Go from “doing quality” to mastering it—and get more value for your quality management investment.
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Quality practices have to be carried out for compliance reasons and to meet customer agreements. But traditionally, they’ve returned little value to the organization beyond “checking the box.”
Sure, site-level analyses translate to incremental improvements, but they don’t transform organizational performance. Quality control has been essential in manufacturing—but it hasn’t necessarily been influential.
That doesn’t have to be the case. Quality control measures can be goldmines for product improvement—and for reaching high-level strategic goals, such as lowering costs and mitigating risk. The insight you need to make more accurate and impactful decisions is being collected—probably right now—through your quality control processes.
These activities accumulate massive amounts of data—and some of your most important operational metrics. Quality control data encompasses nearly every aspect of your business, from suppliers and raw materials to equipment, people, processes, and final product inspections. All that data can be used to inform higher-level decision making—to elevate the impact of quality control in manufacturing.
To extract more value from quality control data, manufacturers need easy access to Statistical Process Control (SPC) data. Quality control tools need to be standardized, comprehensive, and actionable—for users at every level of the business.
You collect quality control data anyway, right? Why not use your information more effectively? Learn how to get more value out of the quality control practices you already have in place.
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.
Then what? 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.
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 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.
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.
With today’s advancements in digital technology, the best place to store this database—and your quality platform—is in the cloud. Doing so significantly reduces deployment and maintenance costs while increasing agility and supporting scalability.
Integration is a key tenet of the Enact quality platform. This integration takes multiple forms:
There’s a huge difference between “doing quality” and “mastering quality” in manufacturing.
Companies that do quality control focus heavily on data collection and action. They spend the bulk of their time checking boxes: Was data collected? When? By whom? They only look for insights if corrective action is required. And in those instances, analysis usually ends once the urgent issue is resolved.
Mastering quality control uses the same data—but applies it differently. Masters spend more time and energy proactively analyzing data, and compare metrics from across the organization to uncover best practices and opportunities. They take action after they analyze.
An analytical approach to quality management empowers manufacturers to be proactive and strategic with their quality control efforts. They uncover opportunities that support big picture strategic goals. They use quality control as a strategic lever to achieve corporate goals.
At the practical, day-to-day level, here’s what it looks like to shift from tactical quality control to strategic quality management.
Organizations that do quality control:
Organizations that master quality control:
When SPC tools are fast, accessible, and easy to use, manufacturers can analyze issues before they take action. With enterprise-wide SPC, you can finally have the tools you need to proactively address quality.
Enact empowers you to quickly realize the benefits of digital data collection and analysis. Start today with:
Your quality management program must support tactical, everyday quality requirements—and bigger-picture strategic goals. How can quality control programs balance both these needs and add value to the organization?
An enterprise-wide, digital SPC solution meets a diverse set of user requirements. The right solution helps you measure quality in real time, prevent costly problems, and reduce risk across the enterprise.
Here’s how a digital enterprise SPC solution can help you balance tactical and strategic quality control needs.
When choosing a quality platform, work with your provider to pin down exactly what you want from the platform:
The best way to launch a successful Enact deployment is via a targeted, small-scale deployment. By starting small—one filling or packaging operation, for example—you can experience Enact and build a foundational understanding of how your quality platform can work.
You begin by setting up an Enact subscription. Then, the in-app Quick Startup enables you to set up a simple data collection right away. You can immediatetly start collecting data and see how Enact works in your manufacturing production environment. When you encounter questions or need help, the Enact Guided Learning Center provides helpful videos and online tutorials.
You get to experience Enact’s dashboards, discuss feedback from your team, and evaluate the results of your initial setup. In other words, you get to see firsthand what Enact can do for you—and how it can help you extract meaningful business insights from your manufacturing quality data.
What to Expect
Key considerations and best practices for smart, data-based decision making.
What do we mean when we talk about a quality platform? Your manufacturing organization needs to prioritize decisions that will bring the greatest business benefit and help you optimize production operations. A manufacturing quality platform enables you to digitize critical quality and process data so that you can gain strategic insights into your operations. To gain that insight, you must have access to your quality and process data in digital form. A well-designed quality platform can fuel a digital transformation for your entire manufacturing ecosystem.
