SPC Software: How it improves Quality in Manufacturing?

Tiffany M. Donica
Continuous Improvement Coach

Statistical Process Control (SPC) is a type of quality control practice that uses statistical methods to monitor and control a process. It allows manufacturing facilities to observe and manage behaviors, uncover bottlenecks, and discover solutions for production problems.

We can trace much of the SPC we see today in modern facilities back to World War II when products such as munitions called for stringent quality measures. SPC methods have seen a significant resurgence in recent years, especially with initiatives such as Six Sigma, a method used to improve the capability of business processes. One hallmark characteristic of SPC is the control chart, which Walter Shewart first developed in the 1920s.

What Does SPC Mean in Quality?

Implementing SPC means manufacturers can move away from a detection-based quality control method to a prevention-based form of quality control. Traditionally, many companies followed production with inspections to ascertain quality levels. While many manufacturers do still utilize inspections, an SPC-based approach means using graphs that help manufacturers predict process variables and outcomes. As the cost of raw materials rises in many manufacturing sectors, so does the cost of scrap or rework. SPC minimizes rework and helps to streamline all processes related to the product. Ultimately, SPC can help inform your quality improvement initiatives by helping you determine whether you should focus on preventing an isolated problem or rework a process entirely.

SPC Quality Charts

Also known as a Shewhart chart, an SPC control chart monitors how processes change over time. Data points are plotted based on time, and there is a central line to indicate the average and an upper and lower line to depict control limits. Analyzing these data points allows manufacturers to determine whether process variation is consistent, in control, or unpredictable. When a process is deemed unpredictable, it means that it is out of control and impacted by special causes of variation. For a quick video on how it works, watch this introduction video about SPC: What is it, and why is it needed? 

SPC Control Charts are Useful for:

  • Identifying problems as they occur for prompt correction

  • Predicting the anticipated range of outcomes for a process

  • Finding out if a particular process is considered stable

  • Drilling down into process variation caused by special causes, including non-routine events versus common causes which occur naturally within the process

The first thing to think about is that all processes will exhibit some amount of variation, which forms the very foundation for SPC charting. In general, there are two types of process variations, consistent and unpredictable. Understanding which process variations are happening will allow you to know what actions to take to ensure quality. 

The Two Types of Process Variations

As mentioned above, process variations can fall into one of two categories.

  1. Consistent: Common cause variations are ever-present and intrinsic to a process.

  2. Unpredictable: Special cause or assignable variations result from external conditions and are thus out of the realm of statistical control.

Common cause variation, sometimes called “noise variation,” impacts all outcomes of a process and everyone involved in it. To manage this type of variation, manufacturers must therefore focus on the process itself. Common cause variations can either be addressed by making a change or by management. Management can identify common cause variation using control charts. A process can be consistent and in control and also be creating an unsatisfactory product.

On the other hand, special cause variation (or “signal cause variation”) is not inherent in the process. To address these variations, manufacturers must identify and address the special cause. Quality assurance analysts often remove special cause variations. There is a risk involved with making adjustments when a process is in control. This tampering with the process can actually increase variation and move the process away from the quality target.

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How Can SPC Improve the Quality of a Product?

Being able to identify the quality challenges in your facility is essential for customer satisfaction, standard and program compliance, and beyond. Through SPC, you can determine which aspects of your production need fine-tuning and where you should direct your efforts. There are fewer wasted movements in SPC because everything is quality-target oriented. SPC charts are a valuable tool for helping manufacturers better understand trends in their facilities. Manufacturers today can implement SPC software to make real-time adjustments and further improve efficiency. For instance, SafetyChain’s SPC software allows manufacturers to set customized specification ranges to ensure targets are met. 

Using SPC also provides a solid, factual basis for change that makes sense to operators and engineers who are directly involved in the process. What an operator may do based on their ‘gut feeling’ may actually be borne out by a control chart. Sometimes, however, the opposite is true. Altering the ways operators have always done things can feel less confrontational when backed up by precise data to which everyone involved has access. A software platform helps deliver that data to everyone in terms they can understand so that everyone with a stake can make accurate decisions that are less vested in emotion and, thus, far more likely to succeed.

Specification Limits—The Voice of the Customer

The limits of what the customer or the internal target will tolerate are the specification limits. These limits are created by people and indicate what manufacturers are intending for the process to do. Specification limits have an upper and a lower limit and demonstrate what a company wants to deliver to the customer. 

Control limits are not the same as specification limits and indicate what the process is capable of based on what it has done in the past. SPC can compare control limits, which manufacturing processes create, with specification limits to determine if the process in use can meet specifications. A process can be out of control but still within specifications, or it can be both out of control and exceed the lower or upper specification limits. Manufacturers may need to adjust the process, but sometimes the specifications are the issue. The most crucial aspect of understanding specification limits and control limits is to view them as entirely separate entities—never base control limits on specification limit calculations. 

The Importance of SPC Software

Automation is a vital tool that vastly improves agility and responsiveness in manufacturing facilities. For manufacturers to perform competitively, time is of the essence. SPC software can generate automated notifications when thresholds are exceeded. Software platforms also automatically apply the appropriate charts and can also create clear, concise reports that anyone from enterprise-level to operators can understand. Managers can also track trends with SPC software, noting changes over time that may not deviate from accepted standards but still indicate variability that customers may notice. 

