With rapid growth of the global electric vehicle market, interest in the development of secondary batteries such as lithium batteries is also increasing. Core functional parts of secondary batteries are known to determine the performance of these batteries. Micro cracks, scratches, and markings that may occur during the manufacturing process must be checked in advance. As part of developing an automated inspection system based on machine vision, this study optimized the design of a linear feeder exposed to an environment with a specific operating frequency continuously to transfer parts at a constant supply speed. Resonance can occur when the natural frequency and the operating frequency of the linear feeder are within a similar range. It can negatively affect stable supply and the process of finding good or defective products during subsequent vision tests. In this study, vibration characteristics of the linear feeder were analyzed using mode analysis, frequency response analysis, and finite element analysis. An optimal design plan was derived based on this. After evaluating effects on vibration characteristics for structures in which vibrations or periodic loads such as mass and rails were continuously applied, the shape of the optimal linear feeder was presented using RSM.

In response to the market’s need for luxurious automobile interiors, automotive parts makers are developing various types of crash pads to give drivers a sense of emotional luxury. In particular, a low-cost and high-quality crash pad manufacturing technology is being developed for mid- to low-priced vehicles, namely, the IMG-S (In Mold Grain-pre Stitch) technology. High defect rate of stitching is a critical problem during the manufacture of crash pad using the IMG-S technology. In order to solve this problem, this paper proposes a method of real-time machine vision inspection of stitches on the automotive crash pad. This paper presents the real-time machine vision inspection system configuration, proposes stitch and reference line detection methods, and method for calculating the distance between stitches and the reference line. According to the distance between the stitch and the reference line, the status of the stitch was judged as normal, warning, or erroneous, and the final result was displayed on the user interface. The applicability of the proposed real-time machine vision inspection method was verified by stitching the test line.

The fourth industrial revolution is rapidly emerging as a new innovation trend for industrial automation. Accordingly, the demand for inspection equipment is highly increasing and vision sensor technologies are continuously evolving. Machine vision algorithms applied to deep learning are also being rapidly developed to maximize the performance of inspection equipment. In this review, we highlight the recent progress of vision sensor technology for the industrial inspection system. In particular, inspection principles and industrial applications of a vision sensor are classified according to the vision scanning methods. We also discuss machine vision-based inspection techniques containing rule- and deep learning-based image processing algorithms. We believe that this review provides novel approaches for various inspection fields of agriculture, medicine, and manufacturing industries.