The knowledge and visibility contained in your quality data powers strategic decision making—not just across one product or line, but across your entire enterprise. By taking quality data out of disjointed, discrete systems—and by automating how you collect and work with that data—you can uncover opportunities to:
What does this mean for you? For one, proactive quality insights reduce the number of nail-biting incidents that crop up. It can alert you to variances before they become defects—or worse, escapes. It can help you determine which areas of a line, facility, or region need the most attention. And it can help you establish best practices and propagate them across all your facilities.
It can be challenging to align your teams and gain the buy-in necessary for selecting the best cloud-based quality platform for your company. That’s why we created a step-by-step buyer’s guide—to ensure that your teams have all the information they need during this important process.
You run your manufacturing enterprise using a wide range of systems, each encompassing a slightly different business focus. The interconnectivity among these systems forms your unique enterprise application architecture.
The success of your manufacturing ecosystem depends on the health—and successful integration—of these systems.
How can a quality platform fit in with your MES, ERP, MOM, and QMS? As a purpose-built manufacturing quality platform, Enact® by InfinityQS® goes beyond the confines of traditional plant floor quality management. It enables you to strategically collect, visualize, centralize, standardize, and analyze data—whatever the source—and provide essential integrations with your other business systems to facilitate meaningful analysis and actionable insights.
Using Enact, you can automate the collection of quality data from other systems, then standardize and centralize it into a unified data repository. Why is this step so important?
What capabilities should you demand in a quality platform? Remember, your quality and process data is your direct source for product quality and business insights. And that means different things to different people in your organization:
A quality platform provides a focused view of information each of these roles, when and where they need it. It delivers focused data insights efficiently and effectively, helping you optimize workflows, sort through today’s data “noise,” and save valuable time and resources.
Enact includes features—such as bubble charts and data stream grading—that make it easy to distill data across systems and locations, enabling the collaboration and prioritization that lead to dramatically effective results.
Manufacturers know it’s important to modernize equipment and tools. But if they’re not investing in the processes and data that feed continuous improvement, they’re not maximizing their investments.
Think about Amazon, whose website and ordering process is slick. But if the company doesn’t fulfill your order in two days (or less), you won’t be satisfied.
What happens behind the scenes is what really matters. In manufacturing, that means every process must come together perfectly, every time, to deliver on customer expectations. Close isn’t good enough.
Oh, and customer expectations? Those change by the second. Natural disasters, political turmoil, generational trends, and global health crises can upend shopping habits and supply chains—overnight.
It’s a tall order for manufacturing organizations to fill. To meet rising expectations around quality, service, and speed, you need more agile and responsive operations. But how do manufacturers know what to respond to? Or how to respond?
In digitally transformed manufacturing companies, data leads the way. More specifically, quality control data leads the way. Advanced manufacturers apply quality control measurements and data toward big-picture challenges and opportunities. They digitally transform their organizations—not just their lines—to embrace more efficient, accurate, and results-focused business practices.
Quality is central to every step in the manufacturing process, but quality hasn’t connected the steps in a meaningful way until now. That’s because manual methods of gathering, analyzing, and sharing data tend to be siloed—connecting the dots is impossible on modern manufacturing lines. There’s too much data to sift through—and no way to quickly and reliably decipher what it means.
Digital transformation in manufacturing erases those barriers—giving quality teams the platform, tools, and insight they need to quickly respond. Digital transformation can help you build manufacturing resilience—and prepare for whatever comes next.
By leveraging the core elements of quality control, quality management teams should be able to answer business-critical questions such as:
Unfortunately, many manufacturers can’t answer these questions at an enterprise level—not without lots of data manipulation and spreadsheet juggling, anyway. And in those cases, data integrity is questionable. How confident are you that every data point—at every site—was collected and calculated the same way?
In today’s competitive environment, there’s no room for uncertainty. Executives need accurate insights from quality data to make strategic decisions for the company.
Luckily, the data to answer these questions is already being collected on the plant floor. The challenge is making data more reliable, accessible, and actionable.
That’s where digital transformation comes in. To find the answers inside the data, manufacturers need the right tools. Quality data needs to be collected and stored digitally, in a central and standardized repository. From there, modern analytics can help you re-imagine quality and transform your business.
