Search

This paper proposes an interpretation methodology for the effect of transient process data on quality of injection molded parts. The transient process data measured in the actual processing space have been regarded as the most relevant information to manufacturing processes and product quality. However, its interpretation to pinpoint which feature in the data would affect part quality has traditionally relied on knowledge and understanding of the manufacturing process. The main objective of this method is to reduce the dependency of the transient process data analysis on process knowledge and understanding by using explainable artificial intelligence (XAI). The contribution of the 'section-wise' features in the transient process data to the quality prediction of machine learning (ML) models was investigated for the first time. The interpretation results of the effect of cavity pressure and mold surface temperature on four different quality factors represented reasonable explanations of the characteristics of the polymer materials, product geometry, and molding process. Due to the intermediate relationship of the transient process data with the user-specified process parameters and the resulting quality variables, the interpretation results can be further utilized to optimize the process and provide the optimal transient process data profile for best part quality. [ABSTRACT FROM AUTHOR]

With a growing global awareness of the ecological challenges posed by plastic waste, the integration of recycled materials represents a crucial step to sustainable additive manufacturing of plastic products. To assess the applicability of recycled materials in 3D printing, we extruded recycled polylactic acid (PLA) into filament and printed specimens based on the fused filament fabrication (FFF) printing technology. For comparison purposes, we selected the virgin PLA filament as a reference. With the filament extruder, we produced filaments using virgin PLA pellets, a mixture of virgin pellets and recycled PLA, as well as fully recycled PLA. The extrudability and transferability of filaments were comprehensively investigated under various extrusion temperatures and speeds. Subsequently, using extruded filaments, we printed parts of different shapes such as cubes, tensile specimens, and flexural specimens. We measured the surface roughness, dimensional deviations, and mechanical properties of the printed parts. Results demonstrated that filament extruded from virgin pellets exhibited similar quality and mechanical properties as the virgin filament. Recycled PLA required higher extrusion temperature and speed to extrude filament than virgin PLA and mixed virgin PLA and recycled PLA. The tensile and flexural strength of printed parts from fully recycled PLA were more than 15 % lower than that from virgin filament. These findings contribute valuable insights towards the continued development of environmentally conscious practices in the field of additive manufacturing. [ABSTRACT FROM AUTHOR]

Microplastic (MP) release into the terrestrial environment has occurred since humans started manufacturing and using plastics. These tiny plastic particles can be found in various media, including the atmosphere, soil, freshwater, sediments, and organisms. MPs migrate through terrestrial environmental media due to wind, water, gravity, and biological processes. Although the variables that affect the migration process have been investigated in various settings, the mechanisms of MP migration in terrestrial environments have yet to be systematically characterized. This study classifies the migration mechanisms of MPs as physical, chemical and biological manners, and discusses the factors affecting migration mechanisms in dynamic factors, environmental factors and MP characteristics. Examining the action mechanisms of migration can establish a foundation for understanding the migration processes of MPs and provide a theoretical framework for modeling MP movement in environmental. Future research challenges include understanding the effect of MP characteristics in the migration process and simulating the migration of MPs in the environment in the long-term. Exploring the MP migration on various spatial and temporal scales, considering the life cycle of MPs is a worthy research direction. [ABSTRACT FROM AUTHOR]

Endocrine‐disrupting chemicals (EDCs) are synthetic compounds that can cause abnormalities in the functioning of the endocrine system of the human being, resulting in various health problems. Bisphenol‐A (BPA) is one of the important EDCs that is used in the manufacturing of plastics, food packaging canisters, and other day‐to‐day necessities. Since BPA is estrogenic in nature; its presence can affect the living component at a very low concentration. BPA and other EDCs are released from various sources like the plastic manufacturing industry, sewage treatment plants, and solid waste disposal points. Due to its global use, BPA has permeated different matrices, including our food sources. As a result, many adverse health effects have been reported, considering which, their treatment is necessary. Under the present investigation, we have reviewed various studies dealing with the sources, concentrations, and impact of BPA on the environment. In addition, we have also incorporated different treatment technologies including phytoremediation and bioremediation which can remove BPA effectively. Regardless of significant developments in our understanding of EDCs, uncertainties and knowledge gaps still occur and more studies are required to eradicate the problems of BPA contamination from our environment. [ABSTRACT FROM AUTHOR]

Manufacturers often blame environmental issues on consumer behaviors. Plastic manufactures provide a classic example, engaging in marketing campaigns attributing responsibility for plastic waste to consumers and deflecting attention from the role of industry. Drawing on attribution theory, we conducted an experiment (n = 113) to test how messaging blaming consumers for plastic waste might influence attitudes, behavioral intentions, and policy support, compared to messaging blaming manufacturers. Compared with the manufacturerblaming frame, the consumer-blaming frame resulted in less support for regulations increasing consumer accountability for plastic waste. We did not find a significant influence of the message frame on support for regulations holding manufacturers accountable for plastic waste. Based on these results, we suggest that practitioners consider framing messages surrounding plastic waste so as to minimize consumer blame in order to maximize potential support for plastic waste reduction initiatives. [ABSTRACT FROM AUTHOR]

