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The electronic control module is an important part of a digital electronic detonator, which undergoes a complex production process that includes three electrical performance tests and three visual inspection procedures. In each inspection procedure, several different types of data are generated daily, including numerical and categorical data. To evaluate the production quality of electronic control modules, an algorithm based on a Deep Belief Network with Multi-mutation Differential Evolution (MDE-DBN) is designed in this study. First, key indicators are extracted to construct a production quality evaluation index system. A Multi-mutation Differential Evolution algorithm is designed to optimize the initial network weights of the Deep Belief Network (DBN) and integrate the production quality information into the pre-training phase. Subsequently, the preprocessed experimental data are input into the MDE-DBN algorithm to obtain the distributions of excellent, general, and unqualified production statuses, verifying the effectiveness of the algorithm. The experimental results show that the MDE-DBN algorithm has significant advantages in evaluation accuracy when compared with DBNs improved by other intelligent optimization algorithms and machine learning methods. [ABSTRACT FROM AUTHOR]

【Objective】The effects of nitrogen fertilizer reduction on the growth and development, nutrient utilization, yield and quality of flue-cured tobacco were studied, and the feasibility of nitrogen fertilizer reduction was preliminarily clarified, which provided a theoretical basis for the sustainable production of flue-cured tobacco.【Method】Five treatments were set up, including no fertilization (control), conventional nitrogen application, 10% reduction of nitrogen fertilizer, 20% reduction of nitrogen fertilizer and 30% reduction of nitrogen fertilizer. The agronomic traits, economic traits, chemical composition and fertilizer utilization rate of tobacco plants in each treatment were compared and analyzed.【Result】An appropriate amount of nitrogen fertilizer reduction could shorten the growth period of flue-cured tobacco, and significantly increased the plant height, effective leaf number and maximum leaf width. In terms of chemical composition of tobacco leaves, the indexes of reducing sugar content, total nitrogen content and nicotine content of flue-cured tobacco leaves treated with nitrogen fertilizer reduction by 10% were all within the requirements of conventional chemical composition indexes of high-quality flue-cured tobacco in Yunnan. In terms of appearance quality of tobacco leaves, the color of flue-cured tobacco leaves treated with nitrogen fertilizer reduction of 10% and 20% was orange, the structure was loose or still loose, the oil was sufficient, and the appearance quality of tobacco leaves was better. In terms of nitrogen nutrient distribution, the nitrogen content of each part of tobacco plants showed the rule of leaf > stem > root, and the nitrogen content of tobacco leaves was significantly increased under the treatment of 10% nitrogen reduction. In terms of nitrogen use efficiency, after reducing nitrogen application by 10% and 20%, the nitrogen fertilizer utilization rate, agronomic efficiency and partial productivity of nitrogen fertilizer increased by 10.15%, 9.31%, 3.66%, 5.22%, 5.22%, 8.72%, respectively. After reducing nitrogen application by 30%, there was no significant difference between nitrogen fertilizer utilization rate and conventional nitrogen application rate. In terms of economic traits, the yield and output value of flue-cured tobacco increased by 6.47% and 16.18% after reducing nitrogen fertilizer by 10%.【Conclusion】The reduction of nitrogen fertilizer by 10% and 20% significantly affected the agronomic traits, nutrient distribution, chemical composition and economic traits of tobacco plants, however, the reduction of nitrogen fertilizer by 30% had no significant effect on the agronomic traits and economic traits of tobacco plants. The appropriate reduction of nitrogen fertilizer application promoted the growth of flue-cured tobacco, and improved the yield and quality as well as fertilizer utilization rate of flue-cured tobacco.

The demographic crisis in Bulgaria, marked by the shrinking population, has significant implications for economic growth. This study examines these effects from 1980 to 2022 through the lens of neoclassical economics and empirical modeling. While the crisis is usually associated with negative consequences, the article reveals a potentially counterintuitive phenomenon: the overestimation of labor productivity, estimated at nearly 60% and caused by the demographic crisis, leads to the so-called “growth illusion”. The article shows that the demographic crisis artificially inflates productivity indicators, thus concealing the poor quality of production and threatening long-term economic stability. The results highlight the need for policies to address the structural challenges of the labor market and the confirmed overestimation of its productivity. [ABSTRACT FROM AUTHOR]