Technology-driven quality management practices provide three key benefits over manual methods:
Many manufacturers have taken preliminary steps toward digital transformation. Perhaps they’ve embraced Industry 4.0 by automating processes or by installing Bluetooth sensors to monitor equipment.
Those are important steps. But to leverage the data that’s being generated, manufacturers need to take digital transformation further. Instead of simply digitizing traditional or manual processes, they need to build stronger connections between systems, processes, and outcomes. Digital tools must talk to one another—using a common language—so data makes sense.
A cloud-based, Software as a Service (SaaS) quality platform brings it all together. Purpose-built, enterprise-wide tools enable more comprehensive and transformative quality management practices.
For example, in a digitally transformed approach to quality management:
These benefits of digital transformation aren’t just conveniences. They lead to “big picture” views of the organization—without losing the opportunity for operators to dig into targeted, in-the-moment metrics. Manufacturers shift from “collecting quality data” to building quality as a competitive advantage.
With analytics-based quality insights, manufacturing leaders elevate the role of quality in their organizations. When decisions about quality performance are driven by quality data:
A comprehensive approach affects more than just quality. Digital transformation in manufacturing supports total manufacturing optimization.
Traditional quality management tools can’t keep up with the demands of modern manufacturing organizations. Yet a recent survey found that 75% of manufacturers still collect data manually. Nearly half still use paper checklists.
Manual processes could be introducing unnecessary risk:
Cloud-based Statistical Process Control (SPC) tools pool all your quality control data—and automatically return extensive, flexible views of performance. With customized reports, notifications, and alerts, your operations and quality teams can save valuable time—and make better use of your quality information.
Take a look at the factors driving digital transformation—and how a tactical move to cloud-based quality management can help you become more agile and efficient.
Digital transformation connects all your quality management data into a comprehensive, purpose-built solution. When compared to home grown or patchwork solutions, true digital transformation is centralized, standardized, and scalable.
A food manufacturer calculated its raw material costs down to the gram, and identified over $3 million in savings. How did they do it? Using line-level quality data they had already collected.
Side-by-side comparisons of production lines and product codes revealed major variances at a top-tier tool manufacturer. By looking at in-spec quality data, they discovered opportunities to reduce scrap and waste—and improve quality, productivity, and profitability.
A metal-forming manufacturer had a 45% scrap rate at one of its plants. By analyzing quality data, they completely eliminated out-of-spec product—and dramatically increased throughput. The key to massive bottom-line cost savings was already within reach: in their quality data.
Explore the many training options available for InfinityQS users of all levels.
Maximize the value of your InfinityQS SPC solutions and achieve your quality goals faster with our online training and performance support. We offer effective, always-available remote learning solutions that leverage the power and convenience of eLearning, multimedia, and robust help system technologies.
Enjoy the convenience of remote learning with our basic and advanced online learning portal. Our self-paced eLearning courses are available online 24/7 in interactive multimedia formats that make learning engaging and effective. These courses are designed to help you develop the fundamental skills required to successfully adopt and utilize InfinityQS ProFicient and InfinityQS Enact across your company.
InfinityQS offers instructor-led training (ILT) at your location. Courses include presentations and hands-on instruction that develop the knowledge and skills employees need to become productive quickly. Customer site training offerings are available on request.
We offer a variety of learning and performance support resources to broaden your knowledge and support your cloud SPC software deployment. The InfinityQS Enact Help Center provides convenient, always available access to training resources that support deployment, adoption, and optimization.
This exclusive workshop is designed to provide InfinityQS ProFicient users with detailed working knowledge of three important automated data collection software components: data management system, data collection service, and remote monitoring service. Reach out to your Advantive account manager for more details.
Elevate the role of quality in manufacturing to optimize processes, productivity, and profits.
“Are we capable of making high-quality products, day in and day out? InfinityQS ensures that we are.”
— Tracy McConnell, Vice President of Technical Services King & Prince Seafood
Quality management and checklists seem to go hand in hand. But the two aren’t synonymous. Inspections and checklists can’t drive meaningful, enterprise-wide quality improvements.