This research deals with the parallel machine scheduling problem for identical machines that need additional operational resources during the changeover. The production strategy is mainly based on make-to-stock. When the current inventory is less than the quantity of the new order, the corresponding products will be scheduled for production in predetermined production batches that are larger than the quantity of the order. Because the additional resources are limited, batch splitting, which increases the number of changeovers, is not permitted. The objective is to minimize both the makespan and total tardiness. A two-phase methodology is proposed. In the first phase, a mixed-integer program is developed to minimize the makespan. The resulting minimal makespan becomes the constraint in the second phase. An extended mixed-integer program is then developed to minimize the total tardiness. A case study of a plastic pallet manufacturing company is introduced. The experimental results show that the proposed methodology can minimize the makespan and total tardiness efficiently. Moreover, it also shows the promise of the proposed methodology for solving practical applications. [ABSTRACT FROM AUTHOR]

Weld line defects, commonly occurring during the plastic product manufacturing process, are caused by the merging of two opposing streams of molten plastic. The presence of weld lines harms the product's aesthetic appeal and durability. This study uses artificial neural networks to forecast the ultimate tensile strength of a PA6 composite incorporating 30% glass fibers (GFs). Data were collected from tensile strength tests and the technical parameters of injection molding. The packing pressure factor is the one that significantly affects the tensile strength value. The melt temperature has a significant impact on the product's strength as well. In contrast, the filling time factor has less impact than other factors. According to the scanning electron microscope result, the smooth fracture surface indicates the weld line area's high brittleness. Fiber bridging across the weld line area is evident in numerous fractured GF pieces on the fracture surface, which enhances this area. Tensile strength values vary based on the injection parameters, from 65.51 MPa to 73.19 MPa. In addition, the experimental data comprise the outcomes of the artificial neural networks (ANNs), with the maximum relative variation being only 4.63%. The results could improve the PA6 reinforced with 30% GF injection molding procedure with weld lines. In further research, mold temperature improvement should be considered an exemplary method for enhancing the weld line strength. [ABSTRACT FROM AUTHOR]

The commercial use of polymers has expanded considerably in recent decades, resulting in exponential expansion in the polymer production business. As a result, polymer recycling is critical to the circular economy's sustainability. Governments and organizations are making significant efforts to reduce the carbon footprint generated by the use of synthetic polymers. Organizations such as the United Nations routinely launch initiatives worldwide to educate people and limit plastic manufacture. UNEP aims to reduce plastic output by 80% by 2040 by establishing a circular economy between the production and use of plastic. The manufacturing industry likewise takes huge steps to lessen its reliance on plastic. The industry is developing new ways and technologies to recycle these polymers sustainably. This paper studies and examines waste thermoplastic and thermoset material recycling initiatives made by other researchers. Various forms of recycling, primary, secondary, thermal, chemical, and biological are explored along with the sustainability of that particular recycling technique. [ABSTRACT FROM AUTHOR]

The copper mold of the micro-triangular pyramid (MTP) is a key component of MTP plastic film manufacturing, and its optical functional surface comprises micro-triangular pyramid arrays (MTPAs). The edge burrs of MTPAs severely affect the optical properties of MTP plastic film. To solve the problem of excessive edge burr of MTPA machining using the fly-cutting method, the orthogonal experimental method was used to optimize the four influencing factors: fly-cutting speed, feed speed, cutting depth, and cooling mode. The results show that the impact of these influencing factors on surface roughness, the projected area of the exit edge burr, and exit edge burr thickness are ranked from largest to the smallest as follows: fly-cutting speed, feed speed, cutting depth, and cooling mode. The factors affecting tool nose wear in descending order are fly-cutting speed, feed speed, cooling mode, and cutting depth. The optimal conditions for minimizing the thickness of the edge burr were a fly-cutting speed of 7.85 m/s, a feed speed of 50 mm/min, a finishing cutting depth of 15 μm, and using compressed air with oil mist for cooling. This study lays a foundation for improving the anti-reflection performance of MTP plastic film. [ABSTRACT FROM AUTHOR]

In this study, the authors performed a strength analysis of seven groups of commercially available materials based on SLS incremental technology. Test samples were made with Original PRUSA SL1S printers, with 10 samples of each type from 7 resins selected for testing. The tests were carried out on an MTS Bionix machine in a static tensile test, during which the basic mechanical properties were determined. This is also a preliminary study to determine material constants in the Johnson-Cook strength model. The authors then performed numerical simulations to mirror the experimental tests in order to tune the rheological model. In addition, a fracture criterion was determined based on a hybrid FEM/SPH numerical method. This allowed for the expansion of material libraries currently used in numerical simulations, as well as the sensitivity of the materials' models. In subsequent studies, in order to determine the nature of material destruction, analysis of fracture surfaces was performed using a scanning electron microscope (SEM). The final study was a biocompatibility test to assess the biological properties of the material. The conducted research made it possible to determine the strength properties of resins currently used in 3D printers, expand the libraries of material models in the computational environment (with an error rate of less than 5%), as well as observe the nature of the cracks formed and biocompatibility in the context of predicting the use of these materials for biomedical applications. [ABSTRACT FROM AUTHOR]

This paper presents a comprehensive approach aimed at developing a coupled process-structure simulation that integrates anisotropic and elastoplastic material behavior for plastic components manufactured through Fused Filament Fabrication (FFF) 3D printing. The simulation incorporates material orientation considerations, linking the process simulation with structural simulation. Subsequently, stress and strain values from the simulations are compared with the test results. Moreover, the fracture behavior of components manufactured in this way is also taken into account in relation to material orientation. The executed simulations have yielded successful outcomes, affirming the efficacy of the anisotropic and elastoplastic simulation across all strand orientations. Special attention is paid to the application of the method. Here, the simulation method introduced in this contribution with the approaches for describing the material behavior under mechanical load can be used in the future in the dimensioning of FFF manufactured plastic components to predict the deformation behavior and failure, especially under consideration of a well economic and efficient virtual product development. [ABSTRACT FROM AUTHOR]