【Objective】The effects of nitrogen fertilizer reduction on the growth and development, nutrient utilization, yield and quality of flue-cured tobacco were studied, and the feasibility of nitrogen fertilizer reduction was preliminarily clarified, which provided a theoretical basis for the sustainable production of flue-cured tobacco.【Method】Five treatments were set up, including no fertilization (control), conventional nitrogen application, 10% reduction of nitrogen fertilizer, 20% reduction of nitrogen fertilizer and 30% reduction of nitrogen fertilizer. The agronomic traits, economic traits, chemical composition and fertilizer utilization rate of tobacco plants in each treatment were compared and analyzed.【Result】An appropriate amount of nitrogen fertilizer reduction could shorten the growth period of flue-cured tobacco, and significantly increased the plant height, effective leaf number and maximum leaf width. In terms of chemical composition of tobacco leaves, the indexes of reducing sugar content, total nitrogen content and nicotine content of flue-cured tobacco leaves treated with nitrogen fertilizer reduction by 10% were all within the requirements of conventional chemical composition indexes of highquality flue-cured tobacco in Yunnan. In terms of appearance quality of tobacco leaves, the color of flue-cured tobacco leaves treated with nitrogen fertilizer reduction of 10% and 20% was orange, the structure was loose or still loose, the oil was sufficient, and the appearance quality of tobacco leaves was better. In terms of nitrogen nutrient distribution, the nitrogen content of each part of tobacco plants showed the rule of leaf > stem > root, and the nitrogen content of tobacco leaves was significantly increased under the treatment of 10% nitrogen reduction. In terms of nitrogen use efficiency, after reducing nitrogen application by 10% and 20%, the nitrogen fertilizer utilization rate, agronomic efficiency and partial productivity of nitrogen fertilizer increased by 10.15%, 9.31%, 3.66%, 5.22%, 5.22%, 8.72%, respectively. After reducing nitrogen application by 30%, there was no significant difference between nitrogen fertilizer utilization rate and conventional nitrogen application rate. In terms of economic traits, the yield and output value of flue-cured tobacco increased by 6.47% and 16.18% after reducing nitrogen fertilizer by 10%.【Conclusion】The reduction of nitrogen fertilizer by 10% and 20% significantly affected the agronomic traits, nutrient distribution, chemical composition and economic traits of tobacco plants, however, the reduction of nitrogen fertilizer by 30% had no significant effect on the agronomic traits and economic traits of tobacco plants. The appropriate reduction of nitrogen fertilizer application promoted the growth of flue-cured tobacco, and improved the yield and quality as well as fertilizer utilization rate of flue-cured tobacco. [ABSTRACT FROM AUTHOR]

Purpose: This paper elucidates the determinants of dishonest behaviour affecting various domains and aims to demonstrate how addressing these practices can substantially improve overall quality. Methodology/Approach: A framed laboratory experiment with economics students from the University of West Bohemia was conducted, where participants chose between honest and lower-quality production. Using the Holt-Laury method, we measured risk aversion and personality traits using the Myers-Briggs Type Indicator (MBTI). Findings: Increased inspection probability significantly reduced lower-quality production, with a statistical significance level of less than 1%. Thinking type of personality and Risk Aversion are significant at the 10% level, indicating a moderate impact. Conversely, punishment and rewards were statistically insignificant, with p-values exceeding 10%. Research Limitation/implication: The study is limited by its homogeneous sample of economics students from a single university and insufficient gender representation, which may affect generalizability. Originality/Value of paper: This research provides insights into how inspection probabilities, rewards, punishments, risk aversion, and personal characteristics influence dishonest behaviour, aiding the development of strategies to reduce dishonesty and improve overall quality. [ABSTRACT FROM AUTHOR]

Robot manipulators are classified as serial manipulators and parallel manipulators. Parallel manipulators are classified into planar and spatial parallel manipulators (SPMs). The parallel manipulators have moved and fixed platforms connected with serial chains. The parallel manipulators have many linkages, which create a singularity problem. The singular positions of SPMs have also gained substantial attention in various industrial applications due to their intrinsic advantages in precision, flexibility, and load-bearing capabilities. The 3-PRPPS SPM has three prismatic joints, one spherical joint, and one revolute joint. This work changed the fixed base with a circular guided base to avoid singularity issues. The manipulator was modeled with direct kinematic relations. The Jacobian matrix for position and orientation was derived. The workspace was taken as the common area of the three circles, whose radius was the maximum arm length. The position and orientation of the end effector were traced. In the form of the end effector traces, no singularities in the mechanism were observed. The path of the robot manipulator was observed in all the possible positions and orientations. The multi-body simulation was also conducted on the 3-PRPPS manipulator, the main findings of which are presented in this article.

