Search Results (58)

Flexible automated assembly lines (FAALs) in Industry 4.0 require robust quality management that integrates operational data with systematic risk analysis. However, Process Failure Mode and Effects Analysis (PFMEA) documents are often developed during the design phase and not systematically updated with actual production data, leading to a gap between formal risk assessment and operational reality. This study addresses this gap by developing and validating an integrated data-driven framework that combines classical quality tools (process flow charts, check sheets, cause-and-effect diagrams, and Pareto analysis) with data-driven PFMEA, creating traceable links from operational logs to risk ratings. While individual quality tools are well-established, the core contribution of this work is a structured data transformation pipeline that creates traceable, auditable linkages from raw operational event logs to calibrated PFMEA ratings with quantified uncertainty—a combination not previously demonstrated for flexible assembly systems. The framework was applied to FMS-200, a modular FAAL for bearing units, consisting of eight stations and a common transfer system. Analysis of 186 failure events across 2743 assembly cycles, including 18 product configurations, identified 40 distinct failure modes with risk priority number (RPN) values ranging from 60 to 378, revealing that approximately 90% of the aggregated risk is associated with pneumatic systems. Monte Carlo uncertainty analysis (10,000 iterations) demonstrated robust rank stability, with the top five failure modes maintaining their relative ordering in over 90% of simulations. The framework provides production and quality managers with a systematic methodology to maintain PFMEA relevance through continuous data integration, enabling evidence-based prioritization of improvement actions. Full article

This study investigates the synergistic influence of multi-walled carbon nanotubes (MWC-NTs), nanosilica powder (NSP), and polypropylene fiber waste (PFW) on the mechanical performance of mortar incorporating demolished concrete waste aggregates (DCWA). The replacement of natural aggregates with DCWA typically results in strength reductions and weak interfacial transition zones; therefore, the combined use of nanomaterials and microfibers is proposed as a mitigation strategy. A Taguchi Design of Experiments (DOE) approach was employed to optimize mix parameters, including MWCNT dosage, NSP content, PFW volume fraction, and DCWA replacement level. Mortar mixtures were prepared with MWCNTs (0–0.1% by binder weight), NSP (0–2% by binder weight), PFW (0–0.3% by volume), and DCWA (0–20% replacement of fine sand). Mechanical performance was assessed through compressive and flexural strength tests. A combined statistical approach using the Pareto chart and ANOVA identified the most influential parameters and their respective contributions to the response variable. The innovative aspect of this research lies in the synergistic integration of MWCNTs, NSP, demolished concrete waste, and polypropylene fiber waste within the mortar matrix, with the incorporation of nanomaterials specifically intended to compensate for the strength reduction typically induced by the use of demolition concrete waste aggregates. Although a potential nano-scale synergy between MWCNTs and NSP was initially considered, the experimental results indicated that the most relevant synergistic effects occurred among broader mix parameters rather than specifically between the two nanomaterials. Even so, when assessed individually, both nanomaterials contributed to improving the mechanical characteristics of the mortar—particularly nanosilica, which demonstrated a more pronounced effect—yet these individual enhancements did not translate into a distinct synergistic interaction between MWCNTs and NSP. The Taguchi DOE proved to be an efficient tool for multiple factor analysis, enabling reliable identification of the most influential parameters with a minimum number of tests. Its application facilitated the development of mortar mixtures that effectively integrate demolition waste while achieving enhanced mechanical performance through nano- and micro-scale reinforcement. Full article

The paper presents the issue of acquired and secondary auditory processing disorder (APD) in children and adolescents in the Polish population. The authors analyzed a group of individuals with APD and younger children who were at risk based on a detailed interview with parents. A comparison of developmental factors showed several similarities between the risk and diagnosed APD groups, including abnormal muscle tone (64.29% vs. 33.33%), ear diseases (42.86% vs. 57.58%), and complicated delivery (32.14% vs. 39.39%). In terms of school factors, the most significant difficulties were associated with poor concentration (78.57% vs. 54.55%), irregularities in mastering phonology related to writing (67.86% vs. 75.76%), and reading (64.29% vs. 78.79%), as well as problems with understanding speech-in-noise perception (60.71% vs. 57.58%). A comparison of children at risk of APD and those with a confirmed diagnosis revealed multiple similarities. The results were visualized using Pareto charts to highlight the most influential factors. The results indicate the need to disseminate screening that could show the APD risk group. Therefore, the diagnostic process could be performed more quickly in such individuals. Based on recurring developmental factors, the Risk Assessment Questionnaire (RAQ) was developed as a non-clinical screening tool to identify children potentially at risk of APD. The RAQ demonstrated a moderate discriminative potential (AUC = 0.68; sensitivity = 75%; specificity = 68%) and may support early referral for diagnostic evaluation. The results highlight the value of systematic screening to accelerate diagnosis and intervention, especially in populations where access to formal assessment is limited. Full article

