TY - JOUR
T1 - Lean Six Sigma practices supported by Industry 4.0 technologies
T2 - evidence from heavy vehicle manufacturers
AU - Sordan, Juliano Endrigo
AU - Oprime, Pedro Carlos
AU - Pimenta, Marcio Lopes
AU - Andersson, Roy
AU - Antony, Jiju
AU - Garza-Reyes, Jose Arturo
AU - Luz Tortorella, Guilherme
PY - 2024/11/26
Y1 - 2024/11/26
N2 - Purpose: This paper aims to provide empirical evidence regarding Lean Six Sigma (LSS) practices supported by Industry 4.0 (I4.0) technologies in heavy vehicle manufacturing processes. Design/methodology/approach: A two-case study was performed involving LSS specialists, leaders and managers of two heavy vehicle manufacturers in Brazil. The data analysis procedure combined content analysis techniques, conceptual maps and network analysis. Findings: The results provide consistent evidence of synergies between LSS and I4.0, including digital mistake-proofing, digital andon, e-kanban, statistical monitoring as well as process mapping aided by cyber-physical systems (CPS) and big data analytics (BDA). To enable such interactions, companies need to invest in automation architectures, system integration, human–machine interfaces and analytical skills. Research limitations/implications: This study relies on data from a two-case study carried out in two companies from a single manufacturing sector in Brazil. For this reason, the findings cannot be generalized to the entire automotive industry. Originality/value: There is still a lack of comprehensive research on the application of digital technologies in LSS practices. This is the first study which provides empirical evidence regarding the LSS practices supported by I4.0 technologies used by heavy vehicle manufacturers.
AB - Purpose: This paper aims to provide empirical evidence regarding Lean Six Sigma (LSS) practices supported by Industry 4.0 (I4.0) technologies in heavy vehicle manufacturing processes. Design/methodology/approach: A two-case study was performed involving LSS specialists, leaders and managers of two heavy vehicle manufacturers in Brazil. The data analysis procedure combined content analysis techniques, conceptual maps and network analysis. Findings: The results provide consistent evidence of synergies between LSS and I4.0, including digital mistake-proofing, digital andon, e-kanban, statistical monitoring as well as process mapping aided by cyber-physical systems (CPS) and big data analytics (BDA). To enable such interactions, companies need to invest in automation architectures, system integration, human–machine interfaces and analytical skills. Research limitations/implications: This study relies on data from a two-case study carried out in two companies from a single manufacturing sector in Brazil. For this reason, the findings cannot be generalized to the entire automotive industry. Originality/value: There is still a lack of comprehensive research on the application of digital technologies in LSS practices. This is the first study which provides empirical evidence regarding the LSS practices supported by I4.0 technologies used by heavy vehicle manufacturers.
KW - Case study
KW - Industry 4.0
KW - Lean Six Sigma
KW - Operational excellence
KW - Quality 4.0
UR - http://www.scopus.com/inward/record.url?scp=85210418026&partnerID=8YFLogxK
U2 - 10.1108/JMTM-10-2023-0471
DO - 10.1108/JMTM-10-2023-0471
M3 - Article
AN - SCOPUS:85210418026
SN - 1741-038X
SP - 1
EP - 30
JO - Journal of Manufacturing Technology Management
JF - Journal of Manufacturing Technology Management
ER -
