We’ve come quite a distance, so far, in our blog series about why it’s probably time your statistical process control (SPC
) legacy system needs an overhaul. So far, we’ve touched on the impact of “islands
” of data within legacy systems in Part 1, the battle against inefficiency
and how real-time SPC
can help provide the insights you need to overcome it in Part 2, and how the limited capabilities
of legacy SPC systems ultimately deliver limited results in Part 3.
If your legacy SPC system is one of the many that has been kept in “maintenance” mode because you do not wish to update it and bring your manufacturing operations into the 21st
century, then this blog series is for you. Please continue on…
Complexity Comes in Many Forms
Across almost every industry sector, manufacturing has evolved into an increasingly complex and demanding endeavor. And there are several high-level reasons that are driving that change. [Once again, I find that I could write another whole article on a sub-topic—in this case, on the external forces driving that change—but…] Here are just a few examples that may resonate with your industry:
- Consumer trends are evolving with ever-increasing demand for better, faster, cheaper products across a wider variety of formats and often higher levels of customization.
- Consumers have greater availability of choice through online eCommerce, online marketplaces, and price-comparison platforms.
- Consumers are subject to greater peer-to-peer ratings, reviews, and feedback influence on a global scale, increasing the pressure on manufacturers to be at the top of their game.
- Consumers are becoming more ethical in their consumption, such as through conscious consumption, re-use, recycling, and upcycling.
- Consumers are becoming thriftier by using their money and other resources carefully and not wastefully. This “destigmatizing” of thriftiness is leading to low-cost online and physical retailers becoming commonplace in many countries.
- Consumers are thus becoming more “promiscuous” (less loyal) to established brands, creating higher levels of unpredictability and uncertainty of consumer demand.
- Consumers are more sensitive to responsibility in the manufacturing sectors, such as waste, sustainability, environmental impact, ethical manufacturing, and sourcing as well as corporate responsibilities and behaviors.
- The liberalization and democratization of markets through advances in global supply chains, logistics, and emerging market economies is creating more intense and volatile competitive markets.
And, of course, to add to those challenges are the uncertainty and risks caused by the impact of geopolitical issues on the flow of goods and trade (such as Brexit), as well as unpredictable events caused by natural disasters, terrorist activities, and as we have all become so acutely aware of in the last 18 or so months, global pandemics.
These forces do not just exert themselves on individual manufacturers or business-to-consumer manufacturers. They have a domino effect throughout the supply chain and thus impact on business-to-business manufacturers in equal measure. Quite simply, there are much greater levels of volatility, uncertainty, unpredictability, and intensity in today’s manufacturing sectors.
Manufacturers have had to respond with more increasing product formats, shorter production runs, and reduced lead times while at the same time maintaining high levels of quality in their products and in their operation’s efficiency and productivity.
Turning Manufacturing Challenges into Opportunities
Although these forces pose challenges, they are also sources of significant opportunities for manufacturers—whether established multi-national brands, new start-up manufacturers on a journey of growth, or anything in between. Manufacturers cannot address these increasingly complex challenges by just developing increasingly complex supply chain and manufacturing processes.
Just trying to scale traditional manufacturing approaches would have led to unmanageable levels of complexity, leading ultimately to a structural failure. Increasingly complex systems and processes are not the answer to solving complex problems. And this is what has principally driven significant amounts of innovation in the manufacturing sector, such as supply chain optimization and manufacturing automation, to significantly increase efficiency, productivity, agility, and quality.
Take a walk around a factory today (as I do a lot, although not recently, due to the pandemic restrictions!) and you will find an impressive display of manufacturing innovation, with automated production lines, intelligent sensors and controllers, robotics, vision detection, and automated inspection systems, to highlight just a few.
Legacy vs. Next-Gen
But these manufacturing processes are still physical
processes that are subject to variability, uncertainty, and unpredictability—and the more complex they become, the more difficult they are to manage. Which means that SPC is just as important, if not more so, than ever before to help manufacturers optimize those complex manufacturing processes to improve performance and achieve higher levels of manufacturing excellence.
As I have stressed throughout this series of articles, the problem is that legacy SPC systems have not been subject to the same transformative innovation as today’s modern manufacturing environments. That’s why they are referred to as legacy
SPC systems and not next-generation
As a result, these legacy SPC system implementations have become overly complex themselves, as manufacturers still try to rely on them to apply solid SPC principles to these modern manufacturing environments. Which, for many clients that I speak to, frustratingly feels like trying to fit a square peg in a round hole: it just doesn’t seem to fit anymore.
