Verification of the Measurement System in a Production Organization

Prístavka, Miroslav; Findura, Pavol; Beloev, Ivan; Kuboń, Maciej; Hrdá, Veronika; Kovalyshyn, Stepan; Shchur, Taras

doi:10.2478/agriceng-2022-0007

Cited by 2 publications

(3 citation statements)

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“…Depending on the availability of resources and the purpose of the study, one or more methods can be used to collect data on the generation of household organic waste in a given area [52][53][54][55][56][57].…”

Section: An Approach To Assessing the State Of Organic Waste Generati...mentioning

confidence: 99%

An Approach to Assessing the State of Organic Waste Generation in Community Households Based on Associative Learning

Tryhuba,

Hutsol,

Tryhuba

et al. 2023

Sustainability

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The purpose of this work is to substantiate the approach to assessing the state of organic waste generation by households of a given community, which is based on passive production observations and intellectual analysis of statistical data, which ensures consideration of the factors and features of organic waste generation, as well as the development of qualitative models for forecasting their receipt. To achieve the goal, the following tasks were solved: the analysis of the state of organic waste generation by households in the EU countries was performed; an approach to assessing the state of organic waste generation by households of a given community is proposed; based on the use of the proposed approach, and models for assessing the state of organic waste generation of households in a given community were substantiated. The hypothesis of the study is to substantiate and use an approach to assessing the generation of organic waste by households in individual communities, based on the method of association learning and search for association rules, which will identify factors that have a significant impact on the volume of organic waste generated by households, the consideration of which will improve the accuracy of forecasting models and improve the quality of management of the processes of collection and processing of this waste in communities. The research methodology used allows for the use of data mining, probability theory, mathematical statistics, machine learning technology, and the Associative Rule Learning (ARL) method. Based on the use of a reasonable algorithm, they identify key trends and relationships between the factors of organic waste generation in communities in different countries, which is the basis for creating accurate models for predicting the volume of collection and processing of this waste in communities. The study found that the largest number of households produced organic waste per capita in the range of 0.14–0.25 kg/person. At the same time, most households have from two to four residents and are located on the adjoining territory from 350 m2 to 680 m2. Based on the method of learning associative rules, it was found that there are no close correlations between individual factors that determine the daily volume of organic waste generation by households per capita. The highest correlation coefficient between the type of housing and the income level of household residents is 0.13. The number of residents and the occupied area of the adjacent territory have the greatest impact on the daily volume of organic waste generated by households per capita. The substantiated associative rules of relationships, as well as the diagrams of relationships between factors, have helped to identify those factors that have the greatest impact on the volume of organic waste generation. They are the basis for creating accurate models for predicting the volume of collection and planning the processing of this waste in communities. Based on the proposed approach, Python 3.9 software was developed. It makes it possible to quickly carry out calculations and perform a quantitative assessment of the state of organic waste generation by households of a given community according to the specified rules of association between the volumes of organic waste generation and their factors. The results of the study are the basis for the further development of models for accurate forecasting of the collection and planning of the processing of organic waste from households in communities.

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Section: An Approach To Assessing the State Of Organic Waste Generati...mentioning

confidence: 99%

An Approach to Assessing the State of Organic Waste Generation in Community Households Based on Associative Learning

Tryhuba,

Hutsol,

Tryhuba

et al. 2023

Sustainability

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“…Since the process cannot be started until the long-term goals of the enterprise are set, we considered a SWOT analysis for this purpose. It was also necessary to conduct an audit of the production processes; i.e., a survey of production capacity, the results of which served as a basis for assessing production capacity and identifying opportunities and needs for its increase or change of character [37]. In this regard, the product portfolio should be considered as allowing for the leading performance indicators such as contribution to income, contribution to expenses, and share in the range.…”

Section: Conceptual Frameworkmentioning

confidence: 99%

“…The scope of the company's products provides the general profile of the enterprises interested in the growing of almonds. Other characteristics of an enterprise might include focusing on producing goods and marketing them directly to consumers, the acreage, the way an enterprise is run (as a sole proprietorships or otherwise), and work in tandem with market gardens and greenhouses [37].…”

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confidence: 99%

Innovative Almond-Growing Strategy in Ukraine: Enterprise Level

et al. 2023

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Almond production in Ukraine is undergoing the process of formation. There is an urgent need to study the almond market in Ukraine, including the formation of production strategies. A content analysis of the scientific literature was used to single out the general approach for enterprise strategy development. With a view toward determining the regions in Ukraine with the most concentrated production of almonds, a cluster analysis was carried out. To maintain the SWOT analysis for the producers of almonds in Ukraine, a factor analysis was conducted. The incoming data for the factor analysis was obtained by surveying 98 domestic almond companies. For the development of product-based conceptual models, frequency analysis and multiple-choice analysis were applied. The main results included a conceptual model of the product portfolio, a generalized product portfolio for nut-producing enterprises in Ukraine, and a strategic approach for an almond-growing enterprise in Ukraine. Given the most promising regions for almond growing in Ukraine, the main SWOT analysis results outlined the broad prospects: lack of competition, high demand, and government support along with weak sector organization and opportunistic strategy. In addition, almond production fell under the investment production category, which was considered to require new employees.

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Verification of the Measurement System in a Production Organization

Cited by 2 publications

References 4 publications

An Approach to Assessing the State of Organic Waste Generation in Community Households Based on Associative Learning

An Approach to Assessing the State of Organic Waste Generation in Community Households Based on Associative Learning

Innovative Almond-Growing Strategy in Ukraine: Enterprise Level

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