It’s time for manufacturers to move away from practicing quality management—and start mastering it. Mastering quality management means focusing on higher-level strategic goals that can be achieved through quality—such as reducing waste or lowering costs—rather than only day-to-day compliance metrics.
Think of it this way: Efficiency is a great goal, but it’s really just a means to an end. You strive for efficiency so that you have more time, material, and resources to get other, more important things done.
Likewise, quality management processes and tools can be used to address bigger-picture, strategic goals—while still meeting detailed customer specifications and compliance metrics. The exact same data and quality management tools that drive tactical, plant-floor-level improvements can be applied toward strategic outcomes.
On the plant floor, quality management centers on how data is gathered, calculated, maintained, and documented. Operators use real-time data to address issues that are immediate or urgent. Then, the data is forgotten. There’s little time for analysis. And “what-if” testing is typically a “no go.”
For most manufacturing organizations, quality management means managing metrics and controlling quality, but not necessarily improving or optimizing processes. Quality data is greatly underutilized—which means opportunities are missed.
There is a better way. Instead of collecting and forgetting your quality data, you can centralize it in a unified repository so it’s accessible for deeper analyses. Notifications, alerts, and calculations can be standardized and automated, making the data more accurate and reliable across sites. And by looking at uniform data across the organization, you can spot and address trends to achieve a greater impact.
When you extrapolate insights from your quality data—across your organization—the value of the data expands. With the right mindset, the quality data you’re collecting today can do more for your organization tomorrow.
Quality practices are essential for compliance with regulatory and customer requirements. But traditionally, they’ve returned little value to the organization beyond “checking the box.” Quality control has been essential in manufacturing—but not necessarily influential.
What happens when you elevate the importance of quality?
Manufacturers know it’s important to modernize equipment and tools. But if they’re not investing in the supporting processes and data that feed continuous improvement, then they’re not maximizing their investments.
How does quality data provide your gateway to digital transformation?
Caring about quality is nice—but it doesn’t help you achieve meaningful goals that improve products, performance, or profit. To do that, you need to establish standards—quality principles—across your organization.
How do you embed quality principles into your company culture?
Having enough data isn’t a problem for manufacturers; making sense of it is. A quality management discipline standardizes data practices, so leaders have access to data when they need it—and have confidence in the quality of that data.
What can your quality metrics tell you about your manufacturing operations?
Investments in quality far outweigh the costs of mistakes, inefficiency, and waste. And modern quality management tools build accountability, engagement, and quality into everyday work tasks. When you give workers the best tools for the job, the benefits add up.
How will you demonstrate the way to lower the cost of quality?
To optimize manufacturing production operations you must have access to your quality and process data in digital form. A well-designed quality platform can fuel a digital transformation for your entire manufacturing ecosystem.
What do you need to know when choosing a manufacturing quality platform?
Here’s some good news: You can improve quality using the same tools you rely on to keep production lines moving today. Both tactical and strategic approaches to quality management use a common methodology: Statistical Process Control (SPC).
The trick is to embrace SPC across the entire enterprise—and with the same discipline that’s applied on the plant floor. When you leverage modern, digital quality management solutions to create a comprehensive quality management discipline, it’s possible to optimize all of your manufacturing operations. Digital access to data empowers you to address quality across your enterprise: supplier and materials management, production, quality checks, packaging, and shipping. Digital tools enable your people, processes, and technology to come together.
Quality isn’t a one-person or even a one-department job; every level of the organization has a role in advancing quality. With access to the right information, each person is empowered to take the right actions at the right times.
Quality Professionals They are responsible for day-to-day quality control issues. Data collected on the plant floor informs bigger-picture quality issues and opportunities. To affect quality overall, plant floor operators and quality leaders need technology-enabled tools—such as tablets and other smart devices—so they can accurately and efficiently record quality data and control variance across shifts, products, and lines.
Plant managers They need a practical way to monitor and prioritize site- and line-level issues—without getting lost in spreadsheets. Most SPC tools have limited reporting capabilities, often relying on managers to retrieve, format, and compare data, and then hunt for conclusions. Different managers might arrive at different quality conclusions, priorities, and actions. An enterprise-wide SPC tool can bring pertinent information to the forefront by using automation to prompt actions based on rules and workflows—rather than leaving users to rely on “gut feelings.”
