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Jason Chester

Innovation

SPC and the Smart Factory: From Automation to Optimization

How we think about and use technology will determine ROI

Published: Tuesday, May 19, 2020 - 12:03

During the last several decades, many forward-thinking manufacturers have adopted factory automation for all that it promises—greater efficiency, consistency, productivity, and cost savings. In fact, if you walk through most modern manufacturing plants, you’ll see lines of machines performing a good majority of once-manual tasks, like molding plastic components or filling packages.

Such electro-mechanical automation has become a part of life on the plant floor. But even as manufacturers continue to want more value and new means of competitive differentiation, the truth is most have reached a point where automation is delivering fewer and fewer returns. We’ve picked all the low-hanging fruit—all the processes ripe for automation have been automated.

To move past this threshold and realize new and significant improvements to quality, process performance, and profitability, we must fundamentally change how we think about manufacturing. Namely, it’s time to shift the focus of factory transformations from the physical production process to decision-making—which has unfortunately seen little investment over the years. Even in the most highly automated manufacturing environments, we still have operators manually collecting data and populating spreadsheets that aren’t even reviewed immediately, prohibiting the timely discovery of issues and quality decisions.

Instead, this shift marks a leap from the manufacturing automation of the past to the manufacturing optimization necessary for the future, wherein manufacturers have intelligent means of understanding process performance in real time and can thereby make informed decisions to drive new improvements and better outcomes. It’s an evolution from having simply an automated factory to having a “smart factory” as part of the digital industrial revolution widely known as Industry 4.0.

Get smart

First, what is the smart factory? What makes it “smart?” Well, if you look in the dictionary, smart is defined as “having or showing quick-witted intelligence,” as well as “an ability to think or respond quickly and effectively.” Within the context of a production environment, that means being able to:
Sense—through collected data—what is happening on the plant floor with a high level of visibility and acuity
Understand—by analyzing those data—where the issues are, concerning trends, as well as the greatest opportunities for improvement
Respond and take timely, proactive action based on the resulting operational insights

Enabling the smart factory and achieving all of these things first requires that all quality and process data from enterprisewide manufacturing operations are captured and stored in a single centralized repository. This means replacing outdated data-collection procedures with advanced, real-time data collection workflows and integrating automated data collection from manufacturing equipment and sensors. Many manufacturers have already invested heavily in these infrastructures, and the data that are captured provide valuable operational insight beyond their primary purpose.

But just having all those data sitting in a central location doesn’t provide the immediate value necessary for manufacturing optimization. That value comes when we can extract meaningful insights from the data, and then deliver those insights to operators and operations management in an easily digestible format. This enables them to proactively respond to issues, reduce variability and uncertainty, and maximize performance. Having this real-time feedback and control is where statistical process control (SPC) comes in and why it plays a fundamental role in the smart factory.

Intelligence amplification

Quality professionals familiar with SPC will immediately think of control charts because they are a common tool used as a visual representation of SPC. But behind the charts are proven techniques for analyzing, monitoring, and predicting the performance of a particular process or product characteristic to detect variations from defined specifications. And today, quality teams can rely on SPC software to follow these techniques and run calculations—while the actual process is running—to identify abnormal trends and provide alarms and notifications before a nonconformance can occur.

In this way, we can think of SPC as a form of intelligence amplification, where smart technology augments human intelligence and capabilities. After all, human beings excel at cognitive tasks like problem solving. We can gather information from the world around us and apply past knowledge and skills to find ingenious ways of tackling hard issues. But we are less adept at interpreting densely populated data. SPC provides that bridge so human operators and quality professionals don’t have to review piles of spreadsheets and can arrive immediately at the right decisions. The continual automated monitoring that SPC software provides frees up cognitive workloads, ensuring that personnel can focus on responses to exceptions and troubleshooting.

For an analogy of intelligence amplification, let’s turn to the autopilot function on commercial airplanes. During flights, your pilot isn’t actually flying the plane the majority of the time. It’s the autopilot that’s behind the wheel—not because it wants to take control away from the human pilot, but because it can help reduce pilot fatigue, increase flight safety, ensure a smoother ride, and improve fuel efficiency.

Within manufacturing, SPC software is the intelligent autopilot—or rather, co-pilot—that shares in the cognitive workload, handles the rigors of analysis, provides enhanced situational awareness, and issues critical information when and where it’s needed to optimize manufacturing.

The new knowledge workers

Intelligence amplification through SPC will notably change how we perceive plant-floor jobs, where such employees traditionally are largely categorized as “blue-collar” workers. They will instead be more aligned to “white-collar” jobs as knowledge workers. Rather than walking the factory floor performing mundane and routine tasks, these smart-factory operators will spend their days using technologies, such as SPC, to continually optimize manufacturing process performance.

The benefits of SPC are by no means limited to the ground levels of the plant, either. When standardized across multiple products, production lines, and manufacturing sites, SPC software can provide visibility and operational insights to decision-makers at all levels of an organization:
For the supervisors or quality managers inside a plant, SPC can highlight the performance of multiple parts, processes, and features, enabling them to monitor wider fields of view and across longer time scales.
For a continuous improvement professional, SPC can help pinpoint where performance bottlenecks or quality risks exist to implement necessary changes.
At the executive level, business leaders and senior managers can leverage SPC as a form of business intelligence to monitor the performance, capability, and yield of multiple plants or regions, and find opportunities for companywide improvements to operation—and thereby the bottom line.

So, actually, in the smart factory—or smart enterprise—of the future, everyone is a knowledge worker, each empowered by intelligent, interconnected technologies that augment human decision-making. And at the heart of it all is SPC, which provides us with the ability to sense, understand, and respond to what’s happening on the manufacturing floor to drive optimization and new levels of improvement that yesterday’s electro-mechanical automation alone could never achieve.

Discuss

About The Author

Jason Chester’s picture

Jason Chester

As director of global channel programs for InfinityQS, Jason chester is responsible for the implementation, management, and overall success of the InfinityQS global channel partner programs. With more than 25 years of experience working directly within the enterprise IT industry, he has gained a deep understanding of how information technology capabilities can deliver significant and sustainable business value to end-user organizations. Currently, his main area of interest is the business impact of next-generation information technologies on industrial and manufacturing sectors—a topic he frequently writes about both online and in the press.