The electronic control module is an important part of a digital electronic detonator, which undergoes a complex production process that includes three electrical performance tests and three visual inspection procedures. In each inspection procedure, several different types of data are generated daily, including numerical and categorical data. To evaluate the production quality of electronic control modules, an algorithm based on a Deep Belief Network with Multi-mutation Differential Evolution (MDE-DBN) is designed in this study. First, key indicators are extracted to construct a production quality evaluation index system. A Multi-mutation Differential Evolution algorithm is designed to optimize the initial network weights of the Deep Belief Network (DBN) and integrate the production quality information into the pre-training phase. Subsequently, the preprocessed experimental data are input into the MDE-DBN algorithm to obtain the distributions of excellent, general, and unqualified production statuses, verifying the effectiveness of the algorithm. The experimental results show that the MDE-DBN algorithm has significant advantages in evaluation accuracy when compared with DBNs improved by other intelligent optimization algorithms and machine learning methods.

Assessing the best set of maintenance guidelines for various types of failures is often a challenging and complex task. It requires understanding various factors such as safety aspects, environmental issues, energy savings, costs, budget constraints, system reliability, resource utilization, and more. Implementing the correct maintenance process is a critical step in production to increase reliability and improve the effectiveness and quality of the production system. Despite the significant importance of this issue, there are not many studies that analyse and develop procedures for selecting the optimal maintenance strategy. This paper presents the selection of the optimal maintenance strategy using multicriteria decisionmaking, specifically the Analytic Hierarchy Process (AHP), for a case study involving a company in the automotive industry. The defined alternatives are the four most commonly used machine maintenance strategies in the industry: corrective, preventive, condition-based maintenance, and total productive maintenance. The decision criteria considered in the analysis are: production quality, reliability, costs, and safety, along with their respective sub-criteria.

Assessing the best set of maintenance guidelines for various types of failures is often a challenging and complex task. It requires understanding various factors such as safety aspects, environmental issues, energy savings, costs, budget constraints, system reliability, resource utilization, and more. Implementing the correct maintenance process is a critical step in production to increase reliability and improve the effectiveness and quality of the production system. Despite the significant importance of this issue, there are not many studies that analyse and develop procedures for selecting the optimal maintenance strategy. This paper presents the selection of the optimal maintenance strategy using multicriteria decisionmaking, specifically the Analytic Hierarchy Process (AHP), for a case study involving a company in the automotive industry. The defined alternatives are the four most commonly used machine maintenance strategies in the industry: corrective, preventive, condition-based maintenance, and total productive maintenance. The decision criteria considered in the analysis are: production quality, reliability, costs, and safety, along with their respective sub-criteria. [ABSTRACT FROM AUTHOR]

Excessive use of nitrogen (N) pollutes the environment and causes greenhouse gas emissions; however, the application of eco-friendly plant biostimulators (BSs) can overcome these issues. Therefore, this paper aimed to explore the role of diluted bee honey solution (DHS) in attenuating the adverse impacts of N toxicity on Phaseolus vulgaris growth, yield quality, physio-chemical properties, and defense systems. For this purpose, the soil was fertilized with 100, 125, and 150% of the recommended N dose (RND), and the plants were sprayed with 1.5% DHS. Trials were arranged in a two-factor split-plot design (N levels occupied main plots × DH– occupied subplots). Excess N (150% RND) caused a significant decline in plant growth, yield quality, photosynthesis, and antioxidants, while significantly increasing oxidants and oxidative damage [hydrogen peroxide (H2O2), superoxide (O2•−), nitrate, electrolyte leakage (EL), and malondialdehyde (MDA) levels]. However, DHS significantly improved antioxidant activities (glutathione and nitrate reductases, catalase, ascorbate peroxidase, superoxide dismutase, proline, ascorbate, α-tocopherol, and glutathione) and osmoregulatory levels (soluble protein, glycine betaine, and soluble sugars). Enzyme gene expressions showed the same trend as enzyme activities. Additionally, H2O2, O2•−, EL, MDA, and nitrate levels were significantly declined, reflecting enhanced growth, yield, fruit quality, and photosynthetic efficiency. The results demonstrate that DHS can be used as an eco-friendly approach to overcome the harmful impacts of N toxicity on P. vulgaris plants. [ABSTRACT FROM AUTHOR]

