About human and learning factors impacting manual picking on assembly lines

Abstract

In the pursuit of competitiveness, human capital remains a critical asset for companies. While automation offers unparalleled production efficiency and error reduction, often surpassing the capabilities of even the most skilled personnel, several factors -such as high initial investment costs, the diversity of products, and other operational complexities- ensure that production systems continue to rely heavily on human involvement as a key resource. This work focuses on assembly workstations, which are integral to a wide range of industries. At these stations, operators perform tasks such as selecting components, assembling parts, verifying outputs, labelling and packaging. The concept of ”pick-to-assemble” is widely discussed in the literature, often accompanied by the use of selection support systems like ”pick-to-light” technology, which assist operators in their tasks. Designing efficient workstations involves considering various factors, including Lean manufacturing principles and ergonomic design. In our study, we prioritized optimizing an assembly line designed to handle multiple product variations. The assistance systems were tailored to adapt to the operator’s level of expertise and experience. By integrating Industry 4.0 concepts, we implemented real-time performance monitoring, enabling the system to dynamically support workers, even when new product references are introduced to the assembly line.