An inspection system to master dimensional and technological variability of fashion-related products: A case study in the eyewear industry

Abstract

Innovation of fashion-related products implies the continuous search for new and appealing shapes and materials in a short period of time due to the seasonality of the market. The design and manufacturing of such products have to deal with a dimensional variability as a consequence of the new shapes. An additional difficulty concerns properly forecasting the technological behaviour of the new materials in relation to the manufacturing process phases. The control of dimensional variations requires time and resource intensive activities. Human's manual and visual inspection solutions are more common than automatic ones for performing such control, where skilled operators are typically the only ones capable of immediately facing non-standard situations. The full control of such variations is even more subtle and mandatory in the field of spectacles, which are fashion-related products and also medical devices. This paper describes an inspection system developed to monitor the dimensional variations of a spectacles frame during the manufacturing process. We discuss the methodological approach followed to develop the system, and the experimental campaign carried out to test its effectiveness. The system intends to be an alternative to current inspection practices used in the field, and also to provide a methodological approach to enable engineers to systematically study the correlations existing among the frame main functional and dimensional parameters, the material behaviour and the technological variables of the manufacturing process. Hence, the system can be considered a method to systematically acquire and formalise new knowledge. The inspection system consists of a workbench equipped with four high-quality commercial webcams that are used to acquire orthogonal-view images of the front of the frame. A software module controls the system and allows the automatic processing of the images acquired, in order to extract the dimensional data of the frame which are relevant for the analysis. A case study is discussed to demonstrate the system performances.