Productivity and production quality have become primary goals for the success of companies in all industrial and manufacturing sectors. Performance in terms of productivity is influenced by several factors including machinery efficiency, work environment and safety conditions, production processes organization, and aspects related to workers' behavior (human factors). In particular, work-related stress is among the human factors that are most impactful and difficult to capture. Thus, optimizing productivity and quality in an effective way requires considering all these factors simultaneously. The proposed system aims to detect workers' stress and fatigue in real time using wearable sensors and machine learning techniques and also integrate all data regarding the monitoring of production processes and the work environment into a single platform. This allows comprehensive multidimensional data analysis and correlation research, enabling organizations to improve productivity through appropriate work environments and sustainable processes for workers. The on-field trial demonstrated the technical and operational feasibility of the system, its high degree of usability, and the ability to detect stress from ECG signals exploiting a 1D Convolutional Neural Network (accuracy 88.4%, F1-score 0.90). [ABSTRACT FROM AUTHOR]

The aim of the paper is to examine the requirements of producers in post-communist countries with lower economic level. The first requirement was how to overcome the limitations of conventional PFMEA to propose measures effectively. The second requirement solved the economic effect of failure modes. The aim of the paper was to create a new hybrid PFMEA–DEMATEL–ERPN model to manage failure modes to resolve the requirements. The DEMATEL model overcame the limitations of PFMEA. DEMATEL data were used to estimate the functionality of the proposed models. Criteria such as the occurrence of defective products and the probability of their occurrence (O and RPN) were monitored. ERPN also overcame the limitations of PFMEA. Internal and external costs arise as effects of failure modes. The costs were included in the economic evaluation of the models. We validated the models in a transfer pressing process. The estimation of models' functionality proved to be correct. The economic evaluation refined the research results and resolved the second requirement of the manufacturers. The DEMATEL and ERPN models (compared to PFMEA) proved their validity when the use of PFMEA was limited. By using DEMATEL, we registered the lowest number of defective products and the lowest costs. [ABSTRACT FROM AUTHOR]

Local radio has played a significant role in keeping local cocoa farmers informed about their farming activities. However, the experiences of these local farmers who should be the real owners of community radio have not been captured. It would be possible to increase cocoa production if the experiences of local cocoa farmers were given the attention needed. Using a quantitative research approach, the multi-stage sampling technique was used to select 385 respondents. Data were analyzed using frequencies, percentages, means, standard deviations and Kendall's coefficient of concordance. Results show that farmers were undecided about their reliance on community radio and the role it plays in disseminating agricultural information. However, they understood the agricultural-related information disseminated on community radio. They agreed that the content and presentation of community radio programs were suitable for them but were undecided on the transmission quality and community involvement. Interference from local leaders was the most severe challenge facing farmers' use of community radio. In order to improve extension delivery there is a need for policymakers and agricultural extension stakeholders to implement programs that will encourage farmers to set up and rely on community radio as a great alternative source of information for their farming activities. This is also necessary to improve the currently low contact of extension agents with farmers, thus, reducing the extension farmer ratio. [ABSTRACT FROM AUTHOR]

Introduction: The productivity of an organization is closely related to the improvement of the safety and health of employees and the development of knowledge and skills of human resources in advancing the organization goals. Based on a combination of questionnaire and survey, this study examines the impact of implementing safety management practices on the performance and job satisfaction of employees in Iran's production units. Research Method: This descriptive-cross-sectional study was conducted in 1400 on 200 employees and managers of the Hacoupian clothing industrial company located in Tehran province. 130 of them were selected based on random sampling using the Morgan table. Data collection tools included a researcher-made questionnaire, which was further confirmed by experts by applying their opinions regarding its validity and reliability. It was approved by experts. The analysis method in this study is mainly descriptive and the type of research is relational. Data and research hypotheses were respectively tested using Structural equation modeling (SEM) and Partial least squares (PLS) approach through SPSS26 software. Results: Findings showed the appropriate fit of measurement and structural models. In addition, results demonstrated the positive effect of improving safety on the job satisfaction of employees in production units, as well as the negative effects of not paying attention to the health of the working environment on the quality of employees' performance. Conclusion: The more companies and governments pay attention to the issue of operational health and safety, the organizational and environmental situation will be formed in such a way that it will optimally motivate employees and increase the quality of production and operations in the organization.

