Application of Industry 4.0, Digital Transformation, and Lean Six Sigma to Detect Cold Weld Defects

Industry 4.0 and digital transformation are two concepts related to the connection of people, machines, objects, and information technology systems to value creation. For example, the application of real-time data analysis to predict process behaviors, obtaining a radical organizational performance improvement. On the other hand, Lean Six Sigma (LSS) is a continuous improvement approach that integrates philosophies from Lean (waste reduction) and Six Sigma (process variation reduction) using DMAIC problem-solving methodology. Although Industry 4.0, digital transformation, and LSS are different ways of organizational value creation, there is a lack of literature describing how industries are using these three approaches to increase their competitiveness. Therefore, the purpose of this research is to demonstrate how philosophies, methodologies, and tools from Industry 4.0, digital transformation, and LSS could be integrated to achieve organizational excellence. To reach this aim, the authors conducted action research to improve cold weld defects detection in a steel pipe manufacturing company (SPMC) using DMAIC, CRISP-DM methodology (data mining methodology), analytics, software programming (Phyton), and metallographic picture analysis in real-time. This improvement project gave the SPMC the opportunity to detect 87% of the cold weld defects and reduce employee inspection errors. Within the present investigation, the most relevant limitations were the accessibility, data cleansing, and data trustworthiness, which are critical criteria to assess data quality. Data processing and data engineering were used to mitigate these limitations. Practitioners could use the following action research as a guideline to integrate Industry 4.0, digital transformation, and LSS to obtain radical process improvement by analyzing real-time data.