Below is a Q&A session with Doug Fair, Chief Operating Officer at InfinityQS International, Inc. Doug is a recognized quality professional with more than 30 years of experience in manufacturing, analytics, and statistical applications, a Six Sigma Black Belt and a senior member of the American Society for Quality. Doug is also a regular contributor to various quality magazines and has co-authored two books on industrial statistics: Innovative Control Charting (ASQ Quality Press, 1998) and Quality Management in Health Care (Jones and Bartlett Publishing, 2004).
COO at InfinityQS
First and foremost, can you share a brief overview of InfinityQS’ history and mission in manufacturing quality management?
InfinityQS has been in the manufacturing quality software business for more than 30 years. At the heart of our software technology is statistical process control (SPC).
The two gentlemen who started the company worked at a large electronics firm in Southern California. While there, they were tasked with selecting a good statistical process control software product for use in their electronics manufacturing facility. Months of searching turned up no software that contained the flexibility and functionality that they required. As a result, they decided to start their own company—InfinityQS. So, I like to say we’re manufacturing people first, and we’re software people second. Our background and work in manufacturing plants has helped us to understand the unique challenges of deploying quality technologies on shop floors.
Our mission is client success. To quote the first sentence in our mission statement: “Our mission is to help organizations of all sizes achieve excellence in quality by providing software services and expertise that exceed expectations.” We’ve focused on our customers’ needs and success for 30-plus years, helping them be successful in their use of SPC and, more broadly, in their use of quality system software. We’ve helped companies around the globe, in every industry, deploy and standardize across multiple plants and to improve efficiencies company-wide.
How has quality management evolved into quality intelligence? And what makes that evolution essential for modern manufacturing operations?
20 or 30 years ago, manufacturing quality was focused primarily on responding to quality issues as they arose (putting out fires, so to speak)—in the shortest amount of time, or in real time. That’s still important today, so we support real-time communications and real-time improvement scenarios. Quality intelligence goes beyond just responding to issues. The idea is to aggregate data that has already been used for real-time decisions on the shop floor. Reviewing data at these higher levels invariably uncovers critical information that would otherwise be missed. Our software has specialized analytical tools that allow our clients to extract incredibly valuable information that can be used to strategically cut costs and improve quality.
Spotlighting the greatest opportunities for quality improvement across all plants is one of the unique capabilities that our products provide. InfinityQS software identifies the highest quality areas that could be used for benchmarking best practices, and the areas in most need of quality improvement. Quality intelligence is about more than just localized plant improvements, it’s about identifying high-level improvements that can be deployed across multiple plants.
There are a few aspects of modern manufacturing that make this move to quality intelligence essential in today’s manufacturing operations: size and scale of manufacturing operations, amount of investment in those operations, and breadth of competition. Many of the companies we work with are global entities, with hundreds of plants. When larger organizations discover quality savings at a single plant, they can replicate those improvements across all operations, saving millions of dollars.
History has shown us that when the competition ramps up, like today, the customer rules the day. Pleasing customers means consistently producing high quality products. It also means constantly analyzing data and looking for opportunities to improve product quality, reduce costs, and improve operational efficiency. And that’s where quality intelligence, and our software, shine.
What are some of the most critical operational challenges facing manufacturers today?
First of all, I would say, there is an overabundance of manufacturers and vendors for any market, and any niche. Take any product that you use in your personal life—an automobile, a table, a pencil, a fork—whatever the product, you will find that there are innumerable manufacturers making it and competing against one another. The result of that fierce competition is that quality has become a very clear differentiator, a critical differentiator. Every consumer wants quality products that are going to last but are also affordable. It’s not just about price anymore, it’s about quality.
For most manufacturers, about 15% to 20% of overall operating costs are the result of poor quality. If you could cut that percentage down to under 10%, then you could undercut your competitors’ pricing and still provide a better-quality product. It’s a huge challenge. Defects, scrap, rework, inspection costs, and more—all contribute to low quality, and all have a cost associated with them. Organizations must continually cut costs but do so intelligently. Organizations must strive to make the highest quality product that meets their customers’ needs—as efficiently as possible, by reducing internal costs of poor quality.