Corporate leaders They can elevate quality across the company by applying site-level best practices across the enterprise—if they can see them. With access to quality data from across the organization, executives can find and address improvement opportunities that will make the greatest impact. When viewed across the business, quality data guides decisions about resources, improvement projects, and future investment.
Quality management practices have to be in sync, line by line and plant by plant. Otherwise, data and performance metrics aren’t reliable or replicable.
Manufacturing is improved when companies use a standardized, enterprise-wide, technology-enabled process to collect, store, and analyze quality data. A unified approach helps manufacturers realize more value at every step in the quality management process.
During data collection, a digital quality management platform can prevent:
Manufacturing companies that use an enterprise SPC solution can avoid:
During reporting, companies using digital solutions can:
People and processes connect through technology. Picking the right quality platform is foundational to mastering quality management.
The right technology platform for your quality management practice:
That’s not a pie-in-the-sky wish list. With the advantage of cloud computing and Software as a Service (SaaS) delivery models, a robust quality platform is within reach of most manufacturers.
An investment in digital quality management is your gateway to greater digital transformation.
When you bring people, processes, and technology together to manage quality, you collect more than just data points. The data begins to tell a bigger story—providing prescriptive insights about how to improve quality.
Quality data analysis enables quality professionals and corporate leaders to spot meaning in their data. With a quality platform, instead of sifting through sifting through dozens of charts or raw data—hoping to see a pattern—you can immediately detect what’s hidden in that data.
Behind the dashboard, the software consumes and processes volumes of statistical data points—and issues of greatest importance rise to the top. That information is presented in an intuitive, graphical way that helps leaders ask the right questions—and take the right actions.
Manufacturers need software solutions that provide instant, easy access to actionable data—especially as the speed and complexity of operations increase. Clipboards and spreadsheets can’t keep up.
Digital transformation is a necessity—not a nice-to-have.
Organizations have options about how they transform their quality management practices.
The second approach is more ambitious—and possibly more challenging. But it also offers a much bigger bang for the investment—and produces measurable ROI across the business.
What’s the difference? Manufacturing optimization builds a framework for reaching more impactful, strategic goals. In a modern quality platform, all your quality data is stored in a purpose-built, centralized data repository. That allows you to coordinate sustainable and meaningful quality management practices across the organization.
Quality platforms improve products and manufacturing processes by ensuring SPC data is always compliant, prioritized, and applied.
Data that is integrated and accessible has more value to the organization—and to related systems and processes. With an integrated quality management platform, you can continuously investigate and improve quality.
Manual data management methods are time-consuming, frustrating, and vulnerable to inaccuracies.
In the free white paper, Moving Away from Manual Processes, you can learn how to use affordable, real-time SPC software and modern techniques to implement more effective approaches.
Consider these practical ways a quality platform helps manufacturers work smarter.
Quality engineers spend much of their time creating and checking charts to make sure product quality compliance requirements are being met. They’re asking: is data in spec? Are SPC rules being met? Is the right data being collected on time, every time?
With a quality platform, those questions are answered automatically. Managers are notified of issues and can take corrective actions quickly—then refocus their attention to higher-value problems.
Managers and quality engineers often spend more time collecting and formatting data than analyzing or applying it. Since they look only at granular data—at the site or line level—it’s hard to measure the magnitude of a problem. Plus, it’s easy to get sidetracked by proverbial “squeaky wheels.” At the corporate level, quality data is often inconsistent or incomplete from site to site.
With a digital quality platform, data from multiple plants and timeframes can be pulled together, benchmarked, and prioritized. Enterprise-wide SPC solutions create “report cards” of quality data that are easy to understand and share—so you can clearly prioritize the biggest risks and opportunities. Managers along the chain of command can see quality data and prioritize company-wide responses.
Many operators spend their time reviewing control charts—even digging into data to verify that it is correct. With more data and charts, it’s easy for operators to become overwhelmed or focus on the wrong charts. And do the charts really matter? A visual might be affirming, but it could also be a distraction.
A quality platform reduces complexity by creating reports and control charts automatically, then displaying information tailored to user roles. The software does the mundane repetitive tasks, like looking for violations, and alerts the right people (e.g., an operator or line leader) to fix the issue. That prevents people from looking for problems or correcting anticipated issues instead of actual, statistically confirmed problems.
