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Statistical Process Control (SPC) is the Key to Quality and Efficiency in Food and Beverage Manufacturing

August 19, 2024
in Food
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Statistical Process Control (SPC) is the Key to Quality and Efficiency in Food and Beverage Manufacturing
High angle portrait of two factory workers using digital tablet while inspecting production at recycling plant, copy space

By Brad Armstrong, VP of Sales at Advantive

Key Takeaways:

  • Many food and beverage manufacturers still rely on outdated, paper-based systems for quality control, which leads to increased costs, wasted efforts, and quality issues that put consumer safety and brand reputation at risk.
  • Statistical Process Control (SPC) is a crucial tool that enables real-time monitoring and automated alerts to detect and correct problems before they escalate, ensuring consistent quality and food safety.
  • Implementing modern, data-driven SPC systems can enhance productivity, reduce waste, improve brand reputation, and foster a culture of continuous improvement, providing a competitive advantage in the fast-paced food and beverage industry.


In the high-stakes world of food and beverage manufacturing, quality-control issues can have serious consequences. With consumer safety and brand reputation on the line, manufacturers must maintain consistency by proactively monitoring and adjusting processes to prevent deviations.

Though this is easily accomplished through the usage of Statistical Process Control (SPC), a recent survey revealed that a staggering 75% of food and beverage manufacturers still use outdated, paper-based systems to collect and verify data. This approach not only puts professionals on the defensive but also leaves businesses vulnerable to increased costs, wasted efforts, and quality-control problems.

Risks posed by subpar paper-based systems are avoidable

The risk of information loss and inefficiency is high when manufacturers use processes that rely on pen and paper. Documents get lost or misplaced, data entry mistakes are common, and the entire workforce becomes bogged down by manual procedures. These challenges not only increase costs and can significantly impact quality control, but they also lead to recalls and reputational damage because manufacturers end up reacting to issues rather than preventing them. This leads to an ineffective workflow and potential disparities in standards.

To avoid these snags and truly optimize operations, manufacturers need to take a holistic approach, leveraging data to gain a comprehensive understanding of their organization’s practices. SPC is a crucial tool in this effort. It empowers companies to make meaningful process adjustments, lower expenses, and ensure consistent quality compliance. By integrating SPC into their operations, manufacturers get a complete picture of their methods and can better identify areas for improvement.

Harnessing the science of SPC for optimal results

SPC uses real-time metrics and statistical analysis to monitor and manage manufacturing processes. Data is plotted on a graph with predetermined control limits, and if the data falls within these limits it indicates normal process variation, while points outside the limits suggest an assignable cause that needs to be addressed. By pinpointing and investigating these variations, SPC helps to reduce waste and inefficiency.

In addition, the technology’s ability to facilitate rapid and precise corrections on the production floor is invaluable. Real-time, automated alerts and notifications enable manufacturers to resolve issues as soon as they arise, minimizing the impact on production and ensuring consistent quality. This proactive approach saves time and money while enhancing overall operational efficiency. SPC insights expedite the analysis of data trends and patterns, allowing companies to make informed decisions that increase profitability. For example, live SPC updates could quickly identify bottlenecks in assembly workflows and reduce overfill and giveaway in filling operations by connecting checkweighers and inline measurements.

SPC protocols can also be driven from a shared cloud system, which establishes one single place for process improvement teams, quality professionals, and managers to access information that each requires. This unified approach enables faster implementation, streamlined data access, and the ability to produce comprehensive reports that provide enterprise-wide insights. With this enhanced visibility, organizations can identify key areas for strategic quality initiatives and drive meaningful changes that have a substantial impact.

Manufacturing industry’s pace demands top-shelf solutions

The holistic view of manufacturing data that SPC offers is critical for preventing issues, boosting productivity, and avoiding a tarnished image. With real-time monitoring and automated alerts, manufacturers can detect and correct problems before they escalate, ensuring that only the best products reach consumers. Prioritizing food safety with traceability tools is crucial for maintaining consumer trust and satisfaction; when customers are happy, brands gain strength. 

In an industry where quality, safety, and efficiency are paramount, food and beverage manufacturers cannot afford to rely on outdated, paper-based systems. Lack of modern statistical process control systems translate into excessive giveaway, unnecessary usage, additional inspection costs, and higher defect rates. But the benefits of implementing SPC extend beyond the production floor, enhancing brand reputation and profitability while fostering a culture of continuous improvement. The results speak for themselves; it’s time to make the leap to modern, data-driven systems. 

Brad Armstrong currently serves as VP of Sales at Advantive and has been in the SPC field for 27 years working across multiple industries to help manufacturing companies implement automated SPC solutions. His primary responsibilities involve global sales for WinSPC and managing channel partners, while most of his time is spent working directly with corporate customers to guide their SPC projects. He is certified in Quality Management and SPC methods and has been on the executive leadership team with DataNet for the past 12 years.

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