Another challenge is standardization. For organizations that have several plants—dozens or hundreds—standardization is a huge challenge. If companies can standardize, then they can simplify their operations and cut operational and system support costs. Standardization can also help ensure production line consistency and consistency of product quality. But I would add this: by standardizing, organizations gain the visibility into data that they need across all their plants. Lack of visibility is a huge problem. Organizations without cross-plant quality visibility are blind to critical information that could be used to improve all plants. Surprisingly, some organizations still rely on spreadsheets and paper-based systems for managing quality. Those systems simply do not lend themselves well to cross-plant quality visibility.
Lastly, another challenge for today’s manufacturers is technology. We still see organizations who use outdated computers and software systems. Many organizations believe that updating technology is very expensive. I believe the opposite is true. Especially with today’s new cloud-based technologies. Software-as-a-Service (SaaS) is far less expensive, frankly, than using spreadsheets and paper-based systems to try to manage quality. Paper-based systems and spreadsheet systems are incredibly inefficient. They’re very costly because they have to be managed, and they are notoriously time-consuming and cumbersome. Because the cloud is a relatively new technology, many organizations are reluctant to move—they’re comfortable where they are. (And, let’s face it, nobody likes change.) But organizations that currently use cloud technologies have an advantage over others that do not leverage SaaS products—they have cross-plant visibility, better standardization, and greater information that can drive costs down and productivity up.
How have those challenges forced manufacturers to change the way they manage processes and product quality in their organizations?
The most obvious example I can think of is companies that use paper-based quality systems. Paper is incredibly inefficient, and expensive too. Information written on paper is only known by the persons who wrote it. Once written down, data is forever imprisoned on paper, never to be reused, repurposed, or even plotted on a simple chart.
Problematically, people cannot be expected to write perfect numbers and letters on paper. Even if your busy operators did write numbers down perfectly, how does the data serve the plant or the company? At best, written data is simply a localized verification to an operator that they, themselves, actually collected the data.
If those data values need to be reviewed by, say, a manager, the review process is a nightmare. I have witnessed quality managers who perform daily reviews of data on paper. One quality manager I met had about 100 pieces of paper on his desk. He told me that to review it all, he’d have to go through every single value that was written on every piece of paper. When I asked what he was looking for, he responded, “I don’t know. I’m just trying to see if something doesn’t look right.” That’s not only inefficient; it’s a waste of time. Operators who wrote the data down might understand context and specification limits associated with the data, but no one else does. What about trends? What about performance comparisons between production lines? It’s all lost when paper is used, and other than the operator (and possibly a supervisor), no one else sees the data.
Moving away from paper and embracing technology is vital for uncovering cost-cutting opportunities. If your quality procedures, processes, data collections, analyses, and reports are all in the cloud, then you can standardize across product codes, production lines, plants—even across your entire enterprise. You can analyze any data you want, while providing data visibility to managers, engineers, quality professionals and Six Sigma teams—the folks who can help quickly cut costs and optimize efficiencies.
What makes InfinityQS’ ProFicient different from other quality management solutions in the market? What are its key advantages over other solutions?
ProFicient was designed to be very easy to use, but also very flexible. Those two aspects of software usually don’t go together, but with ProFicient they do. We understand the desire to ensure that the quality system you use is very simple for operators to work with—and fast—because operators are busy people. Therefore, our operator interfaces are simple, and most features are automated: data collection, alarming, charting, reporting, communications, emails, etc. ProFicient is a flexible, feature-rich product that’s optimized for use on the shop floor, and that’s a big differentiator between us and our competitors in the marketplace.
Another big advantage ProFicient has over competitors is in how it is configured. Unlike other products, a single ProFicient configuration can manage data collection and analysis for multiple products, production lines, shifts, and multiple plants. This means simplicity of deployment and management.
From an operator’s standpoint, a single configuration can support an operator who switches to different product codes a dozen times during their shift. And that same configuration can be used across multiple production lines. Ultimately, this means that not only are configurations easy for operators to use, but they’re fast for administrators to create and manage.
If you have thousands of product codes and hundreds of production lines, you can manage those kinds of deployments with just a handful of configurations. When changes inevitably occur in the manufacturing process, or additional features need to be added to the data collection, administrators need only modify a one or two configurations for the entire plant.
