An Empirical Research on Lean Production Awareness: The Sample of Gaziantep

Gelmez, Emel; Özceylan, Eren; Mete, Süleyman; Durmuşoğlu, Alptekin

doi:10.1007/s42943-020-00010-8

Cited by 5 publications

(1 citation statement)

References 39 publications

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“…Moreover, implementation of LM spread out other industries, including textiles, construction, food, medical, electricity and electronics, ceramic industry, plywood, furniture, slippers, shell, and the service industry [5,6,7,8,9]. Currently, there are seven types of waste, namely overproduction, waiting, transportation, excess processing, inventories, motion, and defects [10] However, following the times and the development of needs, the seven wastes are developed into eight [11]. Eight wastes have now been widely applied in various sectors, including Higher Education Institution (HEI).…”

Section: Introductionmentioning

confidence: 99%

Lean Waste Identification in Higher Education Institution Using Waste Assessment Model

Mulyana

Hartanti

Herdianto

et al. 2022

Management Systems in Production Engineering

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Lean is a philosophy that is seen as a solution to resolve the problem of efficiency in various industries. It can be used to eliminate all forms of waste in the workplace. The implementation of lean is not only applied in manufacturing but is very important to be applied in other fields, such as in Higher Education Institution. Studies on the topic of lean in the workplace have been carried out, but most of the study has been conducted within a manufacturing context. This study aims to determine the type of waste that is most important to be eliminated first by using the Waste Assessment Model and find the root of the waste problem. This study developed the relationship between waste and find out the effect of waste on each other in Higher Education Institution that focused on teaching and learning process. The steps of this study consist of three-step, such as waste identification, waste assessment, and root cause analysis. From data collection show that there are 46 forms of waste in the teaching and learning process. The results of the Waste Relationship Matrix showed three types of waste must be removed first, namely overproduction, defects, and non-utilized talents. 5-Why’s is used to find out the root causes of waste which is the most important to be eliminated first in the teaching and learning process.

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Section: Introductionmentioning

confidence: 99%

Lean Waste Identification in Higher Education Institution Using Waste Assessment Model

Mulyana

Hartanti

Herdianto

et al. 2022

Management Systems in Production Engineering

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Hierarchy of Critical Success Factors (CSF) for Lean Six Sigma (LSS) in Quality 4.0

Yadav

Shankar

Singh

2021

JGBC

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The fourth industrial revolution, often termed as Industry 4.0 or Smart Manufacturing, is influencing all aspects of business management. Application of Industry 4.0 for quality management purpose is termed Quality 4.0. Lean Six Sigma (LSS) implementation process is also getting influenced by Quality 4.0. Use of Lean Six Sigma in Industry 4.0/Quality 4.0 can create differentiation in performance, and will improve competitiveness of organizations, besides making them future ready. Critical Success Factors (CSF) for Lean Six Sigma in Quality 4.0 set-up are recently established. However, the hierarchy of Critical Success Factors (CSF) for Lean Six Sigma under Quality 4.0 framework is not yet available. This paper establishes the hierarchy using multiple methodologies including ISM (Interpretive Structural Modelling) and TISM (Total Interpretive Structural Modelling), MICMAC (cross-impact matrix multiplication applied to classification), and Hierarchical Clustering. Managerial and theoretical implications of this study are presented from both Lean Six Sigma, and Information Technology perspectives.

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Modeling the Factors of Productivity in Airline Industry in India: A Hybrid TISM-P and Fuzzy-MICMAC Approach

Garg

Thakur

2021

JGBC

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The present study explores the productivity drivers of the airline industry in India for their national and international performance. Interpretive structural modeling with polarity (TISM-P) approach is opted for exploring the interrelationships among productivity drivers of the airline industry by considering the experts’ inputs. The study identified 17 factors driving the productivity of the airline industry, and experts’ inputs had placed them in nine levels using a TISM-P approach . Fuzzy-MICMAC (Matrice d’impacts croisés multiplication appliquée á un classment) analysis further has classified these 17 factors into the following four groups: autonomous, dependent, linkage, and independent group. Also, it is observed that refining productivity issues have increased the airline industry’s export performance. The airlines’ administration can plan the short-term objectives by considering the independent factors and long-term policies by focussing on the linkage and dependent factors for improving the overall productivity and export performance. Supplementary Information The online version contains supplementary material available at 10.1007/s42943-021-00035-7.

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An Empirical Research on Lean Production Awareness: The Sample of Gaziantep

Cited by 5 publications

References 39 publications

Lean Waste Identification in Higher Education Institution Using Waste Assessment Model

Lean Waste Identification in Higher Education Institution Using Waste Assessment Model

Hierarchy of Critical Success Factors (CSF) for Lean Six Sigma (LSS) in Quality 4.0

Modeling the Factors of Productivity in Airline Industry in India: A Hybrid TISM-P and Fuzzy-MICMAC Approach

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