Automating Quality Management with SPC Software

Data present the foundational elements for any good quality assurance program. Collected process data can tell food manufacturers how their lines are performing, when there’s a concerning issue or trend, and whether or not products ultimately meet quality and safety standards. With so much insight waiting to be uncovered, it comes as no surprise that most plant-floor teams would want to collect as much data as they can from their various gauges and other equipment.

What that data collection typically involves is far from ideal. Often, you’ll find operators furiously scribbling down measurements onto paper. Some input their handwritten data into spreadsheets. But, given the time-consuming nature of these largely paper-based methods and the sheer amount of information they collect, teams have little time to understand what their data are telling them while production is in process. Thus, many relegate themselves to only a final review after finished goods come off the line.

The challenge with post-production reviews, though, is that if an issue is discovered, teams must shift into firefighting mode, searching far and wide to corral the necessary papers and spreadsheets to understand what went wrong upstream and then (hopefully) contain the problem. Such constant firefighting isn’t the best use of quality and process data, not when manufacturers want to—and can—glean greater operational insights through more advanced, automated means.

Today, food manufacturers can automate many aspects of quality management on the plant floor, including not only data collection, but also process monitoring and even analysis with modern statistical process control (SPC) software. These cloud-based solutions enable quality teams to break away from reactive firefighting and enact real-time, proactive quality control and process improvements.

Automate Data Collection and Issue Detection

In the April/May issue of Food Quality & Safety in an article entitled “Temperature and Humidity” (p. 53), I explained that SPC is an industry standard methodology for measuring and controlling the manufacturing process that involves taking collected process data and plotting it to graphs against pre-determined control limits to identify process variations and ensure optimal quality and consistency. But, rather than having quality professionals produce these graphs themselves, SPC software can do the heavy lifting for them, automatically generating data visualizations for users to review in role-based dashboards. All that remains is for quality professionals to interpret and act on the presented performance information.

Taking full advantage of SPC software and these data visualizations requires manufacturers to drop the paper and pencil and adopt new methods for real-time data collection that goes directly into the system’s own unified data repository. SPC software has advanced backend analysis engines that plot data as it comes in. So, when teams get real-time process- and quality-related data streams into this repository, the data instantly become actionable by identifying sources of process variation, enabling timely detection and remediation of quality issues while production is in process, not after. No more firefighting.

Notably, there are numerous solutions now available for manufacturers to facilitate real-time data collection. There are smart devices, part of the Industrial Internet of Things (IIoT), that can wirelessly collect all the data you need off the production line. Some SPC software directly integrates with a manufacturer’s digital measurement devices, capturing and storing readings into a centralized database.

For those who would prefer to have their operators perform data collection and entry, SPC software can also provide automated notifications to remind them when their next data collections are due. When operators are recording their measurements, pre-defined parameters within the software can enforce best practices, reduce risk of entry error or missed information, and ensure standardization of data entry, with standardization being critical if manufacturers want to conduct any form of comparative analysis between lines, products, or sites.

Automated Alerts & Problem Resolution

From wireless devices to automated notifications, no matter the method for facilitating data collection, they all benefit quality teams at the end of the day. Operators don’t have to worry about getting timely, accurate process information. They also don’t have to glance at the clock constantly to ensure that they make their rounds for quality checks.