Fluorene-9-bisphenol (BHPF) is widely used in the manufacture of plastic products and potentially disrupts several physiological processes, but its biological effects on social behavior remain unknown. In this study, we investigated the effects of BHPF exposure on anxiety-like and social behavior in female mice and the potential mechanisms, thereby proposing a potential therapy strategy. We exposed female Balb/c mice to BHPF by oral gavage at different doses (0.5, 50 mg/kg bw/2-day) for 28 days, which were found BHPF (50 mg/kg) exposure affected motor activity in the open field test (OFT) and elevated cross maze (EPM), resulting in anxiety-like behaviors, as well as abnormal social behavioral deficits in the Social Interaction Test (SIT). Analysis of histopathological staining results showed that BHPF exposure caused damage to hippocampal neurons in the CA1/CA3/DG region and decreased Nissl pyramidal neurons in the CA1/CA3 regions of the hippocampus, as well as a decrease in parvalbumin neuron expression. In addition, BHPF exposure upregulated the expression of excitatory and inhibitory (E/I) vesicle transporter genes (Vglut1, Vglut2, VGAT, GAD67, Gabra) and axon growth gene (Dcc) in the mouse hippocampus. Interestingly, behavioral disturbances and E/I balance could be alleviated by exogenous melatonin (15 mg/kg bw/2-day) therapy. Our findings suggest that exogenous melatonin may be a potential therapy with protective potential for ameliorating or preventing BHPF-induced hippocampal neuronal damage and behavioral disturbances. This study provided new insight into the neurotoxicological effects on organisms exposed to endocrine-disrupting chemicals and aroused our vigilance in current environmental safety about chemical use. [ABSTRACT FROM AUTHOR]

Sustainable development goals (SDGs) issued by the United Nations (UN) have been recognized as the aims for sustainable development of the global economy and companies around the world. In realizing SDGs, social responsibility accounting (SRA) is gradually proving to be an effective quantification tool to enhance transparency and reliability in the social responsibility reports of companies. Therefore, this study aims to evaluate impact factors on SRA in Vietnamese plastics companies, an environmentally sensitive industry. We used a large-scale survey and collected 160 respondents from plastic manufacturing enterprises in the Hanoi area, Vietnam. It is found that three factors, namely, stakeholder pressure, awareness of business managers, and characteristics of plastic enterprises, have positive impacts on the application of SRA in plastic enterprises. Meanwhile, the environmental cost factor hinders the application of SRA. Thereby, the research makes recommendations for plastic manufacturing enterprises in an emerging country like Vietnam on how to best apply SRA to further the SDGs. [ABSTRACT FROM AUTHOR]

In a scenario characterised by mitigation concerns and calls for greater resilience in the energy sector, energy audits (EAs) emerge as an essential mean for enhancing end-use energy consumption awareness and efficiency. Such a tool allows us to assess the different energy carriers consumed in a productive sector, offering insight into existing energy efficiency improvement opportunities. This opens avenues for research to devise an econometrics-based methodology that encapsulate production sites and their environmental essentials. This paper contributes to the literature by exploiting the EAs received by the Italian National agency for New technologies, Energy, and Sustainable Economic Development (ENEA) in 2019 from the Italian plastics manufacturing sector, matched with Italian firm-based data extracted from the Analisi Informatizzata delle Aziende Italiane (Italian company information and business intelligence) (AIDA) database. In particular, we investigate how the implementation of energy efficiency measures (EEMs) is influenced by a set of contextual factors, as well as features relating to the companies and EEMs themselves. The empirical investigation focuses on the EAs submitted to ENEA in 2019, which was strategically chosen due to its unique data availability and adequacy for extensive analysis. The selection of 2019 is justified as it constitutes the second mandatory reporting period for energy audits, in contrast to the 2022 data, which are currently undergoing detailed refinement. In line with the literature, the adopted empirical approach involves the use of both the OLS and logistic regression models. Empirical results confirm the relevance of economic and financial factors in guiding the decisions surrounding the sector's energy performance, alongside the analogous influence of the technical characteristics of the measures themselves and of the firms' strategies. In particular, the OLS model with no fixed effects shows that a one-percent variation in investments is associated with an increase in savings performance equal to 0.63%. As for the OLS model, including fixed effects, the elasticity among the two variables concerned reaches 0.87%, while in the logistic regression, if the investment carried out by the production sites increases, the expected percentage change in the probability that the energy-saving performance is above its average is about 187.77%. Contextual factors that prove to be equally influential include the incentive mechanism considered and the traits of the geographical area in which the companies are located. Relevant policy implications derived from this analysis include the importance of reducing informational barriers about EEMs and increasing technical assistance, which can be crucial for identifying and implementing effective energy solutions. [ABSTRACT FROM AUTHOR]