Continuous flushing systems such as vortex settling basins (VSBs) are commonly utilized to remove sediment particles in power plants and irrigation and drainage networks. This study evaluates the performance of a typical VSB, focusing on sediment removal efficiency (${\eta }_e$), flow efficiency (${\eta }_{flow}$), and inlet canal efficiency (${\eta }_{in}$). In the continuous operation of VSBs, sediment removal efficiency remains the appropriate metric, as opposed to trapping efficiency. The impact of hydraulic and geometric parameters was analyzed using the Taguchi design, experimental modeling, and statistical analysis through response surface methodology (RSM). The performance of the VSB was evaluated using the ANOVA test, along with the Pareto chart and the desirability function approach for multi-objective optimization. The predicted optimal values for ${\eta }_{in}$, ${\eta }_e$, and ${\eta }_{flow}$ were 94.09%, 69.40%, and 91.67%, respectively. This optimum condition for having higher efficiency in the VSB was for the case with 0.3625 mm particle diameter, 0.1 m orifice diameter, 0.1 m end sill height, 22 L/s inlet discharge, and 0.05 m outlet weir. Larger sediment particle size and inlet discharge enhanced VSB desirability, while smaller orifice size and outlet weir height are preferred for optimal performance. This paper provides a framework for the optimum design of VSBs. Full article

Copper joints are indispensable in electronics and the electrical power industry due to their predominant usage in battery pack manufacturing for electric vehicle). Traditional joining methods are often limited by oxidation-related challenges. Recent efforts have focused on addressing these limitations by employing solid-state techniques like ultrasonic welding (USW) for joining similar metals. USW presents attractive advantages such as a lower processing temperature and shorter weld time. This study investigates the ultrasonic welding of Cu-Cu joints with a thickness of 0.5 mm, focusing on both mechanical and metallurgical properties. The influence of key process parameters, such as the welding time, pressure and vibration amplitude, was examined in relation to the welding energy and lap shear strength. Additionally, the relationship between the input energy and lap shear strength was explored. A Pareto chart analysis revealed the standardized effects of these parameters on the welding energy and average lap shear strength. The welding time had a significant influence on the welding energy, while the vibration amplitude had the greatest impact on the joint strength. Longer weld times of 2.50 to 4 s yielded a higher lap shear strength, averaging up to 2.30 kN. Notably, a higher lap shear strength was achieved at lower welding energy levels. Full article