They have become difficult to use, difficult to manage, difficult to understand, and perhaps most importantly, more and more difficult to gain the substantial benefits that SPC still has to offer. Quite simply, they have become part of the complexity problem, not part of the solution, which surely leads to the obvious critical question “are they still fit for purpose?”
A Solution that Fits: Access Advanced SPC in Enact
from InfinityQS was first on the drawing board, we knew that we had to radically rethink how SPC solutions were designed and applied to support the future of manufacturing.
What emerged from those decisions was an entirely new, next-generation solution that was built from the ground up as an enterprise-class next-generation SPC solution able to support increasingly complex and demanding manufacturing environments well into the future.
While there is much greater depth of information in our Quality Check blog
, and across the InfinityQS website, covering the industry-defining features of Enact, I want to highlight some of those key innovations, which are helping manufacturers across the world address the challenges of complexity—specifically, data centralization, usability, the process model, and exception-based reporting.
A Centralized, Cloud-based SPC Solution
Legacy SPC systems relied on isolated siloes of data. We knew that Enact had to be architected around a secure, single, unified, cloud-based repository. The benefits of this architecture are significant—data and information, such as parts, processes, specification limits, data collections, and quality check requirements, for example, are all stored in, and managed from, a single location. A specific part (stock-keeping unit, or SKU), for example, can be defined once and used anywhere in the organization that it is manufactured. A specific data collection or quality check requirement can be defined once and used consistently across the entire organization, and so on.
This principle of reuse promotes a high degree of standardization that is otherwise difficult, if not impossible, to achieve. This significantly reduces the complexity involved in managing and maintaining processes and data across entire manufacturing operations.
Going beyond this metadata, measurement and checklist data that is captured throughout manufacturing processes are also stored in this single unified location. This enables consistent analysis and comparisons to be performed at any level and from any dimension across an entire organization—region by region, plant by plant, line by line, process by process, shift by shift, product by product, and so on. In just a few clicks we can go from a highly aggregated summary of a region’s performance, down to the individual analysis of a particular feature on a particular part, on a particular process.
Another important aspect of a cloud-based solution is universal access. Via a web browser, Enact’s capabilities can be accessed by any device, at any time, and from any location. Whether that’s an operator on the shop floor at a fixed workstation, a supervisor using a tablet, or a plant manager using a smartphone on the road.
Not only does this mean that existing IT infrastructure can be used without the need for dedicated workstations and servers for SPC applications and databases; it also means that we are no longer dependent on these fixed application workstations to access these valuable capabilities. A benefit that has become much needed in the wake of the pandemic…not just to support remote working
, but also to prevent shared surface touches on shared workstations.
The Usability You’ve Been Looking For
As alluded to above, the workforce is challenged enough with operating and managing their manufacturing environment—they certainly don’t need to be managing and navigating a complex and inefficient legacy SPC system, too. The Enact user interface was therefore a critical consideration in the tool’s overall design.
The result is a very clear, highly intuitive, and simple user experience with emphasis on the rapid access to the relevant information, insights, and intelligence required to make proactive decisions. Enact guides the operator through the process of data collection, quality checks, and checklist completion and provides real-time feedback in response to the data being entered.
With Enact, operators can also receive visual cues as to which data collections need to be performed, as well as how they need to be performed. Enact’s dashboard design is utilized throughout the user interface—dashboards can be created using individual tiles to display specific types of information or visualizations. And a single dashboard can be reused by many different roles (subject to a user’s access level) with the scope of the information that the dashboard should contain determined by the selected parameter set or data filter options.
For example, a filling line operator on a particular line may use the same dashboard as a packaging process supervisor, with each seeing only the information relevant to their work responsibilities.
Modeling Your Processes
Another innovative feature of Enact is what we call a “process model.” A process model provides an intuitive way for manufacturers to create a visual representation of their real-world manufacturing processes, how they relate to each other, and the data collection requirements for each process.
In Enact, the process model is many things: it’s visual, it’s functional, it allows you to build things out in step-by-step fashion (which is convenient), it’s expandable, it helps you error-proof your processes, and it centralizes and simplifies the ways in which you manage your operations. We designed Enact’s process model functionality to greatly benefit end-users, and that is a major part of the game in today’s software world.
But ultimately (and on the theme of this article), it helps manufacturers better manage the complex interplay between different processes across the entire manufacturing operations, from raw materials input to finished goods output. My colleague, Eric Weisbrod, InfinityQS VP of Product Management, talks in depth about Enact process models in his blog, The Joys of a Process Model
Enact takes an “exception-based” approach to process monitoring, reporting, and quality control. With legacy SPC systems, operators and others spend a lot of their time watching control charts, and monitoring process parameters and quality measurements…waiting for something to happen. That something is when an abnormality occurs in the process, a statistical trend, a control limit, or specification limit violation, for example. The prevailing wisdom is that unless you’re watching these control charts with a hawk’s eye, then you might miss that all-important signal or event and be caught unprepared to respond.