5S (Sort, Set in order, Shine, Standardize, dan Self Discipline) is a work culture that must be applied in all workplaces both in the formal and informal sectors. The implementation of 5S aims to make workers feel comfortable and safe while working. In addition, the application of 5S can make work more effective and efficient because it can eliminate wasted time due to more time to search for goods, work areas that look full due to excess equipment and un needed goods or dirty environments. Furniture Works In Semanding District, Kauman, Ponorogo is one of the informal sectors that have not implemented 5R. This is seen from the condition of the work area full of unnecessary equipment and goods, messy, and dirty. Therefore, researchers conducted research analysis of the application of 5S in Furniture Works. Purpose: The purpose of the research to know the application of the principle of 5S in Furniture Works. Method: This research uses qualitative design. The research was conducted with direct observation and using the 5S checklist. Research Results: The results showed that the application of 5S in Furniture Works is still not good. This is evident from the achievement of the 5S as a whole which is below 50%. Conclusion: The results of the study concluded that the implementation of 5S in Furniture Works is still lacking so it is necessary to conduct training on 5S and internal audits periodically.

This extensive experimental research provides strong empirical proof of the revolutionary power of deep learning algorithms when integrated into Industry 5.0. Convolutional Neural Networks (CNN), Long Short-Term Memory (LSTM), Generative Adversarial Networks (GAN), and Transformers are a few examples of deep learning algorithms that have shown remarkable accuracy rates of 92.3%, 88.7%, and 95.1%, respectively. Furthermore, the processing durations, which vary between 15 and 25 milliseconds, confirm their ability to make decisions in real time. The abundance of various data accessible in Industry 5.0 is highlighted by data collection sources such as picture databases (300 GB), text corpora (150 GB), equipment records (250 GB), and IoT sensor data (500 GB). The significant energy savings, shown by 20% reductions across a range of machine types, highlight the financial and ecological advantages of deep learning integration. Moreover, the noteworthy improvements in production quality, exhibiting up to 50% reductions in defect rates, highlight the potential of deep learning in quality assurance. These results provide tangible proof of the critical roles deep learning algorithms play in streamlining production lines, increasing energy economy, and boosting product quality in the ever-changing Industry 5.0 environment.

The variation of some parameters of flowering, fruiting, and pepper production, in relation to the fertilization system, was evaluated. The study took place in the area of Cuied Locality, Arad County, Romania. The experiment was in a protected system, modular solar, the summer-autumn crop cycle, year 2020, with a specific technology. Two long pepper varieties of the Kapia type were cultivated (Dumbo 34 - D 34; Elephant's Ear - EE). Three products were used for fertilization, BioHumusSol (BHS), Cropmax (CroM) and Bionat (BioN), together with a control variant (C). The number of pollinated and fertilized flowers per plant (pff) varied between 5.00±0.35 (EE C) and 8.60±0.41 (D34 CroM), and the number of fruits per plant (FruNP) varied between 5.00±0.32 (EE C) and 8.00±0.49 (D34 CroM). The average fruit weight (FaW) varied between 83±13.30 g (D34 C) and 274±22.7 g (EE CroM). The average fruit production per plant (ApP) varied between 0.580±0.13 kg plant-1 (D34 C) and 1.920±0.20 g plant-1 (EE CroM). Quality I production (YQ1, %) varied between 10.20% (S34 C) and 76.00% (EE CroM), and quality II production (YQ2, %) varied between 24.00% (EE CroM) and 89.80% (D34 C). According to PCA, PC1 explained 68.383% of variance, and PC2 explained 28.917% of variance in relation to flowering and fruiting parameters; PC1 explained 65.489% of variance, and PC2 explained 34.28% of variance in relation to productivity and production parameters, respectively PC1 explained 61.09% of variance, and PC2 explained 38.91% of variance in relation to production quality. The regression analysis facilitated to describe the variation of production by quality classes (YQ1) in relation to productivity parameters. [ABSTRACT FROM AUTHOR]

