“…Moreover, surface defect prediction from different aspects, i.e., texture, color, and shape features, is possible in industrial products based on machine learning techniques [38]. Fault prediction is applied in different areas such as manufacturing [39][40][41], health [42], transportation [43], seismology [44], power systems [45], telecommunication networks [46], chemistry [47], electrical machines [48,49], energy [50], and environmental work [51]. In this study, fault prediction is applied to the manufacturing process, in which the accurate investigation of products is essentially considered to reduce processing cost and time, and improve product design and quality.…”