Internal Logistics Process Improvement using PDCA: A Case Study in the Automotive Sector

Authors

  • Vitória Amaral COMEGI, Universidade Lusíada
  • Ana C. Ferreira COMEGI, Universidade Lusíada and ALGORITMI, MEtRICs, University of Minho
  • Bruna Ramos COMEGI, Universidade Lusíada and ALGORITMI, University of Minho

Keywords:

PDCA, Continuous improvement, Logistics, Milk-run, Automotive sector

Abstract

Background: The Plan-do-check-act (PDCA) cycle methodology for a continuous improvement project implementation aims for the internal logistics upgrade, which is especially important in the industrial context of a component manufacturing company for the automotive sector. Objectives: The goal is to quantify the gains from waste reduction based on the usage of the PDCA cycle as a tool in the implementation and optimisation of a milk run in an assembly line of a company in the automotive sector by determining the optimal cycle time of supply and the standardisation of the logistic supply process and the materials’ flow. Methods/Approach: The research was conducted through observation and data collection in loco, involving two main phases: planning and implementation. According to the phases of the PDCA cycle, the process was analysed, and tools such as the SIPOC matrix, process stratification, 5S, and visual management were implemented. Results: Using Lean tools, it was possible to reduce waste by establishing concise flows and defining a supply pattern, which resulted in a reduction of movements. The transportation waste was reduced by fixing the position of more than half of the materials in the logistic trailers. The developed Excel simulator provided the logistic train's optimal cycle time. Conclusions: The assembly line supplied by milk-run was fundamental to highlight a range of improvements in the process of internal supply, such as better integration of stock management systems, greater application of quality, or the adoption of better communication systems between the different areas and employees.

Downloads

Published

2022-12-18