But the reality is that you spend most of your time monitoring processes that are running just fine and have (at that precise moment) other issues to deal with. That’s an inefficient use of resources by any measure. Not to mention the temptation for operators to tamper with, or over-control
, a particular process and potentially make a good situation worse.
When we have manufacturing environments with complex processes, that waste of resources increases exponentially with an army of “control chart watchers.” And that is exacerbated by the limitations of legacy SPC systems, which may mean that you indeed must continuously watch control charts to know when an issue is occurring or is about to occur. It’s a vicious loop. (Eric wrote a blog article on this very topic, Do Operators Need to Keep an Eye on Control Charts All the Time?
Check it out.)
However, just as we now rely on automated manufacturing processes to take the leg work out of physically laborious and rote processes, Enact automates those processes and SPC monitoring “under the hood,” so to speak. Every measurement value that enters Enact is evaluated in real time against that part-process-feature stream. If the process is not subject to any abnormal trend, or violation, then all is well.
If, however, the opposite is true, then notifications are triggered in real-time through the Enact user interface and by email to the relevant responsible parties. This reminds me of the famous philosophical thought experiment that raises the question of observation and perception: “If a tree falls in the forest and there is no one around to hear it, does it make a sound?”
With our exception-based monitoring in Enact, the question could be posed, “Is statistical process control being done even if there is no one watching a control chart?” The answer, of course, is a resounding “Yes.”
Enact is continuously “watching” all the control charts all the time and will notify you immediately when one needs your attention. That is a much more efficient method of applying next-generation SPC in the modern manufacturing environment, freeing up operators and others to focus on the areas and issues that do need their attention, without the distractions of worrying about areas that don’t.
It also works to address some of the issues around managing increasingly complex environments—by being able to effectively deploy SPC-based monitoring across the entire manufacturing operation, 24x7, without overwhelming your human workers.
We’ve all heard of the phrase “information overload,” or perhaps, “data rich, information poor.” These phrases both point to the same underlying issue, which is that we often find ourselves lost in a sea of data where we struggle to make sense of it, feel overwhelmed by it, or are unable to spot the “nuggets
” of information that could potentially tell us something meaningful.
Look around your own manufacturing environment and I bet that you are not short on data. That data is everywhere—on pieces of paper, spreadsheets, management reports, in ERP/MES systems, on machine HMIs, gauges, sensors, SCADA systems, notice boards, And...you guessed it...in legacy SPC systems.
It’s a complex array of data sources and extracting meaningful insights from them can be even more complex. Which means, generally, we don’t
—because we simply cannot see the forest for the trees. When an issue occurs, we try and find the data to diagnose the problem. But what if we don’t know a problem is occurring in the first place? What’s the saying? “You don’t know what you don’t know?”
But back to the theme, already in progress…complex data environments are not the best way to manage complexity
. We need to take all that data and streamline it into a single, unified system—from which we can get to the insights and actionable intelligence quickly. And that is an area in which Enact excels.
Unified with Enact
Much of that data integration, real-time statistical analysis, and processing happens “under the hood” and Enact presents the user with the analysis of the underlying data in a simple and intuitive format. Let’s take one example, the unique grading
capability in Enact.
At the highest level this can show, for example, the performance of each critical feature across all plants using a grade A1 to C3. Clicking on an A3 cell, for example, for a particular site and feature immediately shows how that feature is performing across different lines and products across that site.
Instantly (within a click or two), we can immediately pinpoint where we have potential issues, or where we have opportunities for quick wins in terms of performance gains. (The grading capability is explained in detail in this blog article
To achieve that same level of insight without Enact would take a whole lot of time and effort, and a whole lot of statistical wizardry! This illustrates how next-generation SPC solutions, like Enact, can mitigate data complexity and turn what might currently be “information overload” into easily-accessible, intuitive insights and actionable intelligence
For many reasons, modern manufacturing is becoming increasingly complex and legacy SPC solutions are outgrowing the needs of these environments.
Statistical process control should be part of the solution, not part of the problem.
Just as InfinityQS has re-imagined quality with our next-generation SPC solution, Enact, perhaps it is time for you to re-imagine how overhauling your current solution is probably overdue, and doing so would enable you to further transform your manufacturing operations.
Please come back for the final article in our series about overhauling your legacy SPC system: Part 5: The Big Easy
Read the other articles in this series: