Hasil untuk "Industrial productivity"

Hamed Naderi, Mohammad Ali Rastegar Sorkhe, Bakhtiar Ostadi et al.

This study investigates and predicts the likelihood of operational risk occurrence in the banking industry using machine learning algorithms. The primary objective is to analyze operational risk data and evaluate the performance of various machine learning models to develop effective tools for enhancing risk management and minimizing financial losses in banks and financial institutions. Operational risk data were collected, pre-processed, and then used for predictions with machine learning models, including Random Forest (RF), Decision Tree (DT), Support Vector Machine (SVM), Logistic Regression (LR), Naïve Bayes (NB), and k-Nearest Neighbors (KNN). Model performance was assessed using evaluation metrics such as accuracy, precision, recall, F1-score, and the Area Under the Curve (AUC) to determine the most effective model for risk prediction. The findings indicate that the RF and SVM algorithms outperform other models in predicting operational risk across all scenarios. Furthermore, the results demonstrate the strong predictive capability of machine learning algorithms in assessing operational risk, highlighting their potential as valuable decision-making tools for risk management in the banking sector.Keywords: Risk Prediction, Operational Risk, Risk Management, Machine Learning IntroductionOperational risk is defined as the risk arising from external factors or failures in internal controls or information systems, which may lead to both anticipated and unexpected losses (Crouchy et al., 1998). Lopez (2002) characterizes it as any unquantifiable risk that a bank may encounter. According to the Basel II Agreement, operational risk refers to the probability of loss resulting from deficiencies, breakdowns, or inefficiencies in human resources, processes, technologies, infrastructure, or internal and external events (Pena et al., 2018).To estimate the capital required to cover operational risk, the Basel framework introduces three approaches: the Basic Indicator Approach (BIA), the Standardized Approach (SA), and the Advanced Measurement Approach (AMA) (Mora Valencia, 2010; Mora Valencia et al., 2017). The BIA and SA estimate capital requirements based on annual gross income, with the key distinction being that the SA categorizes a bank’s activities into eight business lines. Under the BIA, an alpha coefficient (α) of 15% is applied, whereas in the SA, each business line has a specific beta coefficient (β) ranging between 12% and 18%. The AMA employs both quantitative and qualitative methods for operational risk modeling, leveraging databases to collect statistical data and utilizing the loss distribution approach (LDA) to model frequency and severity distributions. Capital coverage is then determined based on the cumulative distribution of these variables. Since the LDA is data-driven, the Basel framework (BCBS, 2004) emphasizes the necessity of a robust database for collecting operational risk data. Four key databases are required: internal loss event data, external loss event data, scenario-based analysis data, and a database of business environment and internal control factors.Compared to other banking risks, such as credit and market risks, measuring, monitoring, and managing operational risk is considerably more complex. This risk has gained increasing attention in recent years, as large operational losses have led to the liquidation of financial institutions (Abdymomunov et al., 2020; Afonso et al., 2019). Crisanto and Perino (2017) identify cyber threats and cyber fraud as critical factors influencing operational risk capital estimation. These risks have intensified with the growth of electronic banking services and include illegal access, system disruptions, and the misuse or theft of digital assets for financial gain (BCBS, 2016; Drew & Farrell, 2018). To quantify potential losses in electronic banking transactions, Bouveret (2018) proposed a Bayesian Network (BN) model to estimate operational risk capital requirements in financial institutions.Machine learning has emerged as one of the most promising yet challenging approaches in modern finance (Tsai & Wu, 2008). These methods have transformed the financial industry, with deep learning (DL) being extensively studied and applied due to its adaptability and predictive capabilities (Ivanov, 2019). Pena et al. (2021) employed a fuzzy convolutional deep learning model to estimate the maximum operational risk value at a 99.9% confidence level. Similarly, Zhou et al. (2020) utilized semi-supervised machine learning algorithms to classify operational risks based on financial news, analyzing 5,843 documents from financial articles and newspapers in the Asia-Pacific region between February and March 2019. Their model demonstrated the capability to predict various types of risks in the banking industry. In another study, Akbari and Yazdanian (2023) applied machine learning algorithms to determine optimal thresholds for operational loss severity data, classifying the data and estimating the capital required to cover operational risk by integrating severity and frequency distribution functions with Monte Carlo simulation. Method and DataIn this study, operational risk data were collected, pre-processed, and then used for predictions with machine learning models, including RF, DT, SVM, LR, NB, and KNN. The models' performance was assessed using evaluation metrics such as accuracy, precision, recall, F1-score, and AUC to identify the most effective model for predicting the likelihood of risk occurrence. FindingsThe results indicate that the RF and SVM algorithms exhibit strong performance in predicting operational risk across all scenarios. Specifically, the RF algorithm achieved an accuracy of 0.9690, while the SVM algorithm attained an accuracy of 0.9587 in State 1, making them the most effective models in this setting. Both algorithms demonstrated comparable performance across other modes. Conclusion and DiscussionThis study analyzes and predicts operational risk occurrence in the banking industry using machine learning algorithms. The findings indicate that various algorithms, particularly RF and SVM, demonstrate strong predictive performance. These results have the potential to transform operational risk management in banks, leading to significant reductions in associated costs and losses.A key insight from this study is that leveraging large and diverse datasets can substantially enhance prediction accuracy. Machine learning models can process complex datasets, identify hidden patterns, and facilitate early risk detection, enabling banks to implement preventive measures before risks materialize. Moreover, integrating machine learning into risk management enhances decision-making by providing precise, data-driven predictions, allowing for more effective strategies and efficient resource allocation.Future research could incorporate additional data, such as historical records, economic indicators, and internal process information, to further improve prediction accuracy. With advancements in technology, more sophisticated techniques—such as reinforcement learning methods (e.g., DQN, Q-Learning, DDPG, and Meta-Learning)—could enhance the accuracy and efficiency of operational risk prediction models.

Gábor Lakatos, Bence Zoltán Vámos, István Aupek et al.

Shift organizations in automotive manufacturing often rely on manual task allocation, resulting in inefficiencies, human error, and increased workload for supervisors. This research introduces an automated solution using the Kuhn-Munkres algorithm, integrated with the Moodle learning management system, to optimize task assignments based on operator qualifications and task complexity. Simulations conducted with real industrial data demonstrate that the proposed method meets operational requirements, both logically and mathematically. The system improves the start of shifts by assigning simpler tasks initially, enhancing operator confidence and reducing the need for assistance. It also ensures that task assignments align with required training levels, improving quality and process reliability. For industrial practitioners, the approach provides a practical tool to reduce planning time, human error, and supervisory burden, while increasing shift productivity. From an academic perspective, the study contributes to applied operations research and workforce optimization, offering a replicable model grounded in real-world applications. The integration of algorithmic task allocation with training systems enables a more accurate matching of workforce capabilities to production demands. This study aims to support data-driven decision-making in shift management, with the potential to enhance operational efficiency and encourage timely start of work, thereby possibly contributing to smoother production flow and improved organizational performance.

Korhan Arun, Saniye Yıldırım Özmutlu

Purpose: This study aims to examine the impacts of institutional pressures and individual adaptation performance on the adoption of green supply chain practices and reverse logistics, and their effects on production-based CO2 emissions, focusing on emerging markets with a detailed case study of Türkiye.Methodology: The research methodology employed structural equation modeling (SEM) and SmartPLS for the analysis of the data. This approach allowed for an in-depth examination of the relationships between institutional pressures, individual adaptive performance, green supply chain practices, reverse logistics, and CO2 emissions.Findings: The findings reveal a nuanced relationship where institutional pressures directly impact reverse logistics but show minimal direct influence on green supply chain practices or CO2 emissions reduction. In contrast, individual adaptive performance is crucial in enhancing both green supply chain practices and reverse logistics. Notably, reverse logistics is significantly effective in reducing CO2 emissions. Originality: This study enriches the literature by revealing how institutional pressures and individual adaptive performance influence green supply chain management in emerging markets, particularly demonstrating through the case of Türkiye that the impact of within-field variability on the adoption of superior practices depends on individual adaptive performance.

Ivan Rueda, Grace Tamayo, Byron Acosta et al.

Type of the article: Research Article AbstractToday, manufacturing companies seek tools that enable them to remain competitive in an increasingly demanding global environment, with quality management systems being among the most widely adopted. Despite their broad implementation, empirical evidence regarding their benefits remains inconclusive. Evaluating productivity indicators in certified manufacturing firms is essential to identifying the variables that most influence operational and financial efficiency in this sector. This paper aims to determine the effect of ISO certification on productivity indicators by applying a multivariate discriminant analysis model to a sample of industrial firms with five consecutive years of certification during the 2019–2023 period. The results show that only three indicators – operating income relative to value added, net income relative to value added, and value added relative to working capital – exhibit statistically significant average improvements, associated with increased operational efficiency and value generation. The operating income relative to value added indicator stands out as the variable with the greatest discriminant power, suggesting that ISO 9001 certification positively influences operational productivity. However, the findings also reveal high variability, indicating that the certification’s impact is not homogeneous and depends on both internal and external organizational factors. This study provides valuable empirical evidence in the Ecuadorian context, being the first to assess this relationship using discriminant analysis and contributing to the understanding of quality management system effectiveness in emerging economies.

Mehmet Ceylan, Seda Hezer

One of the most important ways to increase productivity in industrial manufacturing is the efficient design of assembly lines. These lines consist of workstations connected by moving belts or conveyors where products are assembled part by part to reach their final form. In today's competitive manufacturing environment, organizing the work to be performed at these stations in the most efficient way is critically important. This organization process is called the “Assembly Line Balancing Problem (ALBP)” and primarily focuses on two main objectives: minimizing the number of workstations and cycle time. However, recently, this classical approach has given way to a more comprehensive perspective. Now, the optimization of resources such as workers, machines, equipment, and energy is also included in the problem. This advanced problem is termed the “Resource-Constrained ALBP (RCALBP)”. Within the scope of this study, the “Multi-Model RCALBP (MRCALBP)” was implemented in a company manufacturing industrial kitchen machines. Based on a known mathematical model in the RCALBP literature, a solution has been developed adapted to the specific needs of the company. Successful results were achieved through optimization work using 19 different resources for four different products. Two separate production lines were merged into one line, total number of resources was reduced from 46 to 31, and the number of workers was decreased from 4 to 2. At least 49% improvement in total costs has been achieved for each product. This study demonstrates that theoretical models can be successfully applied in real life and provide tangible benefits.

H. Kurinenko, U. Kuts, М. Ostapchuk et al.

Purpose.To characterize the productive and biological features of the first generation crossbreed carp from the crossbreeding of Antoniny-Zozulenets, Galician and Lyubin inbred types of Ukrainian framed and scaly breeds adapted to cultivation in the conditions of Polissiya. Methodology. The study was conducted at the Lviv Research Station of the Institute of Fisheries of the National Academy of Sciences. The material for the study was crossbred age-0+ and age-1 carps obtained from brood Lyubin (LSC), Galician (GFC) and Antoniny-Zozulenets carps obtained by natural spawning in ponds, according to the following scheme: ♀LSC×♂LSC; ♀LSC×♂AZFC; ♀AZSC×♂LSC; ♀AZFC×♂GFC. The brood stock was kept according to the instructions in the carp breeding. Studies of productive and biological parameters were carried out according to the common methods in fish farming and ichthyology. The heterosis effect for the main productive parameters was calculated by the excess of the corresponding parameter in the crossbreed group over the parameter of the original maternal line. Feeding of age-0+ fish was carried out with ground grain starting from the second decade of July. Winter hardiness of crossbred and pure lines was evaluated by absolute and relative loss of body weight and survival rate. The data obtained in the experiments was subjected to statistical processing in MS Excel (2016). The criteria for the analysis of parameters were their average value and standard error (M±m). Findings. The study showed that the survival rate of purebred age-0+ carps was 52.4%, with an average weight of 26.79±1.83 g. The yield of crossbred age-0+ fish grown in nursery ponds was 51.3%, but their average weight was the highest — 33.97±4.49 g. The yield of age-0+ fish obtained from crossing ♀AZFC×♂GFC grown in concrete ponds was 55.4% and was the highest among all experimental groups. The survival rate of age-0+ fish obtained from crossing ♀AZSC×♂LSC was 53.1%. The individual average weights of age-10+ carps grown in concrete ponds were close and amounted to 15.39±2.01 and 16.45±1.30 g, respectively, according to the experimental groups. Fish productivity in concrete ponds was 255.8 and 261.9 kg/ha. The analysis of wintering showed that the yield from the wintering of age-1 LSC and cross-breeding group ♀LSC×♂AZFC was 81.7% and 76.0%, with higher values of the yield of purebred scaly age-1 fish. At the same time, they also had a lower rate, almost 2% weight loss during the winter — 8.9% versus 10.8% in crossbred framed age-1 fish. Age-1 fish of crossbred groups, which were obtained from Antoniny-Zozulenetsk carp females, had a survival rate of 51.3–55.5% with a weight loss of 12.9–13.1%. Originality. For the first time, the advantages and biological parameters of crossbred groups and individual types of carp from the combination of different structural units, namely Antoniny-Zozulenetsk, Lyubin and Galician inbred types of carps were obtained and studied. Therefore, scientific studies aimed at finding optimal combinations of productive traits of carp, by crossing fish of various structural units not only with desired traits, but also with maximally different genetic characteristics, is particularly important. Practical Value. The obtained results demonstrate the effectiveness of the use of industrial crossing in modern fish farming practice. Taking into account the belonging of each inbred type to ecological and geographical conditions, when crossing breeds of different geographical origins, an increase in the effect of heterosis is observed. Industrial hybridization and its high efficiency in pond fish farming due to the use of heterosis plays an important role in increasing the fish productivity of pond farms.

N. Lukianchuk, P. Tretyak

Introduction. The climate changes, in particular, its oxygen and water vapor content in air have acquired special importance for human health. The aim of the study. To investigate the environmental health effect of tree-shrub vegetation on the air as a sanogenic factor. Materials and methods. The impact of tree and shrub vegetation productivity on the air material and energy balance were performed on the fundamental method basis. The forest productivity in Ukraine and, particularly, of Lviv region and individual objects nature reserve fund, is represented by tree trunks annual increment average volume of official data. The amount of deposited carbon in the total phytomass, produced oxygen and water vapor, as well as the thermal energy consumption for its evaporation was calculated on the material-energy proportions basis of photosynthesis and transpiration processes. Results. The Ukrainian forests annually produce 60 million tons of atomic oxygen, making an important impact for air enrichment and local disinfection. Also they vapor 36.3×109 tons of water, consuming for this purpose 25×106 GW-hours thermal energy, which is cooling the boundary air layer upon the Ukrainian territory up to 0.3-0.6 0С. Subjected to an average annual wood increment of 4.2 m3/ha-1/year-1, their tree and shrub vegetation produce annually 6.72 t/ha-1 of oxygen and vapor 4064 t/ha-1 of water. Such evaporation requires consumption of 2.772 GW/h/ha-1 of thermal energy, which is equal for cooling of the 30-meter surface air layer in their stands by 1.84-3.05 0С. Conclusions. The obtained results emphasize an extremely important environment-forming role of the production process of tree-shrub vegetation, in particular, forests, nature reserve objects, parks and green spaces of cities and towns. Such fundamental provisions should be reflected in the educational process of ecology, resort science and phytoremediation. On their basis, it is expedient to develop projects for optimizing the environment of settlements, industrial and resort zones. An increase in the environment-forming influence of vegetation can be achieved by increasing their productivity, in particular, by increasing the potential indicators of the volume, density and growth of stands per unit area. It is desirable to have a large number of large trees of fast-growing species.

Yuri P. Dobrachev, Snezhana A. Menshikova

Purpose: to determine the most advantageous composition of the agro-reclamation measures complex from the ecological and economic positions and its placement taking into account the natural resource, as well as historical and social potential of the lands occupied in agricultural production. Materials and methods. Version programming of the agricultural area development process using modern capabilities of computer modeling allows predicting the effect depending on a hypothetical change in external conditions and identifying the most advantageous strategies for the reclamations development and placement from a variety of options. Methodological approaches to the strategy formation are based on the enumeration of all possible options represented by combinations of interacting reclamations combinations and related agro-reclamation factors, with subsequent assessment of their effectiveness. The choice of options is based on the methodological approach to identifying indices of the state of environmental components. Results. Calculations of the integrated assessment of the efficiency of options for a period of 25 years were performed using the initial most costly technical and economic indicators of reclamation measures. The production and economic characteristics of 254 options for the composition of the complex reclamation measures for sod-podzolic soil of average cultivation in Ryazan region (grass-grain crop rotation) are given. The majority of options (90 %) show low productivity and negative profitability, 8 % of options with high productivity are characterized as “ecologically stressed”, and only 2 % of options meet all the requirements. Conclusions. Already at the stage of implementing an investment project in the agro-industrial complex, measures to compensate for and prevent negative phenomena are provided. Highly effective measures can be implemented only if expensive additional measures to ensure the preservation of the natural environment and compliance with regulatory environmental requirements are included.

Mohammad Taghi Taghavifard, Amir Mohammad Khani, Soraya Beyrami

Small, medium and high-yield industries in the direction of strengthening production and employment, especially to maintain and strengthen the country's economic strength in difficult economic conditions; they play a very important role. Green Human Resource Management (GHRM) is a topic for small and medium industries in developing economies. In this regard, the research focuses on the backgrounds that support the implementation of GHRM practices in small and medium industries. In this study, an extensive literature review was organized to provide background for the implementation of GHRM practices. Interpretive Structural Modeling (ISM) examines the interactions between identified components. In addition, cross-matrix analysis (MICMAC) was performed to determine the driving power of each component. By reviewing previous research, related texts and experts' opinions, 19 effective components related to green human resource management in relation to small and medium industries in Tehran province were identified. The statistical population of this article was the experts and craftsmen who dominated the research topic, and finally 15 experts and industrial experts collaborated to identify and analyze the factors. The results of structural and interpretive modeling show that the trade union is considered as one of the main stakeholders in environmental management and the main foundation of the model and has high leadership power and low intensity of dependence that must be used for green human resource management. Be emphasized first. The other 18 components, which are in the category of connected components, also have high conductivity and dependence and can affect other components. This model helps managers understand the impact of each component on each other before implementing GHRM practices in small and medium-sized industries.IntroductionIn order to maintain environmental sustainability, the recent trend of companies has been to focus on greening their businesses; for this reason, the philosophy of green human resources has been added to the mission statement of organizations as another critical responsibility of human resource management. Although green human resources are still in their infancy, the increasing awareness of organizations about the importance of green issues has forced them to adopt environmentally friendly human resource practices with a particular focus on waste management, recycling, carbon footprint reduction, and the use and production of green products. It is clear that most employees feel more responsible towards the environment and show more commitment and job satisfaction towards an organization that is always ready to be "green". The effects of HRM practices are multifaceted and require continuous monitoring to discern their potential impact on HRM issues. For this reason, the current research was conducted to identify and evaluate the effective factors of green human resource management in small and medium industries of Tehran province by applying the combined ISM approach. Environmental issues of small and medium industries are considered essential factors for the development of these industries. On the other hand, their activities can lead to environmental problems such as; Gas, liquid, and solid waste pollution.Materials and MethodsThe present study is applied in terms of its purpose and descriptive survey in terms of its nature and method. Regarding collecting research data, the factors and components affecting green human resources management were first identified and extracted by an in-depth literature review and study. The experts of small and medium industries of Tehran form the statistical population of this part of the research. The selection criteria of experts are theoretical mastery, practical experience, willingness and ability to participate in research and access, and 15 of these people with at least a master's degree having at least ten years of management experience in the field of human resources, having enough time to be justified about The nature of research and questionnaire completion techniques; They were chosen by judgment. Experts' opinions regarding verifying factors and components affecting green human resources management have been obtained through the Delphi method. The second data analysis stage is based on the ISM technique to examine and analyze the relationships between the green human resource management indicators confirmed in the previous stage.Discussion and ResultsAccording to the ISM model, the green human resources model consists of 6 levels. The first level and the 6th level are the most effective levels. As one of the main beneficiaries of environmental management, the index of the trade union took the first level position, and the index of strengthening the green empowerment of people took the sixth level position (both of these components are related to the dimension of green participation). According to the results of MICMAC analysis, the index of recognizing the joint role in environmental management between employees, management, and labor unions and the index of the labor union as one of the primary beneficiaries of environmental management are independent variables, with low dependence and high direction. The index of strengthening people's green empowerment is also a dependent variable with strong dependence and weak guidance. This variable has a strong influence and little influence on the system. The main characteristics of these variables are the rest of the indicators of interface type, high dependence, and high guiding power.ConclusionsThe results indicated that the trade union and strengthening the green ability of employees have a prominent role in greening human resource management; the development of valuable environmental programs depends on the amount of response that employees receive about a specific environmental issue. People's participation in organizational green projects leads to better environmental management, efficient use of resources, and reduced waste in the organization. Therefore, it is suggested that Tehran's small and medium industries participate as much as possible in the trade unions in strategic decisions related to environmental activities and benefit from their valuable suggestions. Because trade unions, relying on the role of leadership in directing the behavior of employees, can encourage them to internalize organizational values and use these values to guide their behavior in the workplace. Discovering talents and skills in the employees of a company is an important beginning to strengthening their abilities. Moreover, one of the ways to implement this issue is to involve employees in decisions related to Design, production, packaging, distribution, and support appropriate to the environment.

