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Wastes identification through Kaizen events: a case study in the automotive sector

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Resumo:The efficient use of lean tools and techniques leads to the reduction of non-value-added activities in production systems. Continuous Improvement (CI) efforts in a workshop format, a.k.a. Kaizen Event (KE), is one of these lean tools. Measuring the gain from KEs has always been a challenge and as a result, firms spend much effort fixing issues that are non-critical or have low or no effect on factory performance, therefore, it is necessary more research on the metrics and the outcomes KE, including waste metrics. This paper presents a case study within a company in the automotive electronics sector to characterize and present outcomes of eight KEs, within which a total of 136 wastes were identified. Categorizing these wastes by groups, results reveal that the “operator motion” is the waste category most frequently noticed by the teams, while “automatic assembly” is the most impactful one in terms of cycle time reduction. While this case study makes a significant contribution in providing empirical evidence of waste in an organization, more research is needed to develop context-specific tools to narrow down the wastes once they have been identified.
Autores principais:Reis, Angelica Muffato
Outros Autores:Sousa, Sérgio; Costa, Lino
Assunto:Kaizen Event Lean manufacturing Wastes
Ano:2023
País:Portugal
Tipo de documento:comunicação em conferência
Tipo de acesso:acesso restrito
Instituição associada:Universidade do Minho
Idioma:inglês
Origem:RepositóriUM - Universidade do Minho
Descrição
Resumo:The efficient use of lean tools and techniques leads to the reduction of non-value-added activities in production systems. Continuous Improvement (CI) efforts in a workshop format, a.k.a. Kaizen Event (KE), is one of these lean tools. Measuring the gain from KEs has always been a challenge and as a result, firms spend much effort fixing issues that are non-critical or have low or no effect on factory performance, therefore, it is necessary more research on the metrics and the outcomes KE, including waste metrics. This paper presents a case study within a company in the automotive electronics sector to characterize and present outcomes of eight KEs, within which a total of 136 wastes were identified. Categorizing these wastes by groups, results reveal that the “operator motion” is the waste category most frequently noticed by the teams, while “automatic assembly” is the most impactful one in terms of cycle time reduction. While this case study makes a significant contribution in providing empirical evidence of waste in an organization, more research is needed to develop context-specific tools to narrow down the wastes once they have been identified.