Search Results (17)

Repetitive movements and the speed of upper limbs increase the risk of musculoskeletal disorders. This study aimed to analyse the risk of shoulder injuries in repetitive tasks by evaluating the humerus angle, angular velocity, and angular acceleration during simulated chicken wing cutting. The study was conducted in a laboratory simulating a real environment. Thirty-six healthy right-handed volunteers were assessed using an electromagnetic tracking device, TrakSTAR, integrated with MotionMonitor™ (Innovative Sports Training, Inc. Chicago, IL) and software to collect 3-D kinematic data developed in the research centre. The equipment measured the angles performed by the upper limbs during the entire movement. The humerus angles were automatically transformed into angular velocity (°·s⁻¹) and angular acceleration (°·s⁻²). Maximum angular velocities were 27.39°·s⁻¹ (men, right humerus) and 22.39°·s⁻¹ (women, left humerus), both below the safe limit. Maximum accelerations were 25.32°·s⁻² (men, left side) and 28.94°·s⁻² (women, left side); safety values for these accelerations are not established. Monotony is a risk factor, especially for the dominant side. Future studies should evaluate risk factors simultaneously in repetitive tasks. Repetitiveness exceeds the safe limit according to the OCRA method. Full article

Human–robot collaboration stands as one of the research frontiers in industrial applications due to the possibility for human operators to be supported by robots in carrying out their tasks in a shared workspace. However, advances in this field can be slowed down by the lack of standards regarding the safety and ergonomics of such applications. This article aims at reducing this gap by presenting an adaptation of the standard ISO 11228-3 for the ergonomic evaluation of hand-guiding applications through the OCRA index. This innovative methodology is innovatively applied to a drilling application in which a human operator hand-guides a collaborative robotic system consisting of a Franka Emika Panda robot, a force/torque sensor and an IMU suit to track the motion of the operator’s body. The SaRAH app, a MATLAB 2020a-based software tool developed on purpose, implements the ergonomic assessment procedure, allowing the proper redesign of the working shift (offline mode) or providing the worker suggestions to improve his/her behavior (online mode) so as to reduce the ergonomic risk. Full article

Mycotoxin contamination of animal feed is a complex issue in both animal wellness and food safety. The most diffused mycotoxins subject to the official control of animal feed are Aflatoxin B1 (AF), Zearalenone (ZEA), Deoxynivalenol (DON), Ochratoxin A (OCRA), Fumonisins (FUMO), and T-2/HT-2 toxins. This work describes the results of five years of monitoring focused on the evaluation of mycotoxin contamination of animal feed. Analytical determinations were carried out by means of accredited ELISA. The obtained results showed a non-alarming scenario, with several samples resulting as “non-compliant” according to the Maximum Residue Limits (MRLs) set in European Regulation No. 574/2011. Out of 722 analyzed samples coming from 2 Italian regions, Apulia and Basilicata, 14 samples were characterized by mycotoxin concentrations higher than related MRL; in particular, 5, 4, and 5 non-compliant samples for DON, AF, and ZEA, respectively. This study also evaluated the possible correlations between mycotoxin type and feed use with a special focus on animal sensitivity to mycotoxins. Full article

In the search to enhance ergonomic risk assessments for upper limb work-related activities, this study introduced and validated the efficiency of an inertial motion capture system, paired with a specialized platform that digitalized the OCRA index. Conducted in a semi-controlled environment, the proposed methodology was compared to traditional risk classification techniques using both inertial and optical motion capture systems. The inertial method encompassed 18 units in a Bluetooth Low Energy tree topology network for activity recording, subsequently analyzed for risk using the platform. Principal outcomes emphasized the optical system’s preeminence, aligning closely with the conventional technique. The optical system’s superiority was further evident in its alignment with the traditional method. Meanwhile, the inertial system followed closely, with an error margin of just ±0.098 compared to the optical system. Risk classification was consistent across all systems. The inertial system demonstrated strong performance metrics, achieving F1-scores of 0.97 and 1 for “risk” and “no risk” classifications, respectively. Its distinct advantage of portability was reinforced by participants’ feedback on its user-friendliness. The results highlight the inertial system’s potential, mirroring the precision of both traditional and optical methods and achieving a 65% reduction in risk assessment time. This advancement mitigates the need for intricate video setups, emphasizing its potential in ergonomic assessments. Full article

