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Statistical Process Control (SPC) is fundamental to ensuring quality in manufacturing. However, legacy systems prevent manufacturers from harnessing SPC’s true power. 

Modern, cloud-based SPC systems are different. Because they are equipped with advanced capabilities, manufacturers can identify and respond to quality events faster and more efficiently. 

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In this article, you’ll learn why moving to a modern SPC solution—like Enact® by InfinityQS—can help you optimize processes while reducing cost and risk in ways legacy systems can’t. 

SPC in Manufacturing

SPC is an industry-standard methodology for measuring and controlling quality during the manufacturing process. 

Manufacturers typically take a time-ordered data set consisting of measurements of a particular characteristic of a specific part, component, or product. Statistical calculations are then performed on that data to calculate values like mean and standard deviation. 

From there, these data values become visualized plots on a control chart so manufacturers can differentiate and identify special sources of variation. 

Control limits are applied to control charts, and when a measurement value falls outside the set limits, it indicates an unexpected event has occurred. 

Advanced SPC Capabilities

SPC is based on several fundamental tools and methods. But that does not mean that SPC should be limited by only those tools. Not only do advanced SPC solutions provide a greater wealth of statistical calculations and KPIs, but they also provide many more advanced ways to interrogate that statistical data and put that insight to work to add value to manufacturing operations.

Going beyond the traditional approach to statistical calculations and control charts, InfinityQS SPC solutions provide an armory of tools that can be deployed to solve almost any conceivable use case, industry requirement, or problem-solving scenario—such as advanced data analytics and visualization capabilities, and completely new and innovative applications of statistical techniques. 

In the case of InfinityQS Enact, for example, our industry-first Data Stream Grading capability helps organizations summarize manufacturing performance from very specific part-process-feature streams right up to plant-by-plant or region-by-region through a unique and simple 3x3 grading matrix.

Graph: Stream Grading Click on image to enlarge.

Modern quality solutions enable you to get a wealth of information from your statistical analysis. Beyond just measurement, part, processes, or feature data you can also dive into information about the operator, shift, lot number, and more. Mapping the relationship between data and processes, such as through Enact’s Process Models or via Lot Genealogy, for example, turns this data from discrete individual data points into a 360-degree view of manufacturing operations—sort of an “information fabric” woven from all aspects of manufacturing and quality operations.

Advanced SPC: Real-time Data Collection, Analytics, and Notifications

Manufacturing is a real-time activity, so SPC and advanced analytics should be, too.

Consider the effect of variability. If we collect data manually with paper and spreadsheets over time and then batch that data up (prepare it for importing to our SPC tool), import it, and then analyze the results (which is grossly inefficient), then a lot of time passes between the measurement and any statistical insight we may glean. That potentially means a lot of waste, scrap, or downtime.

If we can cut out the middleman, so to speak, and have those measurements enter the SPC solution as they are taken, then each measurement can be evaluated in real time against previous measurements. 

If any specification limit or statistical violation (e.g., limits, zone rules, trends, etc.) is triggered by that measurement, then the operator and other responsible parties can receive immediate feedback of that event, enabling them to take remedial action right away—before problems occur or escalate.

That real-time data can come through automated mechanisms that require no operator interaction or through direct entry at the required time and in the required format.

This real-time data collection capability makes both operators and manufacturing processes much more efficient and enables valuable analysis of process performance and variability.

Just as real-time data collection opens the possibility of real-time SPC, it also opens the door to real-time data analytics. This means interrogating data on the fly and using the right tool for the right question. Most important, it means knowing that the data being interrogated is always accurate and up to date—right up to the point of the last measurement made on the shop floor.

Supervisors, plant managers, and quality executives don’t need to wait for manual reports to be produced and delivered (already out of date the moment they are created). Instead, they can interrogate the data directly either using high-level aggregate analysis dashboards comparing plant-by-plant or product-by-product performance, or dive right into the process-level raw data analysis with just a few clicks of the mouse.

Graph: Analysis Dashboard. Click on image to enlarge.

Advanced Data Analysis and Visualization

SPC tells us when unexpected variation occurs, indicates problems within the production process, and illuminates trends that may impact performance and quality. 

However, a traditional approach to SPC often only focuses on a single part-process-feature combination. It tells us that there is an issue—but not necessarily what the issue might be, or where a particular issue is occurring more or less frequently than others. 

Therefore, by capturing information beyond the measurement-part-process-feature, we can start to interrogate the data in even more ways and use a variety of visualization tools such as Box-and-Whisker plots, animated Bubble charts, and Data Stream Grading.

Graph: Box and Whisker Plot Click on image to enlarge.

Unified Data

When all data is standardized and stored within a single, unified repository, then we can begin to analyze and interrogate data differently.

  • Want to know how a particular feature on a particular product is performing across different production lines or shifts? You might want to use a Box-and-Whisker plot for that.
  • Want to compare different products with different specification limits or feature measurements? Good thing that those Box-and-Whisker charts are normalized for just that reason.
  • Want to know how yield is performing across multiple plants? You might want to use a Grading matrix for that.
  • Want to know how and when quality checks are being performed on time? You might want to use a data collection compliance tile for that.
  • Want to know if your process and products are meeting standards? And how that is evolving over time? You might want to use an animated Bubble chart for that one.
  • Want these questions answered for the last shift? The last day? Last week vs this week? Line 1 vs Line 2? All possible with just a few mouse clicks.

Having these advanced data and analysis capabilities goes far beyond what legacy SPC solutions can provide—and can generate game-changing operational improvements.

Unlock SPC’s Power with Modern Capabilities

Manufacturers using older SPC systems are missing key real-time functionality and advanced features that can help them respond to quality events faster. 

Legacy systems require more time and effort to perform data analysis. By the time a variance or issue is discovered, a line may already have experienced waste, scrap, or downtime.

Modern solutions don’t have those issues. Featuring advanced real-time capabilities, solutions like Enact by InfinityQS unlock the true power of the traditional SPC methodology.   

Want to improve your response to quality events and optimize processes? Read the InfinityQS executive brief 5 Reasons to Overhaul Your Legacy SPC System