In an effort to stay within compliance, every organization collects quality data. Most manufacturing organizations apply it tactically to measure and maintain quality—and that’s it. Quality data is then filed away, sometimes literally in filing cabinets, where it sits until an auditor or customer requests documentation. Then, the data is painstakingly retrieved, lacking all context.
With a quality platform, manufacturers can use quality management data to add value and advance strategic initiatives. Quality data never stands alone. It’s integrated with other information—such as supplier data and machine settings—and can be applied through a number of tools to benefit different users’ needs. When an organization’s quality tools and data are completely unified, the underlying intelligence becomes more powerful for the entire organization.
Monitor your quality control process with advanced SPC tools. Use an empirical rule chart, Pp and Ppk Fallout Rates tables and more control charts. InfinityQS Proficient delivers many SPC tools for businesses in need of process optimization and quality control. The following charts serve as additional SPC tools and resources, including Pp and Ppk fallout rates, control chart constants, empirical rule chart, capability study and capability formulas.
ProFicient™, the leading real-time Quality Management solution, goes beyond typical site-based quality applications by offering an enterprise-ready architecture and statistical process control. Still have questions or need help with SPC tools? Contact us today for more information about our SPC software. It’s time to re-imagine your quality control process.
Our software and services help you Define your objectives, Measure your products, Analyze your data, Improve your processes, and Control your quality.
InfinityQS Consulting Services will help you define your goals and business case, create a project scope and roadmap and determine a timeline.
InfinityQS Data Collection and Integration features allow you to input any type of measurement data into your system for analysis. InfinityQS Metrology tools help you ensure that your measurement devices are calibrated for accuracy and that your gages are functioning properly and yielding reliable data.
ProFicient employs highly sophisticated analytical tools and statistical equations that allow you to sort, slice and dice data in millions of ways, allowing extensive comparative analyses.
The data and analytics provided by ProFicient empower you to make real-time process improvement decisions. The software sends you instant alerts when your processes are out of control (or are approaching limits), allowing you to immediately fix your process before defects occur.
All of InfinityQS products and services are based on the principles of a controlled manufacturing environment for maximum quality and minimal defects. When your processes are in control, so are your products and your costs.
InfinityQS software plays a key role in implementing Six Sigma. Supported Six Sigma requirements include:
Taking the guesswork out of quality control, Statistical Process Control (SPC) is a scientific, data-driven methodology for quality analysis and improvement.
Statistical Process Control (SPC) is an industry-standard methodology for measuring and controlling quality during the manufacturing process. Quality data in the form of Product or Process measurements are obtained in real-time during manufacturing. This data is then plotted on a graph with pre-determined control limits. Control limits are determined by the capability of the process, whereas specification limits are determined by the client’s needs.
Data that falls within the control limits indicates that everything is operating as expected. Any variation within the control limits is likely due to a common cause—the natural variation that is expected as part of the process. If data falls outside of the control limits, this indicates that an assignable cause is likely the source of the product variation, and something within the process should be changed to fix the issue before defects occur.
With real-time SPC you can:
Visit our Case Studies page to learn how top manufacturers are using SPC.
To quantify the return on your SPC software investment, start by identifying the main areas of waste and inefficiency at your facility. Common areas of waste include scrap, rework, over inspection, inefficient data collection, incapable machines and/or processes, paper-based quality systems and inefficient lines. You can start to quantify the value of an SPC solution by asking the following questions:
For more detailed information about SPC and SPC software.
Learn more about Statistical Quality Control.