Yi Zhang, Eric Charles Peterson, Yuen Ling Ng et al.

Raspberry ketone (RK) has high commercial value in the food and healthcare industries. A biological route to this flavour compound is an attractive prospect, considering the need to meet consumer demands and sustainable goals; however, it is yet to become an industrial reality. In this work, fungal production of raspberry ketone (RK) and raspberry compounds (RC) via submerged fermentation of <i>Nidula niveo-tomentosa</i> was characterized in flask, stirred-tank reactor (STR), panel bioreactor (PBR), and fluidized bed reactor (FBR) configurations. The results indicate that the panel bioreactor resulted in larger, floccose pellets accompanied by maximum titres of 20.6 mg/L RK and 50.9 mg/L RC. The stirred-tank bioreactor with impeller mixing yielded compact elliptical pellets, induced the highest volumetric productivity of 2.0 mg L⁻¹ day⁻¹, and showed RK selectivity of 0.45. While differing mixing strategies had clear effects on pellet morphology, RK production presented a more direct positive relationship with cultivation conditions, and showed appropriate mixing and aeration favour RK to raspberry alcohol (RA). Overall, this paper highlights the importance of bioreactor design to fungal fermentation, and gives insight into green and industrial bioproduction of value-added natural compounds.

Eda Bozkurt, Özlem Topçuoğlu, Ali Altıner

Purpose: The sources of economic growth include capital, labor and the Solow surplus, dedicated to the study of Solow (1956). Solow surplus is the inexplicable part of growth with labor and capital and is expressed as technological advances. Solow surplus also means total factor productivity (TFP). In other words, economic growth is explained by TFP depending on technology from the past to the present. These days, digitalization is known to be the new technological revolution. In light of this concept, the study aims to demonstrate the impact of digitalization on TFP. Methodology: A TFP calculation based on the Malmquist index was made using labor, capital and gross domestic product data for 30 countries in the period 2012-2020. The Tobit Panel estimate was then used to determine the effect of digitalization on TFP in the relevant period. Findings: the results of the panel estimate are that digitalization has a significant and positive impact on TFP. The findings suggest that digitalization contributes to productivity. Originality: The most important feature that distinguishes research from studies in the literature is that a verification method is selected that uses real data. In addition, works covering many countries in literature is limited. The research has results from a multi-country perspective.

Didin SE. Fatihudin, Musriha ., Wiwi Wikanta et al.

This research is to analyze the linkage of financial literacy of salt farmers to people's salt production with land, volume, capital sources, market access. Financial literacy is the ability of farmers in understanding various types of financial products/services from the financial industry and able to use. The production of people's salt business (Kugar) has an important contribution to indonesia's national salt production. The quality of people's salt has not been able to meet domestic demand, especially industrial salt. That's what drives salt imports. Research object 7(seven)locations in Cirebon-West Java. Kapetakan, Suranenggala, Gunungjati, Mundu, Losari, Pangenan and Gebang. This region was chosen because it represents the highest salt products in West Java. Descriptive methods, expalanatory, pusposive sampling techniques. Interview and using secondary data from the Marine and Fisheries Service, Central Bureau of Statistics, people's salt business group (kugar), Ministry of Industry and Trade. The results of the study; Financial literacy is still very low. Productivity is also low. 2019 highest disposable salt production 136,695ton, down 2020 only 2,670.78ton. Production costs borrowed by financiers (collectors) from Rp500,000 to Rp1,000,000 with a revenue sharing system. The selling price of salt from farmers to financiers is below the market price between Rp250/kg, Rp300/kg is the highest Rp500/kg. Price of salt from financier to industry Rp1,200/kg, Rp1,500/kg to Rp2,000/kg. Price, market access and capital, salt farmers depend on financiers. Weak financial literacy understanding. The profit of salt is enough for the cost of living. Limited asset deposits in gold, cows, motorcycles. 74 percent of workers. It doesn't have a financial services product. Only know the cooperative and the loan from the collector.

