Impact of Image Processing on Process Improvement in a Manufacturing Industry

Image data has a significant impact on streamlining production processes by representing visual information, thereby improving overall organizational efficiency. Extracting valuable insights from image data is crucial for monitoring and enhancing statistical processes in manufacturing industries. This study introduces a new method based on image processing and fuzzy transform approach to process improvement in the manufacturing industry. The information is monitored using an exponentially weighted moving average chart (EWMA) control chart to detect change points. Furthermore, a real case study in the tile manufacturing industry, along with various numerical examples, is examined under different scenarios to assess the effectiveness of image processing on process improvement with the proposed method. The results of experimental tests show promising performance for the proposed approach.Image data has a significant impact on streamlining production processes by representing visual information, thereby improving overall organizational efficiency. Extracting valuable insights from image data is crucial for monitoring and enhancing statistical processes in manufacturing industries. This study introduces a new method based on image processing and fuzzy transform approach to process improvement in the manufacturing industry. The information is monitored using an exponentially weighted moving average chart (EWMA) control chart to detect change points. Furthermore, a real case study in the tile manufacturing industry, along with various numerical examples, is examined under different scenarios to assess the effectiveness of image processing on process improvement with the proposed method. The results of experimental tests show promising performance for the proposed approach.

Keywords:

Process improvement , Statistical process monitoring , Image data , Mean square error