I once worked with a medical device client that made surgical spinal screws. Because all human bodies are so different, the screws had many different shapes and sizes – 10,000 different part numbers in all.
With a single configuration, ProFicient was able to support their data entry and analysis needs for the entire department. That is, one configuration is all that was required for data entry for any of the 10,000 part numbers on any of their nine different screw machines. ProFicient’s ability to manage these situations with just a few configurations is an enormous differentiator for us.
Another differentiator: ProFicient was specifically designed for multi-plant deployments. Our built-in corporate hierarchy means that quality across your entire enterprise can be managed with a single instance of the software. Corporate hierarchy can prevent plant A from viewing plant B’s data, but it can also allow corporate visibility to all plants’ quality data.
As mentioned earlier, for most organizations, a big challenge is visibility. Because ProFicient can be used in an on-demand, cloud-based environment, we can create cross-plant reports and analyses to provide information that corporate quality people need to identify higher-level quality opportunities. For these analyses, ProFicient uses proprietary algorithms for generating metrics and comparisons with aggregated data. Even product codes that are vastly different from one another can be compared against one another. That means that quality professionals (and even non-technical people) are provided valuable quality information in a very-easily-understood format. You don’t have to be a statistician to use our software. ProFicient makes it easy to consume the information generated by your quality data.
Lastly, ProFicient can manage automated data collection from any electronic system. Whether ERP or MES systems, bespoke database systems, inline data collection systems or handheld data collection devices, ProFicient supports fully-automated data collection from any data source. That means data accuracy, simplicity and a reduction in the amount of time necessary to manage your quality system.
What capabilities does ProFicient provide that improve the way manufacturers approach quality management in their organizations?
Our software products enable organizations to convert data into information. Our customers rely on a wide variety of different data collection systems at their plants. As I mentioned earlier, our customers might use ERP systems, MES products, Programmable Logic Controllers (PLC’s), hand-held gauges and inline data collection devices. They collect enormous amounts of data on their shop floors, and they collect that data with different systems. That’s one of today’s manufacturing challenges: Too much data resides in separate, disconnected systems. I’ll call them “data islands” because, by definition, the data collection systems I just listed are separate from each other; they neither talk to nor integrate with one another.
ProFicient acts as the bridge between these data islands. ProFicient can sample and extract the data from data islands, then store those data in one single repository. ProFicient does this by standardizing each island’s disparate data into a simple format. Then ProFicient stores all sampled data in one database. The result is that you have one place for all your critical quality data—whether process-specific data, product checks, validations, MES, ERP data, it doesn’t matter. Everything is saved in one place—from one manufacturing plant, or from multiple locations.
ProFicient also helps manufacturers improve quality at the manufacturing source – on the shop floor. ProFicient is very easy for operators to work with. Anyone who’s making products on a daily basis receives information from ProFicient that is specific to how their machine is running. ProFicient alerts operators (and managers—no matter where they are) when quality levels have changed, and when something has gone out of specification limits.
It’s more than data aggregation and consolidation; we’re providing the very people that are making products with the information they need to ensure that their processes are as efficient and as high quality as possible.
Because data is stored in one place, quality professionals can easily analyze any data they want, and prioritize critical quality projects and activities. ProFicient is a one-stop shop for your operators, managers, and quality professionals to get the information they need to ensure quality success on the shop floor.
And executives and business owners can easily access the summary information that ProFicient creates. We’ve found that this helps them to direct where they’d like to invest in additional technologies (or determine where they don’t need to invest in additional technologies).
There’s been a real push over the past several years towards automation in manufacturing. What we have found is that blindly spending big money on new automation technologies is not necessarily the right move: if you have a low quality output from a production line, then you don’t want to automate that and just create more bad products at a faster pace.
By business owners and plant managers focusing their efforts in areas where quality is an issue, they can take older machines and dramatically improve the quality levels of those machines by tapping into the information that ProFicient provides them.
ProFicient provides information that can help eliminate quality defects without the necessity of expensive automation.
How do you see today’s manufacturers looking to the challenges of the future and preparing for them?