Most granular flow in nature and industrial processing has the property of polydispersity, whereas we are always restricted to using the monodisperse drag force model in simulations since the drag force model with polydispersity is difficult to establish. Ignoring polydispersity often results in obvious deviations between simulation and experimental outcomes. Generally, it is very hard for us to describe the characteristics of polydispersity in drag force by using a function with analytic expression. Recently, the artificial neural network (ANN) model provides us the advantages of estimating these kinds of outcomes with better accuracy. In this work, the ANN is adopted to model the drag force in polydisperse granular flows. In order to construct a reasonable ANN algorithm for modeling the polydisperse drag force, the structures of ANN are elaborately designed. As training for the ANN drag model, a direct numerical simulation method is proposed, based on the lattice Boltzmann method (LBM), to generate the training data, and an adaptive data filtering algorithm, termed as the optimal contribution rate algorithm (OCRA), is introduced to effectively improve the training efficiency and avoid the over-fitting problems. The results support that the polydispersity of the system can be well scaled by the ANN drag model in a relatively wide range of particle concentrations, and the predicted results coincide well with the experimental ones. Moreover, the ANN drag model is not only effective for polydisperse systems, but compatible with monodisperse systems, which is impossible using traditional drag models. Full article

This research article focuses on the ergonomic design of the workstations for the plastics industry plant to reduce the postural load that improves the workers’ productivity and the operators’ absenteeism due to musculoskeletal disorders. This article develops an innovative solution to deal with one of the main problems of the plastic industry, namely, the high rate of worker absenteeism generated by musculoskeletal disorders due to the high postural load at the stations of work in this industry. The research is divided into four stages, namely the Determination of the objectives through the analysis of the problem and its root causes, the Redesign of the work methodologies in the productive area, the Improvement in the activities and tools used in the production chain, and Evaluations of the different impacts that the proposal entails. A proposed model validated with the Delmia V5 software and evaluation methods such as RULA, REBA, and OCRA, made possible a reduction in the level of risk of 50% and 66.7% in the different jobs analyzed and obtained 42,929 PEN in savings per year in respect to the total costs generated by the absenteeism presented. The result of the new workstations satisfies the ergonomic aspects and the needs of the workers. The study focuses on an analysis of risk levels that occurred in each of the high-density bag production activities, where non-conformity was found regarding the high risks presented, those leading causes with inappropriate postures by the staff, non-optimal working conditions, and absence of ergonomic furniture. This research serves as the basis for future lines of research and other companies with similar characteristics to implement the model. Full article

Background: Several methods with which to assess the risk of biomechanical overload of the upper limb are described in the literature. Methods: We retrospectively analysed the results of the risk assessment of the biomechanical overload of the upper limb in multiple settings by comparing the application of the Washington State Standard, the threshold limit values (TLV) proposed by the American Conference of Governmental Industrial Hygienists (ACGIH), based on hand-activity levels (HAL) and normalised peak force (PF), the Occupational Repetitive Actions (OCRA) checklist, the Rapid Upper-Limb Assessment (RULA), and the Strain Index and Outil de Repérage et d’Evaluation des Gestes of INRS (Institut National de Recherche et de Sécurité). Results: Overall, 771 workstations were analysed for a total of 2509 risk assessments. The absence of risk demonstrated for the Washington CZCL, used as the screening method, was in good agreement with the other methods, with the sole exception of the OCRA CL, which showed at-risk conditions in a higher percentage of workstations. Differences in the assessment of the frequency of actions were observed among the methods, while their assessments of strength appeared to be more uniform. However, the greatest discrepancies were observed in the assessment of posture. Conclusions: The use of multiple assessment methods ensures a more adequate analysis of biomechanical risk, allowing researchers to investigate the factors and segments in which different methods show different specificities. Full article