Response surface methodology (RSM) is employed to reduce air trap in the thin small outline package (TSOP) manufactured via plastic transfer molding by adjusting the process parameter. The study aims to evaluate the key factors and interactions in transfer molding process parameters of integrated chip (IC) encapsulation. A three-level central composite design (CCD) approach–based response surface methodology analysis was applied to statistically specify the effect of important numerical and categorical process variables (i.e., melt and mold surface temperature, curing time, and runner layout) on the key response process output variables of air trap and curing level. By using this rotatable design, a total of 60 simulation data was fitted. The significance of the factors and their interactions were verified by using the analysis of variance (ANOVA) with a 95% confidence level (p < 0.05). The empirical models were computed and thoroughly validated against the simulation results. The optimum process parameters of the TSOP IC package were characterized as follows: melt temperature of 88.09℃, 181.99℃ of mold surface temperature, the 60 s of curing time, and Herringbone type of cavity layout. The results herein could contribute significantly as a reference and further understanding of the optimization process to advancing microelectronic industries. [ABSTRACT FROM AUTHOR]

Spline connection is a key component for force- and torque-transmission, which is widely used in mechanical engineering. External splines in spline connection have been manufactured by rolling process, but the matched inner splines manufactured by plastic deformation are few. Especially, the long inner spline is usually manufactured by cutting process. The rolling process is a plastic forming process with local loading and force saving; so, this study investigated the rolling process and its implementing way for inner spline sleeve. A radial-feed rolling process and two through-feed rolling processes with different structure of entry-angle section were proposed, and the finite element (FE) models were established for different rolling process, respectively. For the FE model of the through-feed rolling process, a multiple meshing strategy is used such as the local refinement window moving along axial direction with rolling die and the total number of mesh increasing by stages. The results indicated that the contact area is the same along axial direction and increases in situ during radial-feed rolling process, but the contact area changes and moves along axial direction during through-feed rolling process; the full and clear shape of inner spline can be obtained by the three rolling processes, but the shapes near the end of expected zone with inner spline are different for the different processes, and the geometry near the end of billet and the rolling process have the influence on the shapes near the end; some metal is accumulated in front of the through-feed rolling die, so non-full teeth present in the entered end by the rolling die and full teeth in the exited end will be out of the expected zone with inner spline. [ABSTRACT FROM AUTHOR]

Void fraction and fiber volume fraction (FVF) are among the most important parameters determining the quality of fiber‐reinforced plastic products. Most of the voids in liquid composite molding–manufactured composites are directly related to the viscous matrix (resin) flow through the porous medium (fiber) during impregnation. In this investigation, a different method, resin spray rather than injection was used to reduce the resin's flow path, which resulted in low void content and higher FVF. The resin was sprayed on the surface of the preform, and compaction was applied to infiltrate the resin towards the thickness. Sample laminates were manufactured, and computer tomography scanning was applied to diagnose void content and laminae quality. The images collected from the scanner were analyzed using ImageJ software. Effects of compaction pressure and compaction speed were characterized. According to the investigation, compaction speed was the key factor in determining a laminate's void content. Only 1.5% void fraction was integrated with a compaction speed of 1 mm/min and a compaction pressure of 100 KPa. On the other hand, compaction speed has less of an impact on a laminate's FVF. Highlights: The void fraction of a composite is reduced via the spray and compaction method.Fiber volume fraction is not much affected by compaction speed.Slow compaction speeds minimize void content.Spray compaction is a low‐cost manufacturing method. [ABSTRACT FROM AUTHOR]

This research integrates machine learning (ML) and Six Sigma's Define, Measure, Analyze, Improve, and Control (DMAIC) methodology to address these issues. The study details the selection and utilization of ML techniques, including Linear Regression (LR), Artificial Neural Network (ANN), Decision Tree (DT), K-nearest neighbors (KNN), and Cluster Analysis (CA). Implemented at the Innovative Plastic Manufacturing Company in Egypt, this research enhances the consistency of plastic bottle production by addressing issues such as surface marks, flashes, bubbles, and variations in liter capacity. Integrating Six Sigma with ML techniques reduces the average defect rate from approximately 67.8%. It elevates the Sigma level from 3.14 to 4.30, reducing material over-consumption costs from 5% to 1.7% of total manufacturing expenses. Notably, the KNN model achieves the best results for defect testing, with an R-squared value of 98.8%. These methodologies lead to cost reduction, increased competitiveness, and improved product quality when implemented. [ABSTRACT FROM AUTHOR]

High‐density polyethylene (HDPE) polymer is one of the largest contributors to plastic wastes causing detrimental effects on various sectors of society, and is not biodegradable in nature. In the first stage, river sand and a recycled HDPE as a binder were used to manufacture eco‐friendly plastic sand bricks with various sand(s):plastic(p) ratios: 60s:40p; 65s:35p; 70s:30p; 75s:25p; 80s:20p; 85s:15p. In the second stage, 1%, 5%, and 10% of Kaolin Clay was added to each ratio of sand:plastic, respectively. Three mechanical tests were conducted: compressive strength, impact, and short beam strength. First, the addition of 5% Kaolin Clay to 75s:25p ratio increased compressive strength significantly from 21.4 to 52.76 MPa. Second, the addition of 10% Kaolin Clay in the ratio of 75s:25p mixture increased the impact strength from 4.8 to 5 J. Finally, the addition of 5% Kaolin Clay in the ratio of 60s:40p mixture increased the short beam strength significantly from 1.84 to 2.27 MPa. SEM analysis showed a well‐compacted interface indicating effective bonding between the HDPE and river sand particles in the 75s:25p ratio. Hence, the results of this study present a potential for the use of recycled HDPE plastic to manufacture plastic sand bricks. Highlights: Addition of Kaolin Clay improved the mechanical properties of the composite material. [ABSTRACT FROM AUTHOR]