Paper presents the effect of the Panoramix biofertilizer, whose composition consists of a combination of fungi (Trichoderma spp.) and bacteria (Bacillus spp.) on the quality of the edible part of sweet corn. The sweet corn crop was established in 2019, by sowing, and the seeds were treated with Panoramix, at a dose of 2 ml/kg seed. In this sense, two sweet corn hybrids were tested:'Basin F1' and 'Challenger F1. The variants were organized as follows:'V1- 'Basin F1'- untreated; V2- 'Basin F1'- treated; V3- 'Challenger F1'- untreated; V4 -'Challenger F1' - treated. The results regarding some the quality components, like TSS, reducing sugar, starch, carotene and antioxidant capacity confirmed the superiority of the application of the Panoramix biofertilizer compared to non-mycorrhizal variants. Among the tested hybrids, 'Challenger F1' recorded a better quality of sweet corn caryopses in the version treated with the micorryzal product. Based on the obtained results, it can be stated that the product Panoramix could be recommended as a promising sustainable approach to stimulate the quality of the sweet corn. Among the tested hybrids, 'Challenger F1' recorded a better quality of sweet corn caryopses in the version treated with the with the mycorrhizal product. [ABSTRACT FROM AUTHOR]

Excessive use of nitrogen (N) pollutes the environment and causes greenhouse gas emissions; however, the application of eco-friendly plant biostimulators (BSs) can overcome these issues. Therefore, this paper aimed to explore the role of diluted bee honey solution (DHS) in attenuating the adverse impacts of N toxicity on Phaseolus vulgaris growth, yield quality, physio-chemical properties, and defense systems. For this purpose, the soil was fertilized with 100, 125, and 150% of the recommended N dose (RND), and the plants were sprayed with 1.5% DHS. Trials were arranged in a two-factor split-plot design (N levels occupied main plots × DH– occupied subplots). Excess N (150% RND) caused a significant decline in plant growth, yield quality, photosynthesis, and antioxidants, while significantly increasing oxidants and oxidative damage [hydrogen peroxide (H2O2), superoxide (O2•−), nitrate, electrolyte leakage (EL), and malondialdehyde (MDA) levels]. However, DHS significantly improved antioxidant activities (glutathione and nitrate reductases, catalase, ascorbate peroxidase, superoxide dismutase, proline, ascorbate, α-tocopherol, and glutathione) and osmoregulatory levels (soluble protein, glycine betaine, and soluble sugars). Enzyme gene expressions showed the same trend as enzyme activities. Additionally, H2O2, O2•−, EL, MDA, and nitrate levels were significantly declined, reflecting enhanced growth, yield, fruit quality, and photosynthetic efficiency. The results demonstrate that DHS can be used as an eco-friendly approach to overcome the harmful impacts of N toxicity on P. vulgaris plants.

This study took food-grade polypropylene packaging products as the research project and discussed how to control the polypropylene extrusion sheet thickness and vacuum thermoforming quality and weight. The research objective was to find the key factors for reducing costs and energy consumption. The key aspects that may influence the polypropylene extrusion molding quality control were analyzed using literature and in-depth interviews with scholars and experts. These four main aspects are (1) key factors of polypropylene extrusion sheet production, (2) key factors of the extrusion line design, (3) key factors of polypropylene forming and mold manufacturing, and (4) key factors of mold and thermoforming line equipment design. These were revised and complemented by the scholar and expert group. There are 49 subitems for discussion. Thirteen scholars and experts were invited to use qualitative and quantitative research methods. A Delphi questionnaire survey team was organized to perform three Delphi questionnaire interviews. The statistical analyses of encoded data such as the mean (M), mode (Mo), and standard deviation (SD) of various survey options were calculated. Seeking a more cautious research theory and result, the K-S simple sample test was used to review the fitness and consistency of the scholars' and experts' opinions on key subitem factors. There are ten key factors in the production quality, including "A. Main screw pressure", "B. Polymer temperature", "C. T-die lips adjustment thickness", "D. Cooling rolls pressing stability", "E. Cooling rolls temperature stability", "F. Extruder main screw geometric design", "G. Heating controller is stable", "H. Thermostatic control", "I. Vacuum pressure", and "J. Mold forming area design". The key factors are not just applicable to classical polypropylene extrusion sheet and thermoforming production but also to related process of extrusion and thermoforming techniques in expanded polypropylene (EPP) sheets and polylactic acid (PLA). This study aims to provide a key technical reference for enterprises to improve quality to enhance the competitiveness of products, reduce production costs, and achieve sustainable development, energy savings, and carbon reductions. [ABSTRACT FROM AUTHOR]