Updated: August 31, 2017 This Professional Services Addendum (“PSA”) supplements the terms and conditions of one or more license agreements (each, an “Agreement”) into which a client (“you”, or “your”) has entered with InfinityQS International, Inc. (“InfinityQS”) for licenses to one of its hosted services (each a “Hosted Solution”) or one of its on-premises software products (each a “Licensed Software Product”). These Agreements include the Master Subscription Agreement for the ENACT Hosted Solution, located here. The terms of this PSA are incorporated by reference in any Agreement between you and InfinityQS and in each Statement of Work into which the parties enter pursuant to this PSA. If there is a conflict between the terms and conditions of this PSA, the terms of an Agreement, or a Statement of Work, the precedence will be resolved in the following order: (1) the terms of the relevant Agreement, (2) the terms of this PSA, and (3) the terms of the applicable Statement of Work. The terms and conditions set forth in this PSA shall take precedence over any different or additional terms set forth in any purchase order you submit for Professional Services or any purchase order acknowledgment InfinityQS may issue. 1. Definitions. For purposes of this Agreement, the following terms shall have the meanings indicated.
2. Statement of Work. From time to time, you may request that we provide certain Professional Services relating to your use of a Hosted Solution or Licensed Software Product. When the parties agree upon the Professional Services for a Project, we will submit an SOW that sets forth the estimated schedule for the Project and the associated tasks. The parties will negotiate and sign the SOW. After we receive a fully-signed SOW, we will issue a Quotation reflecting the fees for the tasks associated with the Project. Each SOW shall be effective upon your issuance of a purchase order against the applicable Quotation. Each SOW shall remain in effect until InfinityQS has completed all Professional Services described in the SOW and you have paid us all related fees and expenses. Each SOW shall incorporate this Agreement by reference and this Agreement shall govern all terms of each SOW both parties agree upon and sign. Nothing in an SOW shall be interpreted as an obligation by either party to limit or otherwise restrict the assignment of its personnel or to constitute an express or implied license to any patents, copyrights, trade secrets or other intellectual property right of either party. 3. Fees and Payment. In consideration of our provision of Professional Services under an SOW, you will pay InfinityQS the fees specified in our invoices for such Professional Services and the reimbursable expenses described below. In addition, you will pay for travel time spent by our personnel at a rate of 50% of the effective hourly rate for the applicable Project, up to a maximum of sixteen (16) hours per visit; except that, if our personnel provide Professional Services on-site at your facilities for five (5) consecutive business days, we will waive all charges for travel time. Unless otherwise specified in an SOW, we will provide Professional Services on a time and materials basis and will issue invoices to you on a monthly basis for the Professional Services provided during the preceding month. You shall pay each invoice within thirty (30) days of receipt of the invoice. You acknowledge and agree that, unless otherwise stated in the applicable SOW, the fees indicated in the Quotation or an SOW for Professional Services other than training constitute good faith estimates based on our understanding of your needs and environment as of the date of the Quotation, and that the actual fees charged may be higher or lower than the estimates reflected in the Quotation. 4. Reimbursable Expenses. You will reimburse InfinityQS for the actual and reasonable travel, lodging, and meal expenses incurred by our personnel in the course of providing Professional Services under an SOW, in accordance with the following guidelines
5. Change Order.
Change Order. Either party may propose by a written change order any changes, additions, deletions, or modifications to an SOW. If the parties agree any such change will affect the amounts due or the time of performance under such SOW, the parties shall negotiate in good faith a mutually acceptable appropriate adjustment; provided, however, that the parties agree that any changes to an SOW or the fees specified in the Quotation will not be effective unless the parties have agreed upon and signed a written change order specifying such changes. 6. Assumptions.
The following procedures and assumptions will apply to all Professional Services provided under an SOW:
7. Warranty; Disclaimer of Warranty.
8. License Grant. Subject to the terms and conditions of this Agreement, including payment of all fees due and payable, we grant you a worldwide, nonexclusive, non-transferable, fully-paid license to use, install, display, perform, reproduce a reasonable number of copies of, and distribute internally any Deliverables we provide in the course of performing Professional Services under this Agreement, solely for your own internal business operations and solely in connection with your authorized use of a Hosted Solution or a Licensed Software Product. 9. Ownership and Retention of Rights. Except for the license granted under Section 8 of this PSA, InfinityQS retains ownership of and the right to use and apply in the performance of Professional Services for third parties, the templates, generalized knowledge, experience, skills, methods, techniques, and know-how of its personnel used in the performance of the Professional Services and the preparation of any Deliverables, as well all rights in any materials or other Deliverables we provide to you under this Agreement; except that, any of Your Data, your Confidential Information or your pre-existing materials that are included in any Deliverables shall remain your sole property.