Plastic granules are a common delivery form for creating products in industries such as the plastic manufacturing, construction and automotive ones. In the corresponding sorting process of plastic granules, diverse defect types could appear. Burn marks, which potentially lead to weakened structural integrity of the plastic, are one of the most common types. Thus, plastic granules with burn marks should be filtered out during the sorting process. Artificial intelligence (AI)-based anomaly detection approaches are widely used in the field of visual-based sorting due to the higher accuracy and lower requirement of expert knowledge compared with classic rule-based algorithms (Chandola et al., 2009). In this contribution, a simple data augmentation strategy, cutout, is implemented as a way of simulating defects when combined with a contrastive learning-based methodology and is proven to improve the accuracy of the anomaly detection of burn marks. Different variants of cutout are also evaluated. Specifically, synthetic image data are used due to the lack of real data. [ABSTRACT FROM AUTHOR]

Phthalates constitute a family of anthropogenic chemicals developed to be used in the manufacture of plastics, solvents, and personal care products. Their dispersion and accumulation in many environments can occur at all stages of their use (from synthesis to recycling). However, many phthalates together with other accumulated engineered chemicals have been shown to interfere with hormone activities. These compounds are also in close contact with microorganisms that are free-living, in biofilms or in microbiota, within multicellular organisms. Herein, the activity of several phthalates and their substitutes were investigated on the opportunistic pathogen Legionella pneumophila, an aquatic microbe that can infect humans. Beside showing the toxicity of some phthalates, data suggested that Acetyl tributyl citrate (ATBC) and DBP (Di-n-butyl phthalate) at environmental doses (i.e. 10–6 M and 10–8 M) can modulate Legionella behavior in terms of motility, biofilm formation and response to antibiotics. A dose of 10–6 M mostly induced adverse effects for the bacteria, in contrast to a dose of 10–8 M. No perturbation of virulence towards Acanthamoeba castellanii was recorded. These behavioral alterations suggest that L. pneumophila is able to sense ATBC and DBP, in a cross-talk that either mimics the response to a native ligand, or dysregulates its physiology. [ABSTRACT FROM AUTHOR]

This study presents a novel hybrid optimization approach for intelligent manufacturing in plastic injection molding (PIM). It focuses on globally optimizing process parameters to ensure high-quality products while reducing cycle time, material waste, and energy consumption. The method combines a backpropagation neural network (BPNN) with a genetic algorithm (GA) and employs a multi-objective optimization model based on design of experiments (DoE). A BP artificial neural network captures the relationship between optimization goals and process parameters. Leveraging the genetic algorithm, it effectively optimizes process parameters for achieving global optimization goals. The case study involves a polypropylene product, considering dimensional deviation, weight, cycle time, and energy consumption during the PIM cycle. Design variables include melt temperature, injection velocity, injection pressure, commutation position, holding pressure, holding time, and cooling time. The results demonstrate that this approach efficiently adjusts process parameters to meet quality standards, significantly reducing raw material consumption (2%), cycle time (12%), and energy consumption (16%). This offers substantial benefits for companies in highly competitive markets demanding swift adoption of smart production methods. [ABSTRACT FROM AUTHOR]

The purpose of this study is to empirically evaluate the model that explains the methods involved in the transformation of environmental strategic capabilities (ESC) into environmental strategic performance (ESP) of manufacturing SMEs in developing economies such as Pakistan. This study also analyzes the role of environmental strategic assessment (ESA) as a mediator as well as the contingent impacts of stakeholder engagement (SE). To evaluate the conceptual model, a cross-sectional design was employed in this study. Data from 489 owners, production managers, finance managers, and CEOs of 133 production units dealing in agriculture equipment (31 units), auto parts (18 units), electrical equipment (25 units), gas appliances (23 units), pharmaceutical instruments (15 units), and plastic products manufacturing (21 units) was gathered to validate the moderated mediation framework. The outcomes of the study support the notion that ESC and ESP are positively correlated. Furthermore, results also support the mediation role of ESA in the association between ESC and ESP. Additionally, the moderation of SE is validated, and this construct is portrayed as a catalyst in interaction of ESC and ESP. The current study contributes to strategic management literature by concentrating on intangible assets such as ESC and its key aspects. As a result, it introduces a new framework as well as a roadmap that will support the accomplishment of ESP. Through focusing on the mediating mechanism in which ESC may well be transformed to ESP of manufacturing SMEs by ESA, the study findings significantly contributed to the understanding of environmental dynamism in contemporary management era. The findings of the study also assist in clarifying the moderating impact of SE and how its interactions with ESC and ESP strengthen the influence that enterprises have on ESA. [ABSTRACT FROM AUTHOR]

Bisphenol A (BPA), a compound widely used in industrial applications, has raised concerns due to its environmental impact. As a key component in the manufacture of polycarbonate plastics and epoxy resins used in many consumer products, concerns about potential harm to human health and the environment are unavoidable. This study seeks to address these concerns by evaluating a range of potential BPA alternatives, focusing on their ecotoxicological properties. The research examines 76 bisphenols, including BPA derivatives, using a variety of in silico ecotoxicological models, although it should be noted that these models were not developed exclusively for this particular class of compounds. Consequently, interpretations should be made with caution. The results of this study highlight specific compounds of potential environmental concern and underscore the need to develop more specific models for BPA alternatives that will allow for more accurate and reliable assessment. [ABSTRACT FROM AUTHOR]