Stefania Cacace, Quirico Semeraro

L-PBF is an additive manufacturing process forming parts with complex geometries by adding material layer by layer. The selection of the process parameters in L-PBF has a significant impact on the mechanical properties of the printed parts. Scan speed, laser power, and hatch distance are among the most influential process parameters in L-PBF because, depending on their combination, different solidification mechanisms take place. However, the procedure for selecting these parameters can be expensive from an experimental point of view. Therefore, it is necessary to identify simplified models that allow fast and reliable optimization of the parameters in L-PBF. Furthermore, the choice of parameters cannot be based exclusively on qualitative aspects but must also consider the productivity of the process to obtain a satisfactory compromise. Increasing productivity leads to the formation of lack of fusion porosity which should be avoided. This paper proposes a procedure for selecting parameters based on a semi-analytical thermal model, which, together with a geometric-based defect model, allows identifying an optimality region where good solidification and productivity are considered. The optimization is carried using a properly defined utility function. The procedure is validated through the production of AISI 316L specimens using an industrial L-PBF system.

Shannay Ayasyifa

Electrical energy is one energy source that plays an essential role in human life daily, such as industrial, commercial, government, and household activities. All processes related to public activities can dash effectively and efficiently with electricity. The electricity consumption in Indonesia has reportedly increased every year. This enhancement can be caused by several factors, one of which is the population. The increasing electricity consumption in Indonesia has shown that electricity is the primary driving sector for the development that supports productivity and public activities. It is hoped that the economy will also increase. Based on this statement, this study aimed to analyze the factors which affect electricity consumption in Indonesia during the 2015 – 2019 period. This study used secondary data by taking four independent variables, including GDRP per capita, population, installed power capacity, and electricity tariffs. The dependent variable used in this study is electricity consumption. The research used the estimation technique of the Fixed Effect Model, which was selected based on the result of the Chow Test. The results in the regression analysis showed that the GDRP per capita and population variable both resulted in positive and insignificant effects on the electricity consumption in Indonesia during the 2015 – 2019 period. The installed power capacity variable had a positive and significant influence on the electricity consumption in Indonesia during the 2015 – 2019 period. Meanwhile, the electricity rate variable had a negative and insignificant effect on the electricity consumption in Indonesia during the 2015 – 2019 period.

Nguyen Ai Nhan, Tran Xuan Thi

Since the implementation of the market economy, innovation and international integration, with the correct guidelines and policies of the Communist Party and the State, Vietnam has rapidly developed industrial parks, attracting a large number of foreign and domestic enterprises came to operate in industrial zones. Having a large number of employees, enterprises operating in industrial zones must pay attention to working conditions and other issues for workers. One of the most important issues of concern is the material and mental life of workers. A sufficient material life when ones’ needs for food, accommodation, clothes, etc. are satisfied allows workers to survive and regenerate their energy for work. A healthy mental life ensures brings positive mood, motivation, attitude and effective working behaviors. Inadequate material and mental life reduces workers’ productivity and thus influences firms’ growth. Ensuring material and mental life for workers in industrial zones is a prerequisite in boosting productivity and achieving sustainable development. This study use survey and interview data to examine the quality of material and mental life of workers in industrial zones in Vietnam. Low income was the main hindrance to a sufficient material life and a rich mental life of workers. In addition, low quality of meal and working conditions had significant impacts to their health. The results were discussed in relation to previous studies on the life of workers in industrial parks.

Abutaleb Varkani motalebi, Ehsan Taghipour, Abutaleb Varkani motalebi

Nowdays, business because of changing the previous economic pattern to global producer pattern, requires different performance preparations. Information technology and its use have produced changes in all sections of organizations. Organizational productivity is one of the Important and key factors in assessing the amount of useful data in industrial productions. In this paper the use of management information system on essential Factors of production organization and the mediator role of organizational productivity among the productive companies have been studied. The research method was descriptive correlation and the sampling method was stratified random one, with 127 managers in Golrang Holding.To analyse the data, trivariate regression was used through increasing organizational productivity was effective in getting the global production class and ranking. <br />

Carlos Eduardo Román Maldonado

This article faces the argument for the acceleration of contemporary social time whose origin is attributed to the colonization of the life world by the expansive and dominant logic of the capitalist system by conditioning all activities, relationships and movements to work, where productivity and effectiveness are oriented to economic growth in a technicized industrial planet. The methodology used is the textual hermeneutics. To conclude the proposal raises to humanize the capitalist economy for humans to colonize social wealth; colonizing the system so that social life is worth living to the fullest.