Transportation systems play a key role in urban development by providing access for people to markets and education, employment, health care, recreation, and other key services. However, uncontrolled urban population and fast growth of vehicle mobility inevitably lead to unsustainable urban transportation systems in terms of economic, technical, social, and geographical aspects of sustainability. Thus, there is a need to select suitable sustainable urban transportation (SUT) alternatives, which can contributed to the technological advancement of a city and changes in societal necessities, mitigating the climate change impact from transport and transforming living habits, in the context of high urban population growth. Therefore, this paper aims to introduce an integrated multi-attribute decision analysis (MADA) framework for assessing and ranking the sustainable urban transportation (SUT) options under an intuitionistic fuzzy sets (IFSs) context. In this regard, firstly IF-distance measures and their properties are developed to obtain the criteria weight. Second, an IF-relative closeness coefficient-based model is presented to find the criteria weights. Third, the operational competitiveness rating (OCRA) model is introduced with the IF-score function-RS-based decision experts’ weighing model and the relative closeness coefficient-based criteria weight determination model under the IFSs environment. To exemplify the utility and effectiveness of the developed IF-relative closeness coefficient-based OCRA methodology, a case study ranking the different SUT bus options is presented from an intuitionistic fuzzy perspective. A comparison with different models is made to prove the superiority and solidity of the obtained outcome. Moreover, the comparative analysis outperforms the other extant MADA models, as it can provide more sound outcomes than others, and thus it is more suitable and efficient to elucidate uncertain information in handling practical MADA problems. In this study, we analyze and determine the most suitable and sustainable SUT by considering the economic, technical, environmental, and social dimensions of sustainability and also make a significant contribution to the current scientific knowledge by providing a novel decision support system from an uncertainty perspective. Full article

The Renaissance treatise De Re Metallica (Georgius Agricola, 1556) is one of the first works that deals in detail with the state of the art of metal mining, compiling the main techniques and mechanical devices used in this industrial activity at that time. An advanced knowledge of the human–machine set is observed in this treatise, from a mechanical and ergonomics point of view. The main objective of this work is to carry out an ergonomics analysis of one of the mechanical devices collected in the sixth book of this treatise. It is intended to show that there was a certain concern for ergonomics in the Renaissance, long before the first appearance of this concept. Specifically, a mine water extraction pump, powered by three different systems, is analyzed. Current ergonomics assessment methods have been used to perform this comparative analysis. The postural load has been assessed by the rapid upper limb assessment (RULA) and the rapid entire body assessment (REBA). The Check List OCRA (occupational repetitive action) has been used to perform the analysis of repetitive movements. The results have shown an evolution of the machine, not only on a mechanical level, but also in movements, postures, and safety of the operator for the three methods applied. It is, therefore, an example of practical and real ergonomics applied to machine design dating from the 16th century. In addition, this work may be a very interesting tool for teaching, since it allows showing examples of ergonomics in productive areas related to historical context. Full article

Temperature gradient changes on the surface of the skin or in the middle of the body are signs of a disease. The aim of this study is to develop quantitative models for the prediction of cumulative trauma disorders (CTDs) arising from highly repetitive activities, considering risk factors, such as age, gender, body mass index (BMI), blood pressure (BP), respiratory rate (RR), and heart rate, to prevent injuries in manufacturing factory operators. This research involved 19 individuals from the area of sanding and 14 individuals from the area of tolex in manufacturing factories who had their vital signs and somatometry taken, as well as thermal images of their hands in the dorsal and palmar areas; an evaluation by the OCRA method was also applied. Factors such as BP and heart rate were determined to significantly influence the injuries, but no strong association with BMI was found. Quadratic regression models were developed, the estimates of which were adequately adjusted to the variable (R² and R² adjusted > 0.70). When integrating the factors of the OCRA method to the generated models, a better fit was obtained (R² and adjusted R² > 0.80). In conclusion, the participants who present levels out of the normal range in at least one of the factors have high probabilities of developing injuries in their wrists. Full article