The aim of the paper is to examine the requirements of producers in post-communist countries with lower economic level. The first requirement was how to overcome the limitations of conventional PFMEA to propose measures effectively. The second requirement solved the economic effect of failure modes. The aim of the paper was to create a new hybrid PFMEA–DEMATEL–ERPN model to manage failure modes to resolve the requirements. The DEMATEL model overcame the limitations of PFMEA. DEMATEL data were used to estimate the functionality of the proposed models. Criteria such as the occurrence of defective products and the probability of their occurrence (O and RPN) were monitored. ERPN also overcame the limitations of PFMEA. Internal and external costs arise as effects of failure modes. The costs were included in the economic evaluation of the models. We validated the models in a transfer pressing process. The estimation of models’ functionality proved to be correct. The economic evaluation refined the research results and resolved the second requirement of the manufacturers. The DEMATEL and ERPN models (compared to PFMEA) proved their validity when the use of PFMEA was limited. By using DEMATEL, we registered the lowest number of defective products and the lowest costs.

Manageability has gotten a significant measure of interest and has been assigned to the board. As a contextual investigation, this paper presents a survey of articles focusing on the meaning of creation and the activities of executives in the manageability of the assembling business, with a specific focus on fossil fuel by-products involving the food and drink industry. This study reviewed current articles that cut across production quality, operation management, and tools for the sustainable development of food and beverages in manufacturing industries. The papers are arranged and examined by the three fundamental areas of activities of the board (issue, execution methodology, and improvement). The concentrate additionally dissects the papers as indicated by whether they address the importance of the activity the board manages towards Nutrition, Health, and Wellness Company, which will be the case study. From this research, it was observed that the activity of the executives shows up as a pertinent variable in all center areas of supportable assembly research; however, the bearing and strength of its effect remain dubious. The research looks at how administrators can effectively manage the problems associated with fossil fuels through products and quality nutrition, health, and wellness of the company for both consumers and employees.

This study took food-grade polypropylene packaging products as the research project and discussed how to control the polypropylene extrusion sheet thickness and vacuum thermoforming quality and weight. The research objective was to find the key factors for reducing costs and energy consumption. The key aspects that may influence the polypropylene extrusion molding quality control were analyzed using literature and in-depth interviews with scholars and experts. These four main aspects are (1) key factors of polypropylene extrusion sheet production, (2) key factors of the extrusion line design, (3) key factors of polypropylene forming and mold manufacturing, and (4) key factors of mold and thermoforming line equipment design. These were revised and complemented by the scholar and expert group. There are 49 subitems for discussion. Thirteen scholars and experts were invited to use qualitative and quantitative research methods. A Delphi questionnaire survey team was organized to perform three Delphi questionnaire interviews. The statistical analyses of encoded data such as the mean (M), mode (Mo), and standard deviation (SD) of various survey options were calculated. Seeking a more cautious research theory and result, the K-S simple sample test was used to review the fitness and consistency of the scholars’ and experts’ opinions on key subitem factors. There are ten key factors in the production quality, including “A. Main screw pressure”, “B. Polymer temperature”, “C. T-die lips adjustment thickness”, “D. Cooling rolls pressing stability”, “E. Cooling rolls temperature stability”, “F. Extruder main screw geometric design”, “G. Heating controller is stable”, “H. Thermostatic control”, “I. Vacuum pressure”, and “J. Mold forming area design”. The key factors are not just applicable to classical polypropylene extrusion sheet and thermoforming production but also to related process of extrusion and thermoforming techniques in expanded polypropylene (EPP) sheets and polylactic acid (PLA). This study aims to provide a key technical reference for enterprises to improve quality to enhance the competitiveness of products, reduce production costs, and achieve sustainable development, energy savings, and carbon reductions.

It is imperative for manufacturing systems to improve production quality not only to maintain profitability, market share and competitiveness, but also to reduce energy waste resulted from defective items. Although quality and energy saving have attracted extensive attention in the past few decades, there is little research effort devoted to a systematic understanding of their intersection. Therefore, this paper analyzes the energy usage of a multistage production system with quality control. The Geometric reliability and Bernoulli quality models are assumed. A Markov process model is established to predict the dynamics of the production system. The energy economics of the production system are analyzed to include both production and energy cost. The optimal PWQ (Production with Quality Inspection) machine allocation method and the cost-effectiveness analysis method are formulated to increase the profit. According to the computational experiments, the proposed optimal PWQ machine allocation method can effectively reduce energy consumption. In addition, pay-back period (PBP) is an effective indicator which helps production managers make cost effective decisions for machine replacement. The research results in an in-depth understanding of the energy economics of systems with quality control, which is necessary for manufacturers to gain competitiveness with better product quality and higher energy efficiency.

