Why Is Quality Control Important in Manufacturing?
Make it better. Make it faster. Make it cheaper.
Manufacturers are under constant pressure to reduce waste and eliminate inefficiencies across processes—and to deliver the highest quality product at the lowest possible price. Along the way, you also need to balance customer expectations, regulatory requirements, and business goals.
Quality control practices are an essential way to track everyone’s requirements, as well as to assign standards and acceptable manufacturing ranges. Once established, quality control teams measure performance against these standards. And measure. And measure. And measure.
Based on SPC triggers, quality managers address core quality issues such as variability, volatility, and unpredictability. But their purview is limited, sometimes to a single product, line, or shift. And their goal is to fix an issue—as quickly as possible—and move on. Like a fire department for quality concerns. When managers return to the data, it’s usually to verify that corrective actions worked, and that production returned to the statistically acceptable status quo.
Quality control is essential to manufacturing. Without the right corrective actions, production lines could stand still. And without exceptional quality, manufacturers risk everything—reputation, sales prospects, and profitability.
And yet, quality control practices can do more.
Using data they already collect, manufacturers can advance their organizations—not just defend and protect them. With enterprise software and quality control tools, data can reveal magnitudes of opportunity. Integrated SPC software makes quality control important—not just in manufacturing, but to the organization overall.
Consider how these benefits of quality control in manufacturing build value across the entire business.
Efficient Data Collection
When quality control data is monitored continuously—in real time—issues get detected and resolved more quickly. At the plant level, digital tools speed up data collection and improve the overall accuracy of the information gathered. With digital data collection, handwritten errors, incomplete information, and inconsistent entries aren’t added to the data set. Digital tools also automate analytics and alerts, ensuring that the right people are notified to act—as issues occur.
At higher levels in the organization, leaders can compare SPC data across shifts, processes, lines, and plants. Reports and dashboards are created automatically, so it’s easier to discover actions that optimize quality. Analysis is more effective and efficient, and best practices can be applied across the organization.
Manufacturers want their production lines to run as smoothly as possible and as close to capacity as possible. They use quality control practices to prevent inconsistencies or other failures (such as equipment or raw material defects) that delay operations.
Since most quality managers focus only on their line or shift, productivity gains are limited. But with an enterprise view of quality control data, organizations can compare performance across products, lines, sites, and other variables and arrive at best practices. Then, they can be replicated for greater organizational gains.
Quality & Consistency
Quality control practices help manufacturers meet customer expectations and compliance standards. Quality measures that ensure product consistency, such as net weight and yield, are tracked multiple times a shift. But if those figures sit on a clipboard or get filed away after each shift, they don’t contribute to continuous improvement.
Improving quality and consistency
is important for the plant floor—and even better for the enterprise. When quality data is collected digitally and stored in a centralized location, leaders are able to extract more insight and value from the numbers. It’s faster and easier for executives to spot emerging trends and make strategic decisions about quality processes, goals, and investments. With an enterprise view of quality control data, manufacturers can maintain product consistency across lines, shifts, and locations.
To improve profitability, manufactures need to reduce scrap, waste, rework, and recalls
. But to fix problems, operators have to be able to see problems.
Quality managers use SPC to spot out-of-spec issues that lead to costly mistakes. With elevated, SPC-based quality control practices, you can stop problems before it’s too late to salvage time and materials.
At the line and plant level, quality control improves efficiencies, and can save hundreds or thousands of dollars each shift. Extend those capabilities across the organization, and manufacturers could save millions of dollars. Consolidated, comprehensive, accessible data gives manufacturing leaders more power over the bottom lines.
Reputation & Brand Value
Most manufacturing companies build their brands around quality. But how do they measure it? How do they prove it?
Customer satisfaction, certifications, and successful audits
help tell your quality story—when (or because) it’s supported by data.
When SPC data is collected, stored, and reported digitally, it’s easier for manufacturers to validate product quality. In mere minutes, you can verify that checks were completed correctly and on time, and you can respond to customer inquiries—in detail—about specific days, shifts, lines, or lot numbers. Precise tracking helps managers pinpoint root cause, and take immediate action to protect the brand.
These benefits also roll up to the corporate level. Using enterprise-wide information about quality control and performance, leaders can make informed strategic decisions and investments that continuously improve quality—and brand positioning.