The use of precast concrete pipes for water and sewage transportation systems is a very important element of a country’s infrastructure. The main aim of this study was to investigate the effects of concrete’s compressive strength and reinforcement levels on the mechanical performance of spun-cast full-scale precast concrete pipes in the local construction industries of developing countries. A test matrix was adopted using a full 3² factorial design. The studied concrete’s compressive strength was 20, 30, and 40 MPa, and reinforcement levels were 60%, 80%, and 100%, representing low, medium, and high levels, respectively. The medium level of reinforcement represented the reinforcement requirement of ASTM C76 in concrete pipes. A total of eighteen full-scale pipes of 450 mm diameter were cast in an industrial precast pipe unit using a spin-casting technique and were tested under a three-edge bearing load. The experimental results showed that the crack load and ultimate load of the tested pipes increased with higher levels of concrete strength and reinforcement levels. For example, an approximately 35% increase in the 0.30 mm crack load was observed when the concrete strength increased from 20 MPa to 30 MPa for all tested levels of reinforcement. Similarly, around a 19% increase in ultimate load was observed for pipes with 80% reinforcement compared to identical pipes with 60% reinforcement. It was found that the pipe class, as per ASTM C76, is highly dependent on the concrete strength and reinforcement levels. All of the pipes exhibited the development of flexural cracks at critical locations (crown, invert, and springlines). Moreover, concrete pipes cast with low-level strength and reinforcement also showed signs of crushing at the crown location near to the pipe failure. The analysis of variance (ANOVA) results showed that the main factors (compressive strength and reinforcement levels) were significantly affected by the cracking loads of precast pipes. No significant effect of the interaction of factors was observed on the crack load response. However, interaction factors, along with main factors, have significant effects on the ultimate load capacity of the concrete pipes, as indicated by the F-value, p-value, and Pareto charts. This study made an effort to illustrate and optimize the mechanical performance of pipes cast with various concrete strengths and reinforcement levels to facilitate the efficient use of materials for more resilient pipe infrastructure. Moreover, the exact optimization of concrete strength and reinforcement level for the desired pipe class will make the pipe design economical, leading to an increased profit margin for local spin-cast pipe fabricators without compromising the pipe’s quality. Full article

In this paper, an assessment of the quantitative and qualitative defects involved in automotive veneer trim parts manufacturing has been presented. The comparative qualitative analyses were carried out using Poisson process capability estimation and a Pareto chart. The visual surface inspection of the veneer trims was aimed to identify the types of defects resulting from the manufacturing process. The results indicate that the percentage of defects for the first sample are between 2.1% and 4.4% and the values for the second category are situated between 1.2% and 2.2%. Using 95% confidence intervals (CIs), the main statistical parameters were estimated. Also, the inferential analysis highlights that the specified acceptable percentage of rejects was not exceeded. Full article

The paper presents a study related to the implementation of failure modes and effects analysis (FMEA). The analysis consists of the identification, assessment, monitoring, and control of potential failure modes specific to the injection process applied to veneer trim parts. Based on the Ishikawa diagram, potential failure modes, effects, and causes of failure can be determined. The assessment results show that the potential risks are mostly located in the medium and high zones. By implementing corrective action, the process is significantly improved, and the potential risks are located in the low and medium zones. From a qualitative point of view, the Pareto chart allows prioritization of the defects that appear for the analyzed manufacturing process. It can be noted that the first two types of identified defects represent 27% of the total defects. Full article

The automobile industry relies primarily on spot welding operations, particularly resistance spot welding (RSW). The performance and durability of the resistance spot-welded joints are significantly impacted by the welding quality outputs, such as the shear force, nugget diameter, failure mode, and the hardness of the welded joints. In light of this, the present study sought to determine how the aforementioned welding quality outputs of 0.5 and 1 mm thick austenitic stainless steel AISI 304 were affected by RSW parameters, such as welding current, welding time, pressure, holding time, squeezing time, and pulse welding. In order to guarantee precise evaluation and experimental analysis, it is essential that they are supported by a numerical model using an intelligent model. The primary objective of this research is to develop and enhance an intelligent model employing artificial neural network (ANN) models. This model aims to provide deeper knowledge of how the RSW parameters affect the quality of optimum joint behavior. The proposed neural network (NN) models were executed using different ANN structures with various training and transfer functions based on the feedforward backpropagation approach to find the optimal model. The performance of the ANN models was evaluated in accordance with validation metrics, like the mean squared error (MSE) and correlation coefficient (R²). Assessing the experimental findings revealed the maximum shear force and nugget diameter emerged to be 8.6 kN and 5.4 mm for the case of 1–1 mm, 3.298 kN and 4.1 mm for the case of 0.5–0.5 mm, and 4.031 kN and 4.9 mm for the case of 0.5–1 mm. Based on the results of the Pareto charts generated by the Minitab program, the most important parameter for the 1–1 mm case was the welding current; for the 0.5–0.5 mm case, it was pulse welding; and for the 0.5–1 mm case, it was holding time. When looking at the hardness results, it is clear that the nugget zone is much higher than the heat-affected zone (HZ) and base metal (BM) in all three cases. The ANN models showed that the one-output shear force model gave the best prediction, relating to the highest R and the lowest MSE compared to the one-output nugget diameter model and two-output structure. However, the Levenberg–Marquardt backpropagation (Trainlm) training function with the log sigmoid transfer function recorded the best prediction results of both ANN structures. Full article