Achieving a supply chain that is resilient to potential unforeseen disruptions (e.g., strikes, floods, tsunamis, etc.) remains one of the vital concerns of decision makers (DMs). To build up a reactive supply chain plan towards resilience, the purchasing department needs to pay the strictest attention to sourcing decisions. This study contributes to the literature through developing an efficient resilient supplier selection approach based on a new holistic framework that enables the identification of key resilience pillars (RPs) and traditional business criteria (TBC) in light of a thorough literature review and experts’ opinions. To this end, the relative importance of TBC/RP was measured by applying the DEMATEL (D) method. This was followed by the application of MABAC-OCRA-TOPSIS-VIKOR (MOTV) methods to verify the suppliers’ ranking. Furthermore, the Spearman rank correlation coefficient (SRCC) approach was used to investigate the correlation among the suppliers’ ranking, revealed via the four methods. In this work, a real sourcing problem of scrap metal for a steel manufacturing company was solved to prove the applicability of the proposed approach. The research outcome revealed that the TBC of “trust” is the most important criterion, followed by the “cost”, leaving the “geographical location” criterion as the least important one. In this context, the RP of “flexibility” attained the highest relative weight compared to “agility”, which secured the lowest weight. The results also showed “absolute” correlation among MABAC, VIKOR, and OCRA compared to “very strong” correlation between TOPSIS and the others. This research can support supply chain managers to achieve supply chain systems that reduce not only sourcing costs, but also potential losses because of disrupting threats, by building resilient supply chains. Full article

In the last decades, Reconfigurable Manufacturing Systems (RMSs) rose as an emerging manufacturing strategy matching the modern industrial and market requirements asking for a wide variety of products in flexible batches. A traditional reconfigurable manufacturing environment consists of dynamic cells, called Reconfigurable Machine Cells (RMCs), including a set of machines called Reconfigurable Machine Tools (RMTs). Such machines are characterized by fixed elements, i.e., basic modules, and dynamic elements, i.e., auxiliary modules, allowing them to perform different operations. Despite their automation level, these systems require the intervention of the human operators in performing specific tasks, e.g., handling of the auxiliary modules from the warehouse to the RMTs and their assembly/disassembly to/from the RMTs. This issue rises relevant ergonomic and safety questions due to the human–machine collaboration. Following this stream, this paper proposes and applies a bi-objective optimization model for the design and management of RMSs. The technical objective function minimizes the reconfiguration time, i.e., the time needed to equip the RMTs with the required auxiliary modules, and the part and auxiliary module travel time among the RMCs. The ergonomic objective function minimizes the repetitive movements performed by the human operators during the working activities according to the ISO 11228-3 standard. Results show the existence of a good trade-off between the two objective functions, proving the possibility to improve the ergonomic conditions of the human operators without excessively increasing the total time needed for RMTs reconfiguration and for part and auxiliary module travelling. Full article

Brazil is the leader in poultry meat exports, in which most products are in the form of cuts. This study analyzed the exertion perception of poultry slaughterhouses workers when performing cutting tasks, as well as the influence of knife sharpness on the risk of developing musculoskeletal disorders by Occupational Repetitive Action (OCRA) method. Participants (n = 101) from three slaughterhouses were asked to rate their perceived exertion on the Borg scale during the cutting task when the knife was well and poorly sharpened. The OCRA results showed that the score for cutting with a dull knife was greater (43.57 ± 13.51) than with a sharp knife (23.79 ± 3.10) (p < 0.001). Consequently, there was a significant increase in the risk level of acquiring upper-limb work-related musculoskeletal disorders (UL-WMSD) by using a “poorly sharpened” knife (29%; p < 0.001; Borg scale 2–8). Thus, maintaining well-sharpened knives for optimal performance of the cutting task (fewer technical actions) is suggested, as well as including knife sharpening in the standard operating procedure to reduce musculoskeletal disorders. Full article