N6-methyladenosine (m6A) is a critical regulator in the fate of RNA, but whether and how m6A executes its functions in different tissues remains largely obscure. Here we report downregulation of a crucial m6A reader, YTHDF2, leading to tissue-specific programmed cell deaths (PCDs) upon fluorene-9-bisphenol (BHPF) exposure. Currently, Bisphenol A (BPA) substitutes are widely used in plastic manufacturing. Interrogating eight common BPA substitutes, we detected BHPF in 14% serum samples of pregnant participants. In a zebrafish model, BHPF caused tissue-specific PCDs triggering cardiac and vascular defects. Mechanistically, BHPF-mediated downregulation of YTHDF2 reduced YTHDF2-facilitated translation of m6A- gch1 for cardiomyocyte ferroptosis, and decreased YTHDF2-mediated m6A- sting1 decay for caudal vein plexus (CVP) apoptosis. The two distinct YTHDF2-mediated m6A regulations and context-dependent co-expression patterns of gch1/ythdf2 and tnfrsf1a/ythdf2 contributed to YTHDF2-mediated tissue-specific PCDs, uncovering a new layer of PCD regulation. Since BHPF/YTHDF2-medaited PCD defects were also observed in mammals, BHPF exposure represents a potential health threat. [ABSTRACT FROM AUTHOR]

This research addresses an inventory classification problem in a company that manufactures plastic pallets. Classification of the inventory is difficult because it is subject to two restrictions: the number of changeovers and the size of inventory storage. A mathematical model is first proposed to maximize the fill rate by classifying all product items into four groups. Due to all items can be classified based on the monthly demand, in descending order. The present study then proposed a procedure to find the classification that is most efficient. According to the experimental results, the maximum fill rate in the current situation is 89.85%. The proposed methodology also tested different production batches and levels of demand. The proposed methodology was found to be appropriate for practical application. [ABSTRACT FROM AUTHOR]

In this paper, we present an approach to efficiently optimize the design of extrusion dies. Extrusion dies, which are relevant to the manufacturing process of plastics profile extrusion, traditionally require time‐consuming iterations between manual testing and die adjustments. As an alternative, numerical optimization can be used to obtain a high quality initial design and thereby reduce the number of adjustments to the actual die. However, numerical optimization can be computationally expensive, so the use of surrogate models can be helpful to improve efficiency. The latter is the goal of this work. Our method uses physics‐informed neural networks (PINNs) that directly incorporate a free‐form deformation (FFD) approach to allow for geometric variations. The FFD approach allows for a wide range of domain deformations, while the fully trained PINN ensures fast evaluation of the objective function. Using a two‐dimensional model of an extrusion die for demonstration, we detail the integration of the FFD method into the PINN model and discuss its potential in the three‐dimensional context. [ABSTRACT FROM AUTHOR]

Injection molding is a widely used manufacturing technology for the mass production of plastic parts. Despite the importance of process optimization for achieving high quality at a low cost, process conditions have often been heuristically sought by field engineers. Here, we propose two systematic data-driven optimization frameworks for the injection molding process based on a multi-objective Bayesian optimization (MBO) framework and a constrained generative inverse design network (CGIDN) framework. MBO, an extension of Bayesian optimization, uses Gaussian process regression adopting a multidimensional acquisition function based on the concepts of hypervolume and Pareto front. The CGIDN, which is an improved version of the original generative inverse design network (GIDN), uses backpropagation to calculate the analytical gradients of the objective function with respect to design variables. Both methods can be used for multi-objective optimization with trade-off relationships, for example, between the cycle time and deflection after extraction. We demonstrate the applicability of the optimization methods utilizing simulation data from Moldflow software for the manufacturing process of a door trim part. We showed that the optimal process parameters which simultaneously minimized deflection and cycle time were obtained with a relatively small dataset. We expect that in a realistic manufacturing facility, the optimal conditions found from simulations can guide the process design of the injection molding machine, or the proposed methods can be directly utilized because they do not require a very large dataset. We also note that the proposed optimization schemes are readily applicable to the optimization of other types of plastic manufacturing processes. [ABSTRACT FROM AUTHOR]

Various kinds of plastics have been developed over the past century, vastly improving the quality of life. However, the indiscriminate production and irresponsible management of plastics have led to the accumulation of plastic waste, emerging as a pressing environmental concern. To establish a clean and sustainable plastic economy, plastic recycling becomes imperative to mitigate resource depletion and replace non-eco-friendly processes, such as incineration. Although chemical and mechanical recycling technologies exist, the prevalence of composite plastics in product manufacturing complicates recycling efforts. In recent years, the biodegradation of plastics using enzymes and microorganisms has been reported, opening a new possibility for biotechnological plastic degradation and bio-upcycling. This review provides an overview of microbial strains capable of degrading various plastics, highlighting key enzymes and their role. In addition, recent advances in plastic waste valorization technology based on systems metabolic engineering are explored in detail. Finally, future perspectives on systems metabolic engineering strategies to develop a circular plastic bioeconomy are discussed. [ABSTRACT FROM AUTHOR]

