Hesitant Fuzzy Linguistic Term and TOPSIS to Assess Lean Performance

Autor: Manuel Iván Rodríguez Borbón, Delia J. Valles-Rosales, Jesús Israel Hernández Hernández, David Luviano-Cruz, Luis Pérez-Domínguez
Rok vydání: 2019
Předmět:
0209 industrial biotechnology
Operations research
Computer science
Fuzzy set
02 engineering and technology
lcsh:Technology
Lean manufacturing
lcsh:Chemistry
020901 industrial engineering & automation
Manufacturing
0202 electrical engineering
electronic engineering
information engineering
General Materials Science
TOPSIS
lcsh:QH301-705.5
Instrumentation
Fluid Flow and Transfer Processes
Flexibility (engineering)
lcsh:T
business.industry
Process Chemistry and Technology
General Engineering
hesitant linsguistic fuzzy term sets
lcsh:QC1-999
Preference
Computer Science Applications
Term (time)
Product (business)
lcsh:Biology (General)
lcsh:QD1-999
lcsh:TA1-2040
020201 artificial intelligence & image processing
lean manufacturing
lcsh:Engineering (General). Civil engineering (General)
business
lcsh:Physics
KPI
Zdroj: Applied Sciences
Volume 9
Issue 5
Applied Sciences, Vol 9, Iss 5, p 873 (2019)
ISSN: 2076-3417
DOI: 10.3390/app9050873
Popis: Manufacturing companies usually expect strategic improvements to focus on reducing both waste and variability in processes, whereas markets demand greater flexibility and low product costs. To deal with this issue, lean manufacturing (LM) emerged as a solution
however, it is often challenging to evaluate its true effect on corporate performance. This challenge can be overcome, nonetheless, by treating it as a multi-criteria problem using the Hesitant Fuzzy linguistic and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method. In fact, the hesitant fuzzy linguistic term sets (HFLTS) is vastly employed in decision-making problems. The main contribution of this work is a method to assess the performance of LM applications in the manufacturing industry using the hesitant fuzzy set and TOPSIS to deal with criteria and attitudes from decision makers regarding such LM applications. At the end of the paper, we present a reasonable study to analyze the obtained results.
Databáze: OpenAIRE
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