Manual vs. Automated Statistical Process Control Food...

Israel Ortega-Ramos The Prime Example Our recent visit to a food packaging plant in New Jersey highlighted the inconsistent results of statistical process control routinely faced by Quality Control Managers. Product weight readings were taken from the manufacturing floor, entered into an Excel spreadsheet and analyzed. The results produced no predictable under or over filling trend despite the fact that the same people used the same scales at the same time of day. The problem is simple and fundamental. Human error is an inevitable part of the process of collecting statistical data. This is consistently overlooked in companies that utilize manual SPC[1] (statistical process control) for their manufactured goods. To ensure the†¦show more content†¦The scale will then calculate the statistical data after the last product is placed on the scale and store this data in a password-protected memory for collection by the Quality Manager. This statistical data can then be sent wirelessly to a spreadsheet, printed on a label to accompany the sampled product, or simply viewed on the scale interface. The flow diagram below shows the improved SPC process. Companies can also utilize various connectivity and software options that can integrate filling machines to automated SPC scale systems. This means that fill volumes based on trends calculated by the scale can be adjusted via an automated system. Quality Control Managers and Plant Managers can also connect all the SPC scale systems in a factory via a central control computer that will provide easy access to â€Å"real-time† data. Integrating an automated SPC Scale System into a manufacturing environment will have the following advantages over the older manual SPC systems: Upgrading outdated manual SPC processes is the first step to improve overall quality, efficiency, and trace ability. This can be accomplished with as little as $5,000 in capital investment. Quality Control Managers and Plant managers have to take a hard look at how their product samples are being weighed and how these measurements are turned into results that can improve production line efficiency. 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