The value of real-time notifications cannot be underestimated in a world when companies must pivot faster than ever to meet customer demand. Managers can root out problems immediately. While companies that do not implement software can apply SPC to monitor variations, the software can save valuable time that allows a manufacturer to make necessary adjustments to product compliance while still delivering on time. The software is able to monitor every aspect of the process, allowing the operators to set alerts for only the most relevant issues. Minor tweaks can be made to adjust in real-time, making the process far more efficient than reworking an entire batch.

Moving to an SPC software can deliver these key benefits:

  • Reduced scrap, rework, and warranty claims

  • Maximized productivity

  • Improved resource utilization

  • Increased operational efficiency

  • Decreased manual inspections

  • Improved client satisfaction

  • Reduced Costs

  • Extensive Analytics and Reporting

  • Reduce margin of error

  • Immediate problem resolution

  • Validate assumptions with data

  • Reduce dependency on tribal knowledge

  • Prioritize Uniformity

  • Create a data-driven decision process

SPC Quality Control Tools

In the 1970s, Dr. Kaoru Ishikawa, author of Guide to Quality Control, described seven quality control tools manufacturers could use to improve processes. In addition to the control chart (described above), here are the remaining tools:

  • Cause-and-effect diagram: Also known as the fishbone diagram, this chart maps out the many potential causes of an issue. For example, you could explore possible reasons why one shift is producing out-of-spec products.  

  • Check sheet: This simple form tracks an event and the causes behind it to help identify patterns. For instance, you might track stops on a particular line over one week, identify a series of reasons, and use tick marks to tally them up.   

  • Pareto chart: This bar graph is designed to identify the significance of different scenarios. The bar lengths indicate cost or frequency in order from longest to shortest.  

  • Histogram: A histogram is similar to a bar chart but different in that it shows frequency distributions. You might use a histogram to plot out quality defects, where the X-axis would represent defects per hour, and the Y-axis would represent the frequency (how many times there have been ten defects in an hour, for instance).

  • Scatter diagram: Also known as an X-Y graph, scatter diagrams are ideal for a pair of numerical data. One variable is set up on each axis to determine if there is a relationship between the two.

  • Stratification: Typically used alongside other quality control tools, stratification sorts data into distinct groups. For example, you might look at data sources such as equipment, materials, shifts, or time of day and plot them using a scatter diagram. You’d then use different colors to stratify the data and look at each subset of data in an attempt to uncover patterns.  

These quality control tools are used when looking at SPC as well as statistical quality control (SQC). Working with quality control tools within a software platform can reduce the possibility of over tampering with a process and risk involving non-relevant workers. The phrases “too many cooks in the kitchen” and “playing Whack-a-Mole” come to mind.

What’s the Difference Between SPC & SQC?

Although SPC and SQC are sometimes used interchangeably, there is an important difference between these concepts: SPC controls process inputs, or independent variables, whereas SQC monitors process outputs or dependent variables. SPC happens in real-time and focuses on prevention during the manufacture of products. SQC is an entirely different strategy that targets actions manufacturers can take after the process is already complete but before the product reaches the customer. Ideally, SPC detects problems well enough to prevent rework and waste. SQC requires large data sets since it is a long-term function. If, for some reason, a manufacturer did not implement some part of SPC properly, it can ensure customers do not end up receiving substandard product. Both SPC and SQC are useful, and many manufacturers regularly apply both strategies.

Why SPC Quality Matters Today

Clearly, a manufacturing tool that has stuck around for nearly a century must have some merit. Even though SPC originated so long ago, its principles are more effective today than they ever were. Thanks to sophisticated data collection tools, pinpointing problem areas and monitoring process behavior have become automated, freeing up the time and effort that would otherwise go into manually tracking quality metrics.

By helping you uncover the root causes of quality issues, SPC delivers several noteworthy benefits for manufacturing. It can allow your plant to:

  • Improve conformance with specifications. Consistently meet customer requirements by efficiently determining and addressing the cause of any non-conformances.

  • Minimize waste. With fewer non-conformances, you’ll have reduced scrap and re-work. Some manufacturers in the food industry worry about giveaway and overcook, which are also wasteful and, ultimately, costly.

  • Satisfy regulatory and other requirements. In food manufacturing, quality and safety often go hand-in-hand. Chances are SPC will help you uncover trends that not only affect quality but could also affect safety. By catching issues early, instead of during audits, you can stay on top of regulatory requirements such as FSMA.

  • Decrease costs. Better conformance with specifications, reduced waste, and minimized risk of safety issues can all help food manufacturers keep their costs down.

  • Become more efficient. Since SPC can also uncover bottlenecks and inefficiencies, you can use it to boost performance further and ensure processes are running smoothly.

While there are many factors to consider when implementing SPC, it’s clearly a worthwhile practice for manufacturers. Read our post to see why many plants are turning to OEE and SPC to save time and cut costs. You can find out how SafetyChain can simplify quality assurance and compliance with the 1# plant management platform here.