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Statistical Process Control (SPC) for Injection Molding

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Last updated Sep 3, 2024 | Published on Jul 22, 2019

Boyd uses several different Statistical Process Control (SPC) tools to refine manufacturing processes.

As customer needs become more nuanced, it is incumbent on injection molders like Boyd to continually innovate and improve our processes to meet their evolving demands. The tools of statistical process control (SPC) are critical in understanding process capabilities, identifying unwanted variations, and refining manufacturing processes. Overall, it enables us to efficiently and consistently meet our customer’s sophisticated needs for quality, lead time, tolerances, delivery, and cost.

Primarily developed by Walter Shewhart at the Bell Labs in 1920s, statistical techniques have been around for decades. Competitive companies worldwide have implemented a wide array of statistical tools to help reduce costs by mitigating scraps, re-work costs, and variances in production processes. These tools range from simple graphing to more complex analysis including Pareto analysis, histograms, capability analysis, fishbone charts, and control charts.

Advanced statistical software has made “data crunching” easy and efficient. At Boyd, it provides us with a quick overview of how our injection molding processes are performing by analyzing data from internal product characteristics and/or customer-driven product features. This data can be viewed in several forms – as a line graph (Individuals data charting), or by stratifying data into a histogram (including process capability indexes), or a control chart (typically x-bar/R). These tools allow us to understand process conditions and provide actionable data to our engineers in the event of an unforeseen production issue or bottleneck.

At Boyd, we work with a broad spectrum of part sizes, shapes, forms, and complexities every day. When manufacturing a wide array of components for diverse customers and industries, it is critical to identify machine capabilities and production processes. Being able to make prompt decisions based on statistical data, developed during both initial qualification and in-process production, gives us flexibility in production and allows us to develop sound process controls.

In our upcoming blogs, we will discuss two of the most commonly used statistical tools at Boyd – capability indexes (Cpk) and control charts.

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