Quality Management is a critical process for any manufacturer, however - one of the most challenging ones. The cost of scrapped products that don’t meet a customer’s quality standards can be quite significant if the quality issue isn’t caught in time. Today with more environmental focus on waste, landfill becomes a greater evil. Scrap may be reintegrated to the production process at a certain cost (best case scenario), but sometimes, especially when non conforming products are detected at the end of the production cycle, they can’t be re-used, and therefore become trash. Worse case scenario, non-conforming products are shipped to your customers, who rejects the order and hurts your corporate reputation/branding and even cost you to lose the client.
It’s