Improving the Efficiency of Plastic Bottle-Blowing Machines in the Fish Sauce Packaging Production Process: A Case Study of a Packaging Company

Abstract

This research aims to improve the performance of the bottle-blowing machine for packaging fish sauce products by reducing defects and machine downtime. From the data collection on the plastic bottle-blowing manufacturing process, two types of bottles were identified: the first type is a round bottle with capacities of 700 and 750 milliliters, and the second type is a square bottle with a capacity of 700 milliliters. According to the data in the three months before the production process improvement. There were 1,105,515 pieces of production, 23,365 pieces of defect (or 2.11% of production), and the machine downtime had four stoppages with a total of 5,760 minutes. To identify the factors affecting the plastic bottle production process, the studies used the fishbone diagram as a tool to analyze the causes of the problems. It was found that the main cause of defects came from the deformation of the machine’s stretch rod unit. The stretch rod stretches the preform after it has been heated and softened, while air pressure is used to blow into the stretched preform tube. When the rod becomes deformed, the expansion becomes uneven, leading to bottle shapes that do not match the intended design. The result of the production process improvement and preventive maintenance planning of the stretching rod unit in the three months after the production process improvement. There were 1,002,655 pieces of production and 8,902 pieces of defect (or 0.89% of production). This represents a reduction of 14,463 pieces of defect (or 61.89% of defect) from the total number of defects. Therefore, the preventive maintenance planning for the stretching rod unit could significantly reduce the defects from the plastic bottle production process, and the machine availability rate increased from 90% to 99.92%, indicating that a planned preventive maintenance schedule can effectively reduce the frequency and duration of machine downtime.