Integration of Analytic Network Process in Adaptive Lean and Green Processing
Identifikátory výsledku
Kód výsledku v 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>
Výsledek na webu
<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>
Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
Integration of Analytic Network Process in Adaptive Lean and Green Processing
Popis výsledku v původním jazyce
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.
Název v anglickém jazyce
Integration of Analytic Network Process in Adaptive Lean and Green Processing
Popis výsledku anglicky
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.
Klasifikace
Druh
J<sub>SC</sub> - Článek v periodiku v databázi SCOPUS
CEP obor
—
OECD FORD obor
20402 - Chemical process engineering
Návaznosti výsledku
Projekt
<a href="/cs/project/EF16_026%2F0008413" target="_blank" >EF16_026/0008413: Strategické partnerství pro environmentální technologie a produkci energie</a><br>
Návaznosti
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Ostatní
Rok uplatnění
2019
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název periodika
Chemical Engineering Transactions
ISSN
2283-9216
e-ISSN
—
Svazek periodika
76
Číslo periodika v rámci svazku
1
Stát vydavatele periodika
IT - Italská republika
Počet stran výsledku
6
Strana od-do
559-564
Kód UT WoS článku
—
EID výsledku v databázi Scopus
2-s2.0-85076292448