This study optimized the input processing factors, namely compression force, pressing speed, heating temperature, and heating time, for extracting oil from desiccated coconut medium using a vertical compression process by applying a maximum load of 100 kN. The samples’ pressing height of 100 mm was measured using a vessel chamber of diameter 60 mm with a plunger. The Box–Behnken design was used to generate the factors’ combinations of 27 experimental runs with each input factor set at three levels. The response surface regression technique was used to determine the optimum input factors of the calculated responses: oil yield (%), oil expression efficiency (%), and energy (J). The optimum factors’ levels were the compression force 65 kN, pressing speed 5 mm min⁻¹, heating temperature 80 °C, and heating time 52.5 min. The predicted values of the responses were 48.48%, 78.35%, and 749.58 J. These values were validated based on additional experiments producing 48.18 ± 0.45%, 77.86 ± 0.72%, and 731.36 ± 8.04 J. The percentage error values between the experimental and the predicted values ranged from 0.82 ± 0.65 to 2.43 ± 1.07%, confirming the suitability of the established regression models for estimating the responses. Full article

The parallel reservoirs in the upper reach of the Hanjiang River are key projects for watershed management, development, and protection. The optimal operation of parallel reservoirs is a multiple-stage, multiple-objective, and multiple-decision attributes complex decision problem. Taking Jiaoyan–Shimen parallel reservoirs as an example, a method of multi-objective optimal operation decision of parallel reservoirs (MOODPR) was proposed. The multi-objective optimal operation model (MOOM) was constructed. The new algorithm coupling NSGA-II, TOPSIS, and GCA was used to solve the MOODPR problem. The method of MOODPR was formed by coupling problem identification, model construction, an optimization solution, and scheme evaluation. The results show that (1) combining the Euclidean distance with the grey correlation degree to construct a new hybrid closeness degree makes the multi-attribute decision making method more scientific and feasible. (2) The NSGA-II-TOPSIS-GCA algorithm is applied to obtain decision schemes, which provide decision support for management. (3) It can be seen from the Pareto chart that for the Jiaoyan–Shimen parallel reservoirs, the comprehensive water supply was negatively related to ecology. (4) The comprehensive water supply and ecological AAPFD value in the extraordinarily dry year was 4.212 × 10⁸ m³ and 4.953. The number of maximum continuous water shortage periods was 4 and 6. The maximum ten-day water shortage was 4.46 × 10⁷ m³ and 2.3 × 10⁶ m³. The research results provide technical support and reference value to multi-objective optimal operation decisions for parallel reservoirs in the upper reach of the Hanjiang River. Full article

The ever-increasing use of motor vehicles causes a number of traffic safety and community issues, which are particularly severe in cities, accompanied by a scarcity of parking spaces and challenges encountered in road layout alteration projects. The commonly applied solutions include the designation of through streets, the implementation of on-street parking on residential streets, and retrofitted traffic calming measures (TCMs). This article presents the results of the study conducted on a two-way street where the Metered Parking System (MPS) was implemented together with diagonal and parallel parking spaces, refuge islands, horizontal deflection, and lane narrowing by a single-sided chicane. The aim of this study was to identify those TCMs that effectively helped to reduce the island approach speed. The heuristic method was applied to assess the effect of the respective TCMs on reducing the island approach speed, and the key speed reduction determinants were defined using a cause-and-effect diagram and a Pareto chart. The determinants were evaluated with the binary system and tautological inference principles, whereby a determinant was rated as true when it was found in the field, with a simultaneous speed reduction determined in the survey. Determinants that were not confirmed in the field were rated untrue. Comparative analyses were carried out to rate the respective TCMs as effective, moderately effective, or ineffective. In this way, the following three determinants were rated as the most important for speed reduction at refuge islands: free view, visibility of a pedestrian on the right-hand side of the island, and the refuge island surroundings. Although the study was limited to a single street in Poland, the findings may hold true in other countries where similar TCMs are used. Full article