Cheesecloth used in cheese manufacturing has technical problems; provides low cheese yield and is difficult to clean and disinfect. The present study investigated the effect of substituting cheesecloth with multiple artificial polyamide plastic micro-filters (PPMFs) on the properties of fresh white boiled cheeses (FWBC) and pasteurized white brined cheeses (PWBC) and their whey. Whey was strained by either traditional cheesecloth (control; C) or by one of the PPMFs with different pore sizes (PPMF10, PPMF20, PPMF40, PPMF57 and PPMF 75). The yields of FWBC were 19.46%, 17.13 %, and 14.98% for PPMF10, PPMF20, and PPMF40, respectively. Slightly lower yields were obtained for the PWBC, and the control had the lowest yield (~11.1%). Using PPMFs with increased pore size in both cheeses reduced the total solids, fat, and protein contents. In the whey, reversed trends in the relationship were observed, indicating a loss of solids as fat and protein during the straining. Microbial analysis showed that PPMF cheeses had lower mesophilic aerobes and LAB counts than those of the control. Yeasts, molds, and Staphylococcus aureus were not detected (˂10 log cfu/g) in treatments or the control. In general, FWBC maintained lower microbial counts than PWBC, which was associated with the final boiling step in the FWBC. Cheesecloth maintained the highest microbial counts which would be indicative of the protective effect of cheesecloth on the bacterial cells and their spores. The customary cleaning procedure was not sufficient to eliminate microbial cells from the cheesecloth therefore could represent a source of contamination for cheeses. Acidity (as lactic acid) resulted from the growth of LAB, and PPMFs produced similar or better cheeses in terms of sensory analysis attributes compared to the control. [ABSTRACT FROM AUTHOR]

The EFSA Panel on Food Contact Materials, Enzymes and Processing Aids (CEP) assessed the safety of the recycling process Umincorp (EU register number RECYC302), which uses the NGR technology. The input consists of washed and dried poly(ethylene terephthalate) (PET) flakes mainly originating from collected post‐consumer PET containers, with no more than 5% PET from non‐food consumer applications. The flakes are dried (step 2), melted in an extruder (step 3) and decontaminated during a melt‐state polycondensation step ■■■■■ (step 4). In step 5, the melt is cooled down and granulated. Having examined the challenge test provided, the Panel concluded that the melt‐state polycondensation (step 4) is critical in determining the decontamination efficiency of the process. The operating parameters to control the performance are the pressure, the temperature, the residence time (depending on the mass and throughput of the melt) and the characteristics of the reactor. It was demonstrated by the challenge test that this recycling process is able to ensure that the level of migration of potential unknown contaminants into food is below the conservatively modelled migration of 0.1 μg/kg food. Therefore, the Panel concluded that the recycled PET obtained from this process is not of safety concern when used at up to 100% for the manufacture of materials and articles for contact with all types of foodstuffs, including drinking water, for long‐term storage at room temperature, with or without hotfill. The final articles made of this recycled PET are not intended to be used in microwave and conventional ovens and such uses are not covered by this evaluation. [ABSTRACT FROM AUTHOR]

This study is mainly focused to obtain stable dimensions for plastic products used in manufacturing industries. A technique of microcellular foaming injection method was chosen with added chemical blowing agents to decrease the mass, clamping force, and cycle time. Mold flow analysis was run to compare the conventional plastic injection (KP) method with chemical foaming injection molding method using added TecoCell H1 (TH) and CS (TCS). The primary process conditions are considered as temperature of the mold, velocity of injection, pressure and time of holding, and cooling time. The experiments were carried under polymer material as (polypropylene) Moplen EP548P. The new chemical blowing agents TH and TCS, having different reactive material ratios (50% and 25% endothermic) and gas concentration ratios, were utilized at a rate of 1% by weight claiming to be a novel method for producing the parts with high efficiency. The results of both the flow analysis and the injection molding experiments demonstrate that, plastic samples produced by conventional plastic injection could be made approximately 7.5% lesser weight, with 33% lesser force of clamping, and a gain of cycle time nearly 15% by adding chemical blowing agents to the process. Topsis technique is carried for determining the best fabrication method. It was observed that, the injection molding method with Tecocell H1 (TH) chemical foaming agent exhibited better results in terms of less clamping force, reduced cycle time, and weight of the product. The experimental results are validated using the Topsis method and the results are satisfied. Hence, the chemical blowing agent Tecocell H1 (TH) can be applied as a foaming agent for manufacturing the plastic products and increase the efficiency of the production. [ABSTRACT FROM AUTHOR]

Injection molding is a method commonly used to manufacture plastic products. This technology makes it possible to obtain products of specially designed shape and size. In addition, the developed mold allows for repeated and repeatable production of selected plastic parts. Over the years, this technology grew in importance, and nowadays, products produced by injection molding are used in almost every field of industry. This paper is a review and provides information on recent research reports in the field of modern injection molding techniques. Selected plastics most commonly processed by this technique are discussed. Next, the chosen types of this technique are presented, along with a discussion of the parameters that affect performance and process flow. Depending on the proposed method, the influence of various factors on the quality and yield of the obtained products was analyzed. Nowadays, the link between these two properties is extremely important. The work presented in the article refers to research aimed at modifying injection molding methods enabling high product quality with high productivity at the same time. An important role is also played by lowering production costs and reducing the negative impact on the environment. The review discusses modern injection molding technologies, the development of which is constantly progressing. Finally, the impact of the technology on the ecological environment is discussed and the perspectives of the process were presented. [ABSTRACT FROM AUTHOR]

