Selection of Production Mix in the Agricultural Machinery Industry Considering Sustainability in Decision Making

Competition among companies is growing globally, with the need to increase productivity and efficiency in the product sector. However, there is also a growing concern about global warming and the depletion of natural resources, as well as their effects on human health. In this context, all human act...

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Main Authors: Anderson Hoose, Víctor Yepes, Moacir Kripka
Format: Article
Language:English
Published: MDPI AG 2021-08-01
Series:Sustainability
Subjects:
Online Access:https://www.mdpi.com/2071-1050/13/16/9110
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spelling doaj-af46b9a0dd5246dea8ae05a043fc7c8a2021-08-26T14:22:05ZengMDPI AGSustainability2071-10502021-08-01139110911010.3390/su13169110Selection of Production Mix in the Agricultural Machinery Industry Considering Sustainability in Decision MakingAnderson Hoose0Víctor Yepes1Moacir Kripka2Civil and Environmental Engineering Graduate Program (PPGEng), University of Passo Fundo, Passo Fundo 99052-900, BrazilInstitute of Concrete Science and Technology (ICITECH), Universitat Politècnica de València, 46022 Valencia, SpainCivil and Environmental Engineering Graduate Program (PPGEng), University of Passo Fundo, Passo Fundo 99052-900, BrazilCompetition among companies is growing globally, with the need to increase productivity and efficiency in the product sector. However, there is also a growing concern about global warming and the depletion of natural resources, as well as their effects on human health. In this context, all human activities that involve intense usage of resources must take into account sustainability as one of the decision criteria. This work presents the application of decision-making methods to define the best product mix in the agricultural machinery industry. With this objective, the current schedule of the production line was identified, along with the production flow, by performing an inventory analysis and an environmental impact study (endpoint). A total of seven alternatives for the production mix of grain trailers were defined, considering different materials and production processes. The selection of the best schedule according to the different criteria was performed through the analytic hierarchy process (AHP) and data envelopment analysis (DEA) to evaluate the managerial implications for decision making. The results obtained through AHP identified a single alternative as being the best, which facilitates the decision making. The DEA method identified two alternatives as the most efficient, and in this case the manager can choose between a product mix that generates lesser environmental impact or greater profitability. Although applied to agricultural industry, the presented methodology can be easily adapted to other activities related to the built environment, such as construction industry.https://www.mdpi.com/2071-1050/13/16/9110analytic hierarchy process (AHP)data envelopment analysis (DEA)sustainabilityproduct mixagricultural industrydecision making
collection DOAJ
language English
format Article
sources DOAJ
author Anderson Hoose
Víctor Yepes
Moacir Kripka
spellingShingle Anderson Hoose
Víctor Yepes
Moacir Kripka
Selection of Production Mix in the Agricultural Machinery Industry Considering Sustainability in Decision Making
Sustainability
analytic hierarchy process (AHP)
data envelopment analysis (DEA)
sustainability
product mix
agricultural industry
decision making
author_facet Anderson Hoose
Víctor Yepes
Moacir Kripka
author_sort Anderson Hoose
title Selection of Production Mix in the Agricultural Machinery Industry Considering Sustainability in Decision Making
title_short Selection of Production Mix in the Agricultural Machinery Industry Considering Sustainability in Decision Making
title_full Selection of Production Mix in the Agricultural Machinery Industry Considering Sustainability in Decision Making
title_fullStr Selection of Production Mix in the Agricultural Machinery Industry Considering Sustainability in Decision Making
title_full_unstemmed Selection of Production Mix in the Agricultural Machinery Industry Considering Sustainability in Decision Making
title_sort selection of production mix in the agricultural machinery industry considering sustainability in decision making
publisher MDPI AG
series Sustainability
issn 2071-1050
publishDate 2021-08-01
description Competition among companies is growing globally, with the need to increase productivity and efficiency in the product sector. However, there is also a growing concern about global warming and the depletion of natural resources, as well as their effects on human health. In this context, all human activities that involve intense usage of resources must take into account sustainability as one of the decision criteria. This work presents the application of decision-making methods to define the best product mix in the agricultural machinery industry. With this objective, the current schedule of the production line was identified, along with the production flow, by performing an inventory analysis and an environmental impact study (endpoint). A total of seven alternatives for the production mix of grain trailers were defined, considering different materials and production processes. The selection of the best schedule according to the different criteria was performed through the analytic hierarchy process (AHP) and data envelopment analysis (DEA) to evaluate the managerial implications for decision making. The results obtained through AHP identified a single alternative as being the best, which facilitates the decision making. The DEA method identified two alternatives as the most efficient, and in this case the manager can choose between a product mix that generates lesser environmental impact or greater profitability. Although applied to agricultural industry, the presented methodology can be easily adapted to other activities related to the built environment, such as construction industry.
topic analytic hierarchy process (AHP)
data envelopment analysis (DEA)
sustainability
product mix
agricultural industry
decision making
url https://www.mdpi.com/2071-1050/13/16/9110
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