Sustainable Evaluation of Production Programs Using a Fuzzy Inference Model - A Concept

Maximilian Zarte, Agnes Pechmann, Isabel L. Nunes

Research output: Contribution to journalConference article

Abstract

Within their lifetime, products and processes pass through characteristic periods, which can be divided into distinct phases, such as design, production, use, and disposal. Specially, the production phase of products consumes a great amount of energy, non-renewable materials, renewable materials, ancillary inputs, and fossil fuels. Moreover, significant amounts of emissions (wastes, effluents, and greenhouse gases) are generated, which lead to sustainable impacts, such as extra costs, environmental damages, social issues. Through a systematic overview of resources and emissions during the production planning process, potential sustainable impacts can be identified and possibly avoided. The paper presents a concept for a fuzzy inference model to evaluate production programs for short- and mid-term production planning according to sustainable indicators. For this approach, the paper presents criteria to select applicable measurements for sustainable production planning, three categories of sustainable indicators to evaluate production programs, a procedure to develop the fuzzy inference model, and possible actions for optimizing production programs to increase the degree of sustainability. In future works, the fuzzy inference model will be implemented in enterprises to demonstrate the benefits of sustainable production planning.

Original languageEnglish
Pages (from-to)241-246
Number of pages6
JournalProcedia CIRP
Volume73
DOIs
Publication statusPublished - 1 Jan 2018
Event10th CIRP Conference on Industrial Product-Service Systems, CIRP IPS2 2018 - Linkoping, Sweden
Duration: 29 May 201831 May 2018

Fingerprint

Fuzzy inference
Planning
Fossil fuels
Greenhouse gases
Sustainable development
Effluents

Keywords

  • Fuzzy Logic
  • Production Planning
  • Sustainable Manufacturing

Cite this

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abstract = "Within their lifetime, products and processes pass through characteristic periods, which can be divided into distinct phases, such as design, production, use, and disposal. Specially, the production phase of products consumes a great amount of energy, non-renewable materials, renewable materials, ancillary inputs, and fossil fuels. Moreover, significant amounts of emissions (wastes, effluents, and greenhouse gases) are generated, which lead to sustainable impacts, such as extra costs, environmental damages, social issues. Through a systematic overview of resources and emissions during the production planning process, potential sustainable impacts can be identified and possibly avoided. The paper presents a concept for a fuzzy inference model to evaluate production programs for short- and mid-term production planning according to sustainable indicators. For this approach, the paper presents criteria to select applicable measurements for sustainable production planning, three categories of sustainable indicators to evaluate production programs, a procedure to develop the fuzzy inference model, and possible actions for optimizing production programs to increase the degree of sustainability. In future works, the fuzzy inference model will be implemented in enterprises to demonstrate the benefits of sustainable production planning.",
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Sustainable Evaluation of Production Programs Using a Fuzzy Inference Model - A Concept. / Zarte, Maximilian; Pechmann, Agnes; Nunes, Isabel L.

In: Procedia CIRP, Vol. 73, 01.01.2018, p. 241-246.

Research output: Contribution to journalConference article

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AB - Within their lifetime, products and processes pass through characteristic periods, which can be divided into distinct phases, such as design, production, use, and disposal. Specially, the production phase of products consumes a great amount of energy, non-renewable materials, renewable materials, ancillary inputs, and fossil fuels. Moreover, significant amounts of emissions (wastes, effluents, and greenhouse gases) are generated, which lead to sustainable impacts, such as extra costs, environmental damages, social issues. Through a systematic overview of resources and emissions during the production planning process, potential sustainable impacts can be identified and possibly avoided. The paper presents a concept for a fuzzy inference model to evaluate production programs for short- and mid-term production planning according to sustainable indicators. For this approach, the paper presents criteria to select applicable measurements for sustainable production planning, three categories of sustainable indicators to evaluate production programs, a procedure to develop the fuzzy inference model, and possible actions for optimizing production programs to increase the degree of sustainability. In future works, the fuzzy inference model will be implemented in enterprises to demonstrate the benefits of sustainable production planning.

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