InfinityQS Quality Control, Industry Today

August 28, 2019

By Doug Fair, Chief Operating Officer, InfinityQS® International, Inc.

When I ask manufacturers, “What does ‘quality’ mean to you?” I get a handful of answers. Quality means all our products and processes are within specification limits. Quality is a constant uphill battle with plant-floor issues. Quality is a necessary evil and expense. Rarely do I hear about quality as an investment—something that provides dividends and accruing value (much like when you purchase a home or piece of real estate).

In truth, quality can be one of your greatest investments—particularly when you have a strong quality control program in place. This starts with having a quality management system, so you can realize fast returns and continuous, transformative results by way of data. Manufacturers that view quality as an investment can strategically use process data to proactively address plant-floor problems, minimize capital expenditures, and uncover opportunities for operational improvement.

Realize a return on investment (ROI)

It is easy for manufacturers to think implementing a quality management system is just an additional cost. However, it is a fundamental component of having a good quality control program—one where you don’t simply react to problems but prevent them from occurring in the first place. This is where real-time data collection and statistical process control (SPC) fit into the picture, providing timely and meaningful information so that the right people can take the right action, at the right time.

On the plant floor, operators can immediately see when a process is starting to change so they can quickly and proactively make corrections to ensure products are as consistent as possible. Manufacturers typically realize an immediate ROI as information provided to operators helps them cut costs associated with scrap, waste, defects, and rework. Organizations in the consumer goods space, such as food & beverage companies, can prevent costly recalls and losses incurred through product destruction and potential damages to brand reputation.

Make the most of existing systems

Unfortunately, many companies get caught in the “technology trap,” where they think they need to throw money into the latest technologies to solve their problems. Investing in a quality management system is the exact opposite approach—it enables you to refine and improve existing processes and existing technologies to minimize quality costs and save on expenditures.

The math is easy: if you use existing machinery and make progressively better products, then your costs continue to go down. I have worked with many companies to gather and analyze their production data to pinpoint fixes and incrementally improve the performance of older machinery. Most of the organizations I have worked with have been able to eliminate or delay the purchase of new production lines and technology through quality data analysis. Big money is typically saved as they are able to avoid expensive and unnecessary capital expenditures. In effect, the intelligence provided by a quality control program can help sidestep enormous capital outlays.

For instance, I once worked with a beverage manufacturer whose quality checks showed their products were all within specification limits. But a detailed analysis of the fill data showed that while they were “in spec,” they were still overfilling every bottle. We used the data to identify discrepancies in fill-head performance, product-to-product differences, the effect of speed on filling, and more. Through these insights, the beverage manufacturer made improvements that generated over a million dollars in savings—on just one filling line. Extrapolate that over the plant’s 20+ lines, and the savings were astronomical. There was no investment in a new production line. They purchased no new equipment. Instead, the million-dollar cost improvements were simply the result of acting upon the insights found in their filling data.

Mine process data for quality intelligence

While plant-floor data can alert you to process variations and show you how to finetune machinery, there is a second life for that data that can be resurrected at the executive level. Like a miner searches for gold, quality professionals and decision-makers can evaluate the data to extract quality intelligence across a broad spectrum of machine tools, product codes, shifts, etc. By evaluating aggregated data, overarching trends can be identified, and detailed information regarding how to improve products, processes, and operations are revealed. Through cloud-based solutions, it is possible to gain enterprise visibility to compare data between lines, regions, and sites and uncover opportunities for global improvement.

Sometimes these “golden nuggets” of information can be found in unlikely places, such as in-spec data. Reviewing and analyzing data that falls in spec seems antithetical. That is, most managers would say, “Why even look at the data if it’s in spec? Like the beverage example above, managers and quality professionals may be missing out on extraordinary savings because they ignore data that falls within specifications.

What we are talking about isn’t difficult to achieve. You just need systems that support plant-floor data collection and enterprise-wide data analysis tools, a means of aggregating that data, and the ability to make it digestible by quality professionals, engineers, managers, and executives.

Ultimately, when you view quality control as an investment, you’re able to better leverage the data you already have. You can see how processes are running in real time and extract information to determine how performance can be improved. Viewing quality as an investment can transform seemingly mundane data into your greatest asset—a powerful way to realize new efficiencies, minimize scrap and rework, increase productivity, drive down costs, and positively impact the bottom line.

Doug Fair InfinityQS, Industry Today
Doug Fair

Doug Fair, Chief Operating Officer, InfinityQS® International, Inc.

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