People represent one of the most significant resources of an organization, and therefore, personnel selection is one of the problems that organizations have increasingly been facing. The criteria that influence the final decision are usually opposing, so the application of multiple-criteria decision-making methods (MCDM) represents a suitable way for the facilitation of the given process. Additionally, the decision environment is characterized by the vagueness and uncertainty and, because of that, it is very hard to express the criteria over the exact crisp numbers. To acknowledge the unpredictability and obscurity of the available information important for the selection of the optimal candidate, a hybrid grey MCDM model for personnel selection is proposed in this paper. As an extension of the PIPRECIA method, the novel Grey Pivot Pairwise Relative Criteria Importance Assessment—the PIPRECIA-G method—is proposed and used for the determination of criteria importance. The PIPRECIA-G method preserved the good features of the PIPRECIA, but its superiority is reflected in its ability to deal with input data that are vague and grey. For the final ranking of the considered alternative candidates, the OCRA-G method is used. Basing the decision process and candidate selection on the two grey extended MCDM methods contributes to the increase of the reliability and confidence in the performed selection. Full article

In this paper, we present the Hefei EMI Cloud Retrieval Algorithm (HECORA), which uses information from the O₂-O₂ absorption band around 477 nm to retrieve effective cloud fraction and effective cloud pressure from satellite observations. The retrieved cloud information intends to improve the atmospheric trace gas products based on the Environment Monitoring Instrument (EMI) spectrometer. The HECORA method builds on OMCLDO2 and presents some evolutions. The Vector Linearized Discrete Ordinate Radiative Transfer (VLIDORT) model has been used to produce the Top of the Atmosphere (TOA) reflectance Look-up Tables (LUT) as a function of the cloud fraction and cloud pressure. Applying the Differential Optical Absorption Spectroscopy (DOAS) technique to the synthetic reflectance LUT, the reflectance spectra can be associated with O₂-O₂ geometrical vertical column densities (VCD_geo) and continuum reflectance. This is the core of the retrieval method, since there is a one-to-one relationship between O₂-O₂ VCD_geo and continuum reflectance, on the one hand, and effective cloud fraction and effective cloud pressure, on the other hand, for a given illumination and observing geometry and given surface height and surface albedo. We first used the VLIDORT synthetic spectra to verify the HECORA algorithm and obtained good results in both the Lambertian cloud model and the scattering cloud model. Secondly, HECORA is applied to OMI and TROPOMI and compared with OMCLDO2, FRESCO+, and OCRA/ROCINN cloud products. Later, the cloud pressure results from TROPOMI observations obtained using HECORA and FRESCO+ are compared with the CALIOP Cloud Layer product. HECORA is closer to the CALIOP results under low cloud conditions, while FRESCO+ is closer to high clouds due to the higher sensitivity of the O₂ A-band to cloud vertical information. Finally, HECORA is applied to the TROPOMI NO₂ retrieval. Validation of the tropospheric NO₂ VCD with ground-based MAX-DOAS measurements shows that choosing HECORA cloud products to correct for photon path variations on the TROPOMI tropospheric NO₂ VCD retrievals has better performance than using FRESCO+ under low cloud conditions. In conclusion, this paper shows that the HECORA cloud products are in good agreement with the well-established cloud products and that they are suitable for correcting the effect of cloud in trace gas retrievals. Therefore, HECORA has the potential to be applied to EMI. Full article