Are You Quality Obsessed? 7 Steps To An Effective Quality System (Control Engineering)

View article online.

How To Establish An Effective Quality System: Statistical Process Control (SPC) Can Help.

By Steve Wise

Without a doubt, manufacturers today are under more pressure than ever to ensure the quality of their product, especially given the growing number of strict industry regulations. If the smallest part or ingredient is out of spec and a recall occurs, it is not only the manufacturer, but the entire supply chain, that is at fault. All it takes is one negative headline about a defective engine or a contaminated package of spinach to jeopardize a brand’s reputation.

The companies that avoid negative press are the ones that truly embrace quality as a business function and recognize the value of an enterprise quality system. These manufacturers exert a tremendous amount of effort to secure their respective industry standards—whether Six Sigma, the Good Housekeeping Seal of Approval or positive reviews on CNET—and interestingly, all demonstrate the same habits when it comes to ensuring the quality of the products they produce.

By emulating the habits of these quality-obsessed manufacturers, you can make certain that a quality product runs through your facility and reaches the consumer, while making your entire manufacturing organization more effective along the way.

  1. Brag about your quality.Customer satisfaction can make or break a manufacturer. Therefore, it is imperative to give upper management the data they need to build customers’ confidence in your product. Sure, you can claim to produce a top-quality product, but sometimes your word is not good enough. Buyers want to see data that is meaningful to them, not just the required Cp (variation measurement) and Cpk (center tendency measurement). With a statistical process control (SPC) system, you can present upper management with data that quantifies quality in clear terms.

    Most importantly, do not hide your data from the top brass; transparency is vital. To begin effectively bragging about quality, create a list of metrics and divide them into two groups – metrics that are impressive now, and metrics that, if improved, will help achieve higher organizational goals.

  2. Do what counts. Now that you know the importance of data, keep in mind that more does not necessarily mean better. Data collected must have value, and should be concise. Consider the following when determining whether the data you are collecting is meaningful: If the data values significantly change, from the norm, during production, would the change lead to a corrective action? Also, if a corrective action is needed, is there a procedure in place to deal with it?

    Prior to monitoring a process, make sure you have an effective sampling strategy and systems in place to take corrective action. Be sure to decide which employees are able to take action based on real-time data intelligence and provide them with the necessary reports to do their job the best they can.

    [Sidebar: How can you know who needs the data? In the case where data are already being collected and reported, be bold and challenge the status quo. At one large airframe manufacturer, a new manager wanted to find out who needed, or was even reading the numerous scheduled reports his department generated. He decided to stop all publications and wait for the phone to ring. He got all his answers in just a couple of weeks. Using the feedback from the few that contacted him, he completely revamped the reporting content and schedules.]

  3. Give the process a leading role.True SPC involves three components: the process, the test characteristics being monitored, and the part being produced. When collecting data, the most important of these factors is the process, as it controls the consistency of the final product and influences manufacturing as a whole.

    The process is needed to produce test characteristics, and test characteristics are needed to produce parts.  Therefore, it is vital to include processes in your data collection and analysis – you will achieve new insights by monitoring even the seemingly smallest pieces of the process, such as which nozzle filled a particular container.

    Remember, the machines (processes) in your plant that are most critical to quality, and make sure that you have a system that can measure their performance.

  4. Keep it simple. With the right SPC software, capturing data should be a simple process. If data collection is difficult, an organization risks capturing inordinate amounts of meaningless data. Select an SPC platform that displays only what is helpful to the user. Visualizations, charts and even user-friendly spreadsheets are ideal. The software should also automate calculations and prompt users when specific quality checks are due.  It’s important to make sure that your shop floor systems are optimized for your shop floor environment so data can be accurately collected.

  5. Expect a value chain reaction.Always remember, suppliers are an extension of your factory. The quality of the suppliers’ products directly affects your final output.

    For example, what happens if an automotive manufacturer unknowingly assembles a car with a supplier’s defective transmission? With  cloud-based SPC, manufacturers can extend quality throughout the supply chain—all the way down to the suppliers—so the faulty transmission, for instance, never even makes it to the production line.

    The transparency provided by cloud-based SPC will ultimately increase profitability for both the supplier and the manufacturer by reducing scrap. If you are considering implementing a supply chain-wide, cloud-based SPC solution, begin by discussing the value of sharing real-time data with your customers and suppliers.

  6. Always be vigilant.Control chart plot points will send one of two messages: Do something, or do nothing. As the “first life of a data point,” both are equally important.  When you see the ‘do something’ message, you should be able to decide on a course of action simply by comparing the data point with the previous plot point.

    You must also understand the natural process variations so that you know when to avoid taking action. Don’t tamper with the process if the signals are telling you to ‘do nothing.’ Make the control charts more meaningful by finding the earliest possible point to capture the data and be vigilant with responding to those messages.

  7. Always dig deeper. What happens to all the real-time data you’ve collected? A process capability database houses the once real-time data. You can use this database to gain insight on how to improve processes in the future. Even the simplest data, such as lot numbers and raw material suppliers, can provide value and help you pinpoint their effects on a process’ output.

    Furthermore, the process capability database can make additional calculations that can lead to more accurate business decisions on a variety of levels, including make/buy, scheduling and raw material usage. You can improve your organization’s ability to use data analysis to “predict the future” by identifying attributes that  affect process outputs.

These seven simple steps will increase your organization’s understanding of the impact quality has on operational efficiency and the bottom line. Data are your greatest assets for gaining visibility into causes of quality issues and  quick analysis often equals quick resolution. The correct approach to quality control yields benefits ranging from reduced scrap, rework and warranty claims to audit and recall management; from supplier benchmarks to customer satisfaction.

Perhaps more importantly, these seven steps lay the framework for making your company more data driven. By working smarter, you will eliminate the day-to-day headaches caused by fighting fires and replace them with a balanced, systematic approach to quality control.

Take the first step from quality to excellence