Customers desire two things: greater functionality and enhanced simplicity. Those requirements have been growing in recent years. While they seem to be contradictory needs, they’re what we’re seeing manufacturers produce these days. Take for example, smart phones. When one prominent smartphone was introduced years ago, the company CEO said, “There’s going to be one button and one button only on this phone.” They made that product with tons of functionality and yet enhanced simplicity as compared with competitive products. That smartphone was a game changer in the world of cellular communications. The same is true of automobiles. The modern automobile’s ability to sense things before they happen and prevent accidents from occurring has been amazing.
At the same time, consumers want more freedom for customization. There’s a company that I’m working with right now that makes large industrial products. Their customers want their products, but they want them customized specifically to their unique specifications. Therefore, nearly every single product that this company makes is customized to the point where specification limits are different, functionality is different, and it’s a wholly bespoke product compared to the last unit that rolled off the production line. The implications are that manufacturing processes must become ever more agile and flexible. As a result, they will be required to be more complex. That could be a problem for quality.
Additionally, because organizations collect so much data on the shop floor, there continues to be an accelerated interest in using that data to make intelligent manufacturing decisions. As mentioned, today’s shop floor is overflowing with data. The real challenge is trying to make all that data useful and consumable.
Organizations are asking how to manage that data. How to make it valuable to the people who need to make important decisions on a minute-to-minute basis. Presenting valuable information like this to the right people is going to drive manufacturing excellence in the near future.
With so much competition, the stakes are high for manufacturers. There will be greater reliance on data in order to make the right decisions, improve efficiencies and reduce costs. From our standpoint, data intelligence is the key. We have found that data is at the heart of how organizations drive lower operational costs. With the ever-increasing number of vendors and competitors in every market, lowering quality and other costs is a strategic endeavor whose focus will soon accelerate.
Data intelligence will be the key to ensure manufacturing automation works as intended. The data should tell manufacturers what they need to do and when. Humans can no longer be relied upon to review data 24 hours a day, seven days a week, and then tell us what needs to happen. Extraction of quality intelligence must, instead, be automated.
Automated data analysis and sharing of that information will soon be expected so that the machines themselves will tell us what needs to be done. In the near future, the machines themselves will gather data, learn from it, and then make their own modifications and changes to configurations and settings. This real-time, “closed loop control” based on data has been manufacturing nirvana that organizations have unsuccessfully strived for. However, with the overabundance of data and the inability of humans to make sense of it all, machine learning and closed-loop control will, in the near future, be needed to ensure manufacturing quality viability.
How does quality intelligence support that future?
I think that quality intelligence is at the core of how the future of manufacturing unfolds. Quality intelligence is going to help organizations to understand how they can mass-customize with both speed and high quality. ProFicient is already at the forefront of that; we support what’s called short-run SPC. It’s one of our great capabilities. ProFicient supports over 300 different control charts to manage incredibly technical short-run situations—like what is needed with mass manufacturing customization. ProFicient also provides aggregated data analytics that support automated extraction of quality intelligence from enormous amounts of data.
As I mentioned earlier, quality intelligence is all about the information learned from collected quality data. ProFicient can act as the bridge between all your disparate data islands. ProFicient can sample data from every data island, consolidate it into a centralized data repository, making all your critical quality data available to anyone. Quality intelligence metrics and analytics are also built into ProFicient, allowing users to easily extract meaningful information from lots of data. ProFicient does these actions automatically and can present those findings automatically to the quality professionals, managers, business owners, and others who need to make critical decisions. That’s what ProFicient was built for.
The future challenges of technologies such as machine learning, artificial intelligence, and closed-loop control are becoming more obvious all the time. All these technologies are based on data. And data is at the core of what ProFicient does. There needs to be one place where those AI engines, those machine learning engines can go for information, and that place is ProFicient.
About InfinityQS
In business for more than 30 years, InfinityQS is the leading provider of Statistical Process Control (SPC) software and services to manufacturers worldwide. Our solutions automate data collection and analysis during the manufacturing process, so you can make real-time process improvement decisions and prevent defects before they occur. Developed by industrial statisticians using proven methodologies for quality analysis and control, InfinityQS solutions are saving leading manufacturers millions of dollars each year.
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