Integration of Analytic Network Process in Adaptive Lean and Green Processing

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26210%2F19%3APU134376" target="_blank" >RIV/00216305:26210/19:PU134376 - isvavai.cz</a>

Result on the web

<a href="https://www.aidic.it/cet/19/76/094.pdf" target="_blank" >https://www.aidic.it/cet/19/76/094.pdf</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.3303/CET1976094" target="_blank" >10.3303/CET1976094</a>

Result language

angličtina

Original language name

Integration of Analytic Network Process in Adaptive Lean and Green Processing

Original language description

The manufacturing and processing industry have been an important part of the global economy. Many industry players are constantly looking for an alternative to improve their operation and environmental performance to remain competitive in the market. The lean and green approach aims to reduce operation and environmental waste within an organisation. In this study, a lean and green framework is proposed to evaluate the industrialist performance to achieve higher performance efficiency and reduce environmental impact. Three main clusters are incorporated in the framework such as environment, machine and resources. The analytic network process (ANP) method is used to establish the relationship between the three clusters with the input from industry expert from the respective field. A lean and green index is developed from the ANP model as a benchmarking for the industrialist. Backpropagation method is utilized as the continuous analysis tools to analyse the performance of the organization accordingly to the time step. The adaptive characteristic of backpropagation method is reflected from the ability for continuous improvement with time. In this study, the lean and green index will be further optimized with the adaptive approach. This paper proposes an adaptive model that can improve the industry’s performance and practise continuous improvement through establishing the adaptive approach.

Czech name

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Czech description

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Type

J_SC - Article in a specialist periodical, which is included in the SCOPUS database

CEP classification

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OECD FORD branch

20402 - Chemical process engineering

Project

<a href="/en/project/EF16_026%2F0008413" target="_blank" >EF16_026/0008413: Strategic Partnership for Environmental Technologies and Energy Production</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2019

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Chemical Engineering Transactions

ISSN

2283-9216

e-ISSN

—

Volume of the periodical

76

Issue of the periodical within the volume

1

Country of publishing house

IT - ITALY

Number of pages

6

Pages from-to

559-564

UT code for WoS article

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EID of the result in the Scopus database

2-s2.0-85076292448