Our process improvement consulting company was contacted by a new design client requesting assistance in improving its quality management system (QMS). The company had used an existing system for several years, but it was still experiencing difficulties in making on-time delivery of designs; it had a higher-than-industry average, and missed customer requested dates in some cases. The designs themselves were sometimes nonconforming, having a higher-than-industry average for errors or missing a promised function. We agreed to work with the designers to identify areas of their QMS that could be strengthened, and to develop and implement a comprehensive quality plan to address these concerns.
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Closing the Loop on CAPAs with Quality Management Software by Mike Jovanis
Corrective and preventive action management is vital to an organization’s quality management initiatives. It ensures that issues that appear unexpectedly in the manufacturing process can be addressed quickly and efficiently, with procedures implemented that can make certain these issues do not repeat themselves.
Many companies fail to realize the advantages of a proactive, closed-loop CAPA process, integrated with enterprisewide quality management software to drive organizational efficiencies. With an effective CAPA procedure, aided by the right software, organizations can alleviate recurring issues that may arise in the manufacturing process, save time and resources, and help generate revenue.
Here are five steps to implementing a closed-loop CAPA system:
1. Deploy an effective electronic quality management system (QMS) for tracking incidents and events that occur, utilizing centralized software. Implement the system to log and manage all issues and incidents that have occurred. This will guarantee that the desired conclusion is reached when it comes time to correct issues, determine the causes, and take the necessary steps to prevent future occurrences.
2. Use your electronic QMS to apply escalation procedures to ensure that the correct people are notified of high-priority incidents, ensuring that these occurrences receive the necessary level of awareness and visibility.
3. An electronic QMS can help you correct problems expediently, and ensure that the proper incident approvals and routings have been executed prior to closure. Such software allows you to define the appropriate routings for different types or areas of problems.
4. Initiate preventive actions using investigation and root cause analysis. QMS software will help you maintain accountability by allowing you to assign responsible parties to investigate the catalyst for the issue and assign an identified timeline for resolution and a structured escalation process of overdue actions.
5. Employ routine effectiveness checks to measure how well the preventive solution is working at set points in time post-implementation. If appropriate, take additional action based on results of the check to ensure a true resolution of identified root causes.
By following these steps, organizations can effectively reduce the cost of quality operations and reporting, while increasing the level of regulatory compliance.
About the author Mike Jovanis is vice president of product management for Sparta Systems, an enterprise quality management solutions provider.
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Typically, for a new client, our first action is to assess its as-is/current state system, then develop a customized to-do list based on the discrepancies indicated when the assessment is compared to the company’s ideal state. Our analysis showed areas where the client had done a good job (this was independently validated by its customer feedback and third-party audits) and other areas where its system needed improvement (validated by customer feedback and internal audits). We knew we could install tools and techniques that would not only ensure the system conformed to customer requirements, but also exceed them in some areas. We set about to design a streamlined and productive QMS.
One challenge facing our client was long lead time in design, longer than industry average. To add insult to injury, designs didn’t meet customer requirements in some cases. We planned to tighten discipline in the existing QMS process and started by encouraging the designers to use project management methodology. We recommended they install a “lessons learned” database to monitor and report on mistakes made during the design phase; it would also document good practices and techniques for publicizing throughout the organization.
A lessons learned database helps identify what went right, what went wrong, and any suggested improvements for future designs based on “hard knock” lessons implemented during current design cycles. Across many industries, new designs are often derived from similar existing designs where some portion of the form, fit, or functionality is enhanced or replaced. Because many designs use 50 to 80 percent of previous design specifications, avoiding the same mistakes made during the previous design, and capitalizing on the benefits and enhancements discovered during that design process, can speed up the current design process considerably. Initial revisions tend to be accurate, and design costs go down accordingly.
During our discussion on the benefits of using a lessons learned database, we discovered that the client was using a quasi-lessons learned database already. Actually, six different databases--of varying ages, in different program languages, and with different initial foci--were accessed for this purpose. The problem in using these legacy systems was that they didn’t interact. To address this shortfall, the client had its IT group develop a portal that interfaced with the different databases and could display search results from all of them. This lessons learned database wasn’t slick and shiny, but it did represent something already in place. That was encouraging. So, next to “step one” on the to-do list--database in place--we could place a check (sort of). Our next step was to understand how often the databases were used for both input and output.
To determine the portal’s level of data completeness and accuracy of input, we selected a current product in design and then searched the databases to find previous similar designs.
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