In this article, we develop a system based on WSN platform to measure the data of crop parameters for the agriculturists aimed to enhance the quality and quality of the crops. The proposed system will minimize the exhaustive field visits of the farmers. This system will facilitate the precision agriculture by measuring three most key parameters (temperature, humidity and light) of the crops. The proposed system consists of IRIS motes MDA100CB data board, and MIB520 USB interface board. These are considered as sink and sensor nodes respectively. TinyOS is used to develop the code for WSN nodes, and GUI device is composed in Microsoft Visual Studio-2008 for displaying the measured data and stored in data base accordingly. ZigBee IEEE 802.15.4 and direct topology are utilized for the correspondence of sensor nodes with the base station

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Copyright of Technical Electrodynamics / Tekhnichna Elektrodynamika is the property of National Academy of Sciences of Ukraine, Institute of Electrodynamics and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The aim of this study was to evaluate the influence of medium chain fatty acids (MCFAs) and organic acids (OAs) supplements on the caecum microbial profiles, productivity and production quality characteristics of broiler chickens (BCs). BC (900 chicks) were attributed to three groups: (i) control; (ii) MCFAs group (BCs fed with feed supplemented with MCFAs); (iii) OAs group (BCs fed with feed supplemented with OAs). Broilers were slaughtered at the end of the trial (42 days old), and the caecum microbial profiles, productivity and production quality characteristics were analysed. Supplementation with OAs resulted in a more appropriate environment in the caecum for beneficial microorganisms than with a diet supplemented with MCFAs. This was supported by data on the presence of higher amounts and an increased species variety of probiotic bacteria (Lactobacillus and Bifidobacterium) in the caecum of birds. The above-mentioned changes of the caecum microbiota led to significantly higher villus height (p = 0.003) of the OAs broiler group and significantly lower crypt depth (p = 0.037). Notwithstanding the significant increase of acetic, propionic, isobutyric, butyric, isovaleric, and valeric acids that were established in caecum samples from the MCFAs group, better parameters of broiler production performance (higher body weight and lower mortality) and carcass traits (higher both thigh and shin muscles with skin and bone weight; both shin muscles without skin and bone weight; abdominal fat yield) were found in the OAs-treated group. For chemical, physical and technological characteristics of breast meat samples, increased yellowness and water holding capacity by 14.7% and 2.3%, respectively, were found in MCFAs group samples. A more appropriate environment in the caecum for beneficial microorganisms could be obtained when BCs were fed with OAs supplement, comparing to MCFAs, and these positive changes were associated with higher efficiency of poultry production.

The purpose of this paper is to systematically examine available empirical evidence on the impact of human factors (HF) in the design and management of manufacturing operations on system quality performance. A systematic review was conducted to map the linkages between the human-system fit in the design of operations systems (OS) with production quality. A total of 73 empirical studies were identified linking HF to OS performance in manufacturing. Quality risk factors included HF aspects in product design, process design and workstation design of the manufacturing OS. Quality deficits were associated with undesirable human effects of workload like fatigue and injury-related risk factors. Forty-six percent of the studies reported on efforts to improve HF in the OS with effect sizes for quality improvements reaching up to 86%. The paper documents available quality risk factors in the design of OS. It also provides a conceptual framework explaining HF-Quality linkage. [ABSTRACT FROM AUTHOR]

Opportunity cost is an economic concept which takes on multiple forms of expression. One of these is the foregone profit as a result of the manufacturer’s option to produce goods by quality classes or of its choice of goods with certain values of gross margin and production lead times. This paper is focused on presenting some situations of avoiding opportunity costs within the meaning of foregone profit. To this end we contemplated two situations: i) one where manufacturers may opt, or not, to produce branded goods; ii) another where a restrictive factor (technical/physical and financial) may influence the manufacturer’s decision-making in what type of goods should be manufactured.

The article presents an information technology model for the transparent feedback of quality-related information on the vehicle assembly production process in real time. This system integrates huge amounts of heterogeneous data sets, gathered through quality gates in the assembly line, to provide new user-focused information for controlling production quality. All information is prepared to cater to the specific needs of three different types of users and then reported back via four levels of quality feedback to the recipients as a defect occurrence in quality. This ensures that quality-related process information is provided immediately as essential to make progress towards achieving first-time quality and improving production quality. [ABSTRACT FROM AUTHOR]