Complexity is just about everywhere in manufacturing quality management, including deployment and configuration of your quality software, setting up and maintaining data collection plans, sifting through the rafts of data we collect, responding to issues in our processes, and much more.
Reducing that complexity starts at the ground level, ideally when you deploy your quality system for your organization. But even at that point, when you’re already looking at a highly complex organization, you may be asking lots of questions such as:
- Is this a company-wide, enterprise deployment?
- Or internal to your department?
- Or perhaps it will start with your department and then, over time, roll out to the rest of the organization?
- Is this state-wide? Regional? All of North America?
In addition, you need to know the goals of your deployment. Is this something you’re considering because you want to improve your processes? Is it a long-term commitment aimed at deriving benefits that directly improve your bottom line?
Lots of questions to answer. But one of the first questions to tackle is “Where do I start?”
The answer is: Start where you are—and start small.
Start Small and Scale
One great thing about InfinityQS quality management solutions is that they are scalable. You can start small (which means, hopefully, simple) and scale your deployment to whatever size fits your quality project.
For example, you can start by implementing data collection on something basic, like a brand-new part you’re going to release for a customer. Just one part; two or three features—but you need to do special data collections, perhaps even special reports, for the customer. All the data access, reporting, and submitting for this small project is the same information that you’d need for a big deployment. But starting small gives you the ability to control and understand the deployment. Then, when the time is right, you can scale up to a whole program.
Mapping the Structure—Why It’s Important
When issues occur—and we all know they will—you need to know exactly how your processes work in order to track down the precise point at which things went wrong. That’s a complex task.
But it’s easier to identify the root cause of an issue when you have a map to follow through the process. In the InfinityQS Enact® Quality Intelligence platform, this map—called a process model—provides a visual representation of your process to help you connect the dots from raw materials all the way to finished product.
One function of the process model is that it can help you accurately document your entire process from start to finish—something you might not otherwise do. Building the process model forces you to know what the inputs and outputs are for each operational step, what features are created along the way, and what and where tentacles branch off.
Building a process model without the Enact tool is a daunting task but Enact makes it easy. It takes the complex and makes it simple, visual, engaging, and online.
Data Collection: The Backbone of Your Quality Project
The types of data collections you plan to perform must be flexible, robust, and consistent. Whether it’s manual or electronic data collections, you need software that is capable of handling data from many sources. Your software should make it easy to manage where the data comes from, where it goes, and how and where it’s stored.
The foundation of data collection is standardizing the structure of the data. In practical terms, that means asking, “How are we going to tag the data?” At a minimum, we must tag each measured value with a part, process, feature, and timestamp. But there is a lot more to consider; for example, you might add employee, lot number, data collection name, customer name, reason for the data check, and any number of other bits of information.
Structuring the data upfront is important because later, during analysis and reporting, you will want to sort the data by these different tag fields. You can’t do the kind of sorting you will want to do unless you deal with tagging at the beginning.
However, tagging must also be flexible. You must be able to remove, update, and change tags. Perhaps you included tagging something like ambient temperature settings as part of your original plan. You obviously thought that was important at the onset but now you’ve decided that it’s just not as important as you once thought. You should be able to remove those tags on the fly. That’s flexibility in the face of complexity.
Analysis: Discovering Meaning in Your Data
Analysis and reports are important. What good is the data if you can’t explain it to management, or analyze it to determine what is working and not working on your shop floor?
Much of what happens during data collection is driven by the decisions being made at the backend by someone who reads your reports, responds to alerts, and makes process adjustments.
If you set up data collections correctly at the beginning, the analysis and reporting that occurs later on is that much better. Ask practical questions about the data you’ll be using in analysis and reporting, such as:
- Who are the customers of the data?
- Is the usefulness of this data limited to an operator on a particular machine? Or is there a broader audience?
- Is it destined for a manager? Or a department head?
- Is someone downstream interested in this data? Maybe they need information about what’s happening in the process to help them set up their machines.
InfinityQS tools enable real-time access to data to anyone in the organization who needs it, even if they aren’t at the data collection station. Having access to data from other areas of the organization enables every data user to make quick, informed decisions about their own processes.
Dashboards for Focus and Consistency
Dashboards are one of the best ways to access your real-time quality data and make it available to users at any level of the organization. On the plant floor, they quickly tell you when something is amiss or requires your attention. In Enact, they graphically display comparisons of any data you want—across lines, shifts, sites, or facilities—at a glance. And then, say you as an operator need or want to drill down into the data related to a particular machine or lot, you can easily do that and get to highly detailed information.
In Enact, dashboards combat complexity by providing role-based data access. Your dashboard provides the information you need to see based on your role; you don’t have to sift through a lot of extraneous information. You focus on your job, and when something needs your attention, you get real-time notifications in your dashboard. You remain focused on what’s important to you and continue pushing out quality product.
When you are alerted to a required data collection or a potential issue, it’s important to make it easy to respond in a timely way—and responses must be consistent for every user, across lines and plants. Workflows provide a simple solution by stipulating rules for how your organization reacts when an event occurs. By “event” we mean data and timing violations.
Data violations include manufacturing limits (e.g., specification, reasonable limits, net content control limits) and statistical violations. Timing violations include missed or late data collections and checklists. You may define any or all of these as exceptions to your day-to-day plant-floor operations.
The benefit of workflows is obvious: nothing is left to chance, and it’s easy for users to see what is happening—and what they need to do—at a glance.
Combined, all of these details help you manage and reduce complexity across your manufacturing operations. Even though manufacturing organizations are complex by nature, the right tools and a methodical approach can help you achieve standardization and scalability that is essential to optimizing productivity. When you have a handle on complexity, you can focus on doing what you do best: making quality products.
How can modern quality management solutions help you reduce complexity in YOUR organization? Please visit the InfinityQS website for more information.