Juan Hidalgo Sanchez, José Celso Contador, José Luiz Contador

Este artigo relata a metodologia e os resultados da pesquisa empírica qualitativa realizada para identificar os fatores determinantes da competitividade dos principais autoveículos compactos brasileiros produzidos pela Fiat, Ford, General Motors e Volkswagen. Optou-se pela utilização da metodologia prescrita pelo modelo de campos e armas da competição, visto que é qualitativa e quantitativa e consegue representar com bastante clareza as estratégias competitivas de negócios e as operacionais da empresa. Os resultados obtidos confirmaram as hipóteses, validadas segundo o método popperiano dedutivo de prova: 1) não há diferença estatisticamente significativa entre os campos da competição escolhidos para os autoveículos mais competitivos e os escolhidos para os menos competitivos, pois todos eles competem basicamente em projeto, qualidade e preço do produto; e 2) o foco (variável matemática que mede o alinhamento das armas da competição aos campos da competição escolhidos para cada veículo) explica por que um autoveículo é mais competitivo que outro.<br>This article describes the methodology and the results of a study carried out to identify the determinants of competitiveness of the most important compact automotive vehicles produced by the four major car manufacturers operating in Brazil: Fiat, Ford, General Motors and Volkswagen. The methodology chosen was the one suggested by the Fields and Weapons of the Competition model, because it is both qualitative and quantitative, and because it provides a very clear representation of the competitive business and operational strategies of companies. The results validated the hypotheses formulated, and it is possible to conclude that: 1) there is no statistically significant difference between the fields of competition chosen for the more competitive automotive vehicles and the ones chosen for the less competitive, since they all compete primarily on design, quality and price of product; 2) the focus ( the mathematical variable that measures the alignment of the weapons of the competition to the fields of competition chosen for each vehicle) explains why one automotive vehicle is more competitive in relation to the other.

Moacir Godinho Filho, Reha Uzsoy

O presente trabalho apresenta um modelo quantitativo que utiliza de forma híbrida as abordagens System Dynamics - SD (FORRESTER, 1962) e Factory Physics (HOPP; SPEARMAN, 2001) objetivando estudar o efeito conjunto de seis programas de Melhoria Contínua - CI (variabilidade na taxa de chegada, variabilidade do processo, qualidade, tempo até a falha, tempo de reparo e tempo de set up) e de redução de tamanhos de lote de produção nos níveis médios de Estoque em Processo (WIP) e Utilização em um ambiente produtivo com uma única máquina que processa múltiplos produtos. Os resultados dos experimentos realizados utilizando-se o modelo desenvolvido fornecem insights e subsídios que dão suporte a uma série de modernas ferramentas e filosofias de gestão da manufatura, tais como programas de redução da variabilidade do processo como, por exemplo, Seis Sigma; programas de redução de set up, como por exemplo os programas SMED (Single Minute Exchange of Die), Sistema Toyota de Produção/Manufatura Enxuta e Quick Response Manufacturing (QRM). Além disso, o modelo também serve para auxiliar na escolha de diferentes possibilidades de programas de Melhoria Contínua no chão de fábrica.<br>This paper builds a quantitative model, which is a result of a combination of System Dynamics (FORRESTER, 1962) and Factory Physics (HOPP; SPEARMAN, 2001) approaches aiming to examine how six Continuous Improvement (CI) programs (arrival variability, process variability, quality (defect rate), time to failure, repair time, and set up time), together with lot size reduction, affect Work In Process (WIP) and Utilization in a multi-product, single-machine environment. Results of the paper provides support for: i) the importance of implementing set up reduction programs; ii) Lean Manufacturing (LM) philosophy regarding the implementation of small CI programs in a lot of variables and areas of the shop floor; iii) Quick Response Manufacturing (QRM) philosophy regarding the importance of managers to know the convex relationship between lot size and WIP in order to decide the amount of lot size reduction to be performed on shop floor; iv) the choice between alternative CI programs.

Katia Alexandra de Godoi, Stephania Padovani

Neste artigo, discute-se a importância da avaliação de materiais didáticos digitais centrada no usuário. Primeiramente, apresentam-se as abordagens de avaliação passíveis de aplicação a esses materiais, assim como suas definições e classificações. Em seguida, revisam-se conceitos de usabilidade em materiais didáticos digitais. Por fim, descreve-se uma série de instrumentos avaliativos passíveis de serem utilizados por professores.<br>In this study, we discuss the importance of user-centered evaluation of digital learning materials. First of all, different evaluation approaches are introduced, as well as their definitions and classifications. Then, concepts of usability in digital learning materials are surveyed. Finally, a range of evaluation tools subject to use by teachers are described.