Analysis of Kanban Systems for Enhanced Operational Efficiency - A Case Study at Nexans

Abstract

The purpose of this thesis is to analyze and optimize the Kanban system in use at Nexans, specifically focusing on production line 522. The aim is to enhance operational efficiency, reduce waste, and improve inventory management. The study covers the current Kanban process, identifies inefficiencies, and develops targeted optimization strategies. The methodology involves conducting site visits, interviewing key personnel, and collecting production data from 2023. A detailed process map was created to analyze production flow, and data was processed using MATLAB for predictive modeling. The analysis includes performance metrics for key production stations, such as average production time, stop time, and setup time, enabling the identification of bottlenecks. The results show significant disparities between Kanban and non-Kanban articles in terms of production time and order volume. Non-Kanban articles often outnumbered Kanban items in terms of orders, highlighting the need for re-evaluation of the Kanban selection. The study found that optimizing machine allocation and updating the Kanban article list can lead to substantial improvements in production flow. The study concludes with recommendations for Nexans to refine its Kanban system by incorporating predictive demand models and prioritizing more efficient machine utilization. The findings provide actionable insights that can support Nexans in streamlining its production processes and improving operational responsiveness.