The SDWL vector determined a final score of 1.24, indicating the absence of decent work in production areas. This study found that the workers suffer a lack of long and healthy lives and a bad standard of living without economic growth due to work-related musculoskeletal disorders and work illnesses, increasing their out-of-pocket spending and catastrophic health expenses. As a CSR approach, assessing SDWLs helped managers improve policies and work conditions.

Objective: A hierarchical cluster analysis for the cardboard manufacturing industry was developed with the aim of identifying similarities between workstations in terms of musculoskeletal stress factors (MSFs) and their impact on workers’ bodies. Methods: The hierarchical clustering analysis was conducted using data from 44 workstations, which included 6 body part divisions and 51 stress factors as variables with 36 answer options. Firstly, the content of the dataset was defined. Secondly, the data were agglomerated and classified into 3 clusters using Ward’s method based on the presence or absence of stress factors. Finally, the multivariable matrix was reduced to 2 factors: the x-axis representing the risk level of the workstation, and the y-axis representing the impact on the workers’ health. Results: The study found that workers’ knees were the most affected body parts, with 47 cases. The resulting work-related musculoskeletal disorders included tendinitis, arthralgia, chondromalacia, and gonarthrosis. The MSF with the most significant impact on the body’s health was fatiguing work that involves repeated jumps, prolonged squatting, or kneeling, present in cluster 1 and cluster 3. Moreover, two of the most common MSFs associated with repeated work positions were identified: a mild forward flexion of the back (63 cases) in combination with one leg being used more often to support the body (56 cases). Conclusions: It was possible to identify the main work-related musculoskeletal disorders and the associated stress factors for the cardboard manufacturing industry by using hierarchical cluster classification and analysis, enabling the classification of risk levels and the impact on body health for each workstation.

In this work, we propose a fuzzy inference as a decision support system built in the MATLAB Fuzzy Logic Designer for evaluating manual material handling risk conditions. The input variables for the fuzzy decision were: (1) the total time duration of the manual material handling in one shift of 450 min, with 3 h considered the maximal exposition time; (2) 25 kg as a maximal mass reference which should never be exceeded; (3) the repetitiveness of the manual material handling task through the shift considering as the maximal frequency of four lifts per min. Results of 135 earlier direct ergonomic evaluations made using the method proposed by the ISO 11228-1 were used as validator results, and called “expected results”. The experimentation intended to simulate an ergonomic evaluation in different boundary conditions of work and verify if the fuzzy interface could correctly replicate the results of the ergonomic evaluations. As validation, the list with the 135 expected results was compared against the evaluation made by the fuzzy logic interface, called “Work_Conditions”. From the comparison, only three evaluations (0.02%) differed with respect to the expected results. Consequently, it is concluded that the fuzzy interface can be used as a tool for automating the determination of manual material handling ergonomic risk levels, with great precision.

An ergonomic intervention method based on QOC Matrix the workers’ voice was implemented in a study case. The diagnosis and analysis developed are used in improvement proposals for workstation redesign. The workers’ voice resulting from reports of the employee’ complaints and symptomatology was the base for a standardized method that comprises: (a) QOC questionnaire application, (b) risk factor categorization, (c) determination of unsafe and unhealthy ergonomic metrics, (d) figuring out the task content impact in the workers’ body, and (e) work system diagnosis. Since workers’ voice, the risk identification made included: (1) the task content linked to work method: repetitiveness associated with the sensor activation using the fingers and the repetitive movements include twist and the stretch of wrist, (2) workplace design regarding container height and injuries caused in wrists and elbows due to hits, (3) task developed regarding risk time exposition and workers position, and (4) workplace design regards to housing collector distance from filling area linked to workers position adopted for reach bags. Improvements included redesign of the workstation with a system of 90° exit discharge curve, one elevation system, and a photoelectric sensor in filling nozzle for automatic filling. As an improvement result, the activity called bags provision was eliminated from the task.

A correct identification of ergonomic risks and their physical location in production areas becomes vital for the prevention of work-related illnesses. The method proposed for detecting musculoskeletal disorders (MSDs) in industrial workplaces has the objective of identifying the relationship between the workplace design and the nonergonomic task content. A mapping of work conditions was implemented to develop a diagnosis about hazards and ergonomic risk factors present in the work system. The information collected was organized in an ergonomic risk map with the following structure: inputs, information about risks and hazards, process, information about how the risk exposure leads to MSDs and outputs, and information about the consequences of risk factor exposure. The mapping results allowed determining the causes of work-related illnesses in activities of polishing and screening metals, establishing as a main cause of risk the barrel height (1.70 m) that forces the material handling above the shoulders. Force demands required to perform the task (around 277 N in each lifting) were determined. The work-related illnesses identified were low back injuries and rotator cuff injures. The information contained in the map improves the understanding of employers and workers about the origin of ergonomic problems and supports the decision-making about improvement projects focused on risk elimination.

The present research is focused on the analysis of an industrial activity where the case under study is wire extrusion activity, which has been developed using old machines. This activity is analyzed considering the task and its elements to identify the movements and sequence of actions performed by the workforce and the machines. One of these activities is the roll-up of lead wire coming from the extruding machine. The task is done by the workforce 73 times during a shift and roughly consists in transporting the wire to the pulley guide and driving the lead wire until the container is rolled up manually. The analysis shows that the workers are exposed to hazardous conditions that could affect their health, meaning they are under risk of suffering an injury or a disease by exposure to repetitive actions and high temperatures (>90°C). Based on the latter, the design and development of a wire winder device has been proposed, which implements a programmable logic controller and servomechanism to replace the activities done manually. A ladder diagram is proposed to control the action performed by the servomechanism based on a stimulus received from the environment.