The findings from Pareto charts, main effect plots, and interaction plots demonstrate the importance of polymer concentration. Increasing concentration improves the inhibition percentage and decreases the MIC₅₀. However, the primary factor that influences these changes is chitosan (CS). Additionally, the interaction between CS and PVP, along with other polymers, plays a crucial role in achieving better antimicrobial effects. These results enhance our understanding of the antimicrobial properties of the studied polymers and offer valuable insights for developing effective antimicrobial formulations. The MIC₅₀ value of M1–M16 was at a polymer percentage of 12.5%. At 12.5% polymer percentage, with the limits of [PVA], [PEG], and [PVP] being 0.002–0.004 g/mL and [CS] being 0.001–0.002 g/mL, using the 2-level full factorial method, the inhibition percentage is equal to 174.1 − 27,812 PVA − 18,561 PVP − 25,960 PEG − 38,752 CS + 9,263,047 PVA*PVP + 10,430,763 PVA*PEG + 15,397,157 PVA*CS + 7,088,313 PVP*PEG + 7,841,221 PVP*CS + 14,228,046 PEG*CS − 3,367,292,860 PVA*PVP*PEG − 5,671,998,721 PVA*PVP*CS − 6,619,041,275 PVA*PEG*CS − 3,917,095,529 PVP*PEG*CS + 2,273,661,969,470 PVA*PVP*PEG*CS. Theoretically, the most economical concentrations of PVA, PVP, PEG, and CS are 0.002, 0.002, 0.002, and 0.001 mg/mL at a concentration of 12.5% to reach an inhibition percentage of 99.162%, which coincides with the MBC value. Full article

In recent years, fused deposition modeling (FDM) based on material extrusion additive manufacturing technology has become widely accepted as a cost-effective method for fabricating engineering components with net-shapes. However, the limited exploration of the influence of FDM process parameters on surface roughness parameters, i.e., Ra (average surface roughness), Rq (root mean square surface roughness), and Rz (maximum height of the profile) across different sides (bottom, top, and walls) poses a challenge for the fabrication of functional parts. This research aims to bridge the knowledge gap by analyzing surface roughness under various process parameters and optimizing it for nylon carbon fiber printed parts. A definitive screening design (DSD) was employed for experimental runs. The Pareto chart highlighted the significant effects of layer height, part orientation, and infill density on all surface roughness parameters and respective sides. The surface morphology was analyzed through optical microscopy. Multi-response optimization was performed using an integrated approach of composited desirability function and entropy. The findings of the present study hold significant industrial applications, enhancing the quality and performance of 3D printed parts. From intricate prototypes to durable automotive components, the optimized surfaces contribute to production of functional and visually appealing products across various sectors. Full article

In the present study, the recovery of valuable molecules of proven anti-inflammatory and antimicrobial activity of the acidophilic microalga Coccomyxa onubensis (C. onubensis) were evaluated using green technologies based on ultrasound-assisted extraction (UAE). Using a factorial design (3 × 2) based on response surface methodology and Pareto charts, two types of ultrasonic equipment (bath and probe) were evaluated to recover valuable compounds, including the major terpenoid of C. onubensis, lutein, and the antimicrobial activity of the microalgal extracts obtained under optimal ultrasound conditions (desirability function) was evaluated versus conventional extraction. Significant differences in lutein recovery were observed between ultrasonic bath and ultrasonic probe and conventional extraction. Furthermore, the antimicrobial activity displayed by C. onubensis UAE-based extracts was greater than that obtained in solvent-based extracts, highlighting the effects of the extracts against pathogens such as Enterococcus hirae and Bacillus subtilis, followed by Staphylococcus aureus and Escherichia coli. In addition, gas chromatography–mass spectrometry was performed to detect valuable anti-inflammatory and antimicrobial biomolecules present in the optimal C. onubensis extracts, which revealed that phytol, sterol-like, terpenoid, and even fatty acid structures could also be responsible for the antibacterial activities of the extracts. Moreover, UAE displayed a positive effect on the recovery of valuable molecules, improving biocidal effects. Our study results facilitate the use of green technology as a good tool in algal bioprocess engineering, improving energy consumption and minimizing environmental impacts and process costs, as well as provide a valuable product for applications in the field of biotechnology. Full article