Specifications are the standards or the minimally accepted requirements for important features (or characteristics) of a product. Many manufacturers also set their own specifications. The confusion between specification compliance and quality can lead to financial loss, wasted time, and so on. For example, a product can fall within specifications but still prove unsatisfactory for clients. Additionally, manufacturers that rely solely on meeting specifications can miss out on opportunities to create more cost-effective processes. Thus, applying several statistical principles can immensely help a company identify ways to positively reform a process and product. By moving beyond the gauge parameters of specifications, manufacturers can boost quality with an efficient, optimized, and cost-effective process that performs better and satisfies the customer base.
At its core, manufacturing success is all about quality. Consistently adhering to quality standards ultimately delights your customers and takes you far beyond the benefits of brand loyalty. Determining the cost of quality (COQ) is a complex but essential endeavor; there’s the cost of poor quality to consider and the cost of good quality or preventing issues from happening in the first place. In plants producing hundreds of separate items, tracking the many variables that influence quality can feel like a massive undertaking. And of course, it’s not just tracking this information that facilitates change; the goal is to derive meaningful insights from the data to inform future decisions.
Both SPC and SQC help to drive smooth operations to promote efficient output and optimal results. They both play a role in overall success in operations, but those two roles are different. Here’s what to know about SPC and SQC to determine which is right for your Food & Beverage or CPG manufacturing facility.
What Is Statistical Process Control?
Simply put, SPC uses statistical methods and sampling programs to help plant and operations managers understand and control variability in their manufacturing processes. Charts highlight process variations in real-time, triggering alerts as processes begin to trend out of expected, standard limits. The main objective of statistical process control (SPC) is to manage operations better and reduce waste and rework. Plant and Ops managers benefit from SPC because it gives them the concrete information and clear markers needed to stop a line and fix problems before things spin out of control.
In challenging times, every little bit of continuous improvement adds to the bottom line. In 2020, we're seeing more and more F&B companies doubling down on data and leveraging SPC and OEE to boost margins and profits.
Developed by Bell Laboratories about a century ago, Statistical Process Control (SPC) is a quality control tool employing statistical methods to monitor and control a process, ensuring it meets specifications. We created a quick video for the process manufacturing industry insiders. This high-level overview defines SPC and how using specific metrics like Ppk, SPC, Cpk, control limits, spec limits, and run rules helps users understand and manage variability.