Stress is a critical concern in manufacturing environments, as it impacts the well-being and performance of workers. Accurate measurement of stress is essential for effective intervention and mitigation strategies. This paper introduces a holistic and human-centered protocol to measure stress in manufacturing settings. The three-phased protocol integrates the analysis of physiological signals, performance indicators, and the human perception of stress. The protocol incorporates advanced techniques, such as electroencephalography (EEG), heart rate variability (HRV), galvanic skin response (GSR), and electromyography (EMG), to capture physiological responses associated with stress. Furthermore, the protocol considers performance indicators as an additional dimension of stress measurement. Indicators such as task execution time, errors, production rate, and other relevant performance metrics contribute to a comprehensive understanding of stress in manufacturing environments. The human perception of stress is also integrated into the protocol, recognizing the subjective experience of the individual. This component captures self-assessment and subjective reports, allowing for a more nuanced evaluation of stress levels. By adopting a holistic and human-centered approach, the proposed protocol aims to enhance our understanding of stress factors in manufacturing environments. The protocol was also applied in the automotive industry and plastic component manufacturing. The insights gained from this protocol can inform targeted interventions to improve worker well-being, productivity, and overall organizational performance. [ABSTRACT FROM AUTHOR]

The Kyrgyz Republic, as a developing country with a socialist past, has great opportunities for further economic development. An important factor to consider is the growth of the manufacturing industry, which highlights the significance of analyzing this sector within the country. This study centers on the potential contribution of the Eurasian Economic Union (EAEU), of which Kyrgyzstan is a constituent, towards the advancement of this industry. The research aimed to evaluate the current manufacturing capacity of the Kyrgyz Republic in the industrial sector and to comprehend the influence of the EAEU on industry growth. The main methods that were used during the writing of the research were analysis, forecasting, abstraction, and historical analysis. The work analyzed the industrial sector of Kyrgyzstan within the framework of its integration into the EAEU. The research assessed the historical background of Kyrgyzstan’s accession to the EAEU and the subsequent harmonization of national legislation with the provisions and requirements of the union. In addition, data comparing the industrial production and growth rates of Kyrgyzstan, Armenia, and Kazakhstan have been presented, highlighting notable trends and differences. The work examines specific components of the manufacturing industry of the Kyrgyz Republic, the manufacture of food, beverages, and tobacco products; rubber and plastic manufacture, and non-metallic mineral goods; manufacturing of basic metals and metal products (excluding machinery and equipment); and supply of electricity, gas, steam, and conditioned air. It also talks about the manufacturing sector's importance in Kyrgyzstan, current trends, and possible future improvements, and it enables the assessment of the country's involvement in the EAEU. [ABSTRACT FROM AUTHOR]

In this paper, production scheduling for rotomoulded plastics manufacturing in a multi-machine environment is considered. The objective is to minimise total tardiness. The problem has some commonality with hybrid flow shop scheduling with batching, where additional constraints are needed to control which machines may be used at each stage. The problem is shown to be NP-hard and is formulated as a mixed integer program. Given consequently large solve times to obtain optimal solutions, simulated annealing and tabu search algorithms were developed alongside a constructive heuristic to obtain near-optimal solutions within a practical time-frame. The solution algorithms were tuned and tested using randomly generated problem instances. The best results in terms of solution quality were generally obtained by simulated annealing. The problem instances were generated to be representative of a real production environment located in Queensland, Australia. [ABSTRACT FROM AUTHOR]

In this work, a soft sensor–based digital twin (DT) was developed to reduce the startup time in manufacturing plastic tubes and enable real-time product quality monitoring, i.e., the weight per unit length and the inner and outer diameters of the tube. An experimental campaign was conducted on a real tube extrusion line using three polyvinyl chloride (PVC) compounds and different process conditions, and machine learning regression algorithms were trained and tested to create the models of the extruder and the extrusion die the DT is based on. The characterization of the considered material, whose properties were given as input to the digital models, was carried out according to a procedure based only on the data collected by the production line. The DT was tested for the startup of the production of a single-layer tube and allowed to achieve the specified customer requirements (thickness and weight) in a few minutes. The proposed solution thus proved to be a valuable tool for reducing the setup time, thus increasing the efficiency of the process. [ABSTRACT FROM AUTHOR]

In Kampung Sanan Malang, designated as a tourist destination for small household-based industries, tempeh chips are its flagship product. The 636 tempeh artisans are from Sanan Malang Tempeh and Tempeh Chips Production Center Association. Members of this community have processed tempeh into 50 types of preparations like various flavors of tempeh chips, tempeh satay, mendol sticks, tempeh brownies cakes, dry tempeh, processed soybean stew to produce nata de soya, muffins, tempeh mud cakes, and bloeder cakes. The last innovation made in 2021 was named Character Tempeh. This new product is manufactured by utilizing a plastic mold. The problem is that no member of this community has been able to make their own desired shape of the character model, nor have they been able to make a more effective print. The solutions offered include making character models using plasticine and training in printing these models using food-grade RTV. At the end of this activity, artisans can produce processed character tempeh with unique and good quality so that it becomes a typical product of Sanan Malang. [ABSTRACT FROM AUTHOR]

Plastic is common material widely used all over the world. Plastic manufacturing crosses 150 million tonnes per year. Plastic is involved in all activities of human life. So, waste of plastics is also increasing gradually. This paper focuses on recycling waste plastic and making plastic composite construction material (PCCM) that include fine and coarse aggregate along with three types of waste plastic, i.e. high density polyethylene (HDPE), low density polyethylene, and polyethylene terephthalate. In this research, 27 mixes of plastic composite construction materials (PCCM) have been made, in which plastic is softened or melted up to a semi-liquid state with the help of used engine oil and mixed with aggregate. This material has been evaluated for various properties such as compressive strength, flexural strength, split tensile strength, density, and water absorption. HDPE with fine aggregate gives better results. [ABSTRACT FROM AUTHOR]