Scalable Integration of Machine Vision Systems in FMCG Lines. A study on Lead Time, Planned Downtime and Capital Optimization

In the fast-paced world of Fast-Moving Consumer Goods (FMCG) manufacturing, minimizing planned downtime and optimizing lead time are critical for maintaining high productivity and operational efficiency. With the growing adoption of machine vision systems, their increasing performance capabilities, and the significant reduction in associated costs, these technologies have become the preferred solution for quality control across production lines. Today, almost every quality check is conducted using machine vision systems and the benefits of using these systems over manual inspection are evident: machine vision systems offer higher speed, repeatability, and objectivity, as well as the ability to operate continuously without fatigue. However, the implementation of such systems often necessitates planned downtime, which is challenging to schedule in the highly dynamic FMCG environment. Furthermore, the setup and integration phases can be critical bottlenecks, potentially affecting the entire system’s lead time. Although the use of machine vision technology is widely recognized as a strategic investment to increase productivity, there is a common expectation that the most resource-intensive activities, such as integration and validation, should be confined to pilot lines. The scalability of these systems should, in theory, allow for their rapid deployment on roll-out lines or during the introduction of new Stock Keeping Units (SKUs). Unfortunately, real-world experience frequently deviates from these expectations. For these reasons, this thesis aims to explore the implementation timeline of machine vision applications, with a focus on two distinct scenarios: • The roll-out of solutions previously validated on pilot lines to additional production lines • The introduction of new SKUs on existing lines In each scenario, the study will identify key activities that contribute to planned downtime and those that significantly impact the overall lead time. This investigation will consist in the analysis of actual projects carried out within the oral care production sector, thereby ensuring that the findings are informed by real-world constraints and conditions. The ultimate goal is to propose strategic initiatives to streamline the implementation process.