Improving quality control for food containers
Description of the Problem
A company producing poorly manufactured products will eventually lose sales and market share; manufacturers of vacuum-sealed food storage containers are no exception. Containers with faulty seals subject consumers to the possibility of food poisoning. Endangering public health inevitably exposes corporations to negative publicity or even lawsuits. Hence, quality control issues for food container manufacturers are crucial. Yet even the most proficient quality control staff cannot improve products without first determining the quality of current products. Determining quality and making these improvements requires accurate data from thousands of samples.
The Solution using OPTIMAS
Using OPTIMAS, companies can take advantage of a simple camera and a Windows-based PC to streamline the process of collecting valuable quality control data. For example, quality control departments use OPTIMAS macros to collect spatial measurement data about vacuum-sealed food storage containers. This data is stored in ASCII format on the PC and is transferred later to a VAX computer for performing statistical analysis. Analyzing this information allows quality control engineers to effectively determine which manufacturing processes, if any, require modification.
With OPTIMAS, measurements are extracted from cross-sectional images of individual containers. By using OPTIMAS, this measurement process can be run by temporary workers instead of expensive engineers. These operators simply turn on the computer and are immediately directed into the OPTIMAS data collection macro. Operators enter their name and various container information. Prompting the operators with messages, OPTIMAS instructs them to position container cross-sections in front of the camera, and then guides them through the process of making measurements. The required measurement data is collected automatically and saved to disk. OPTIMAS provides an automated method for reducing human error, increasing measurement accuracy, and providing the large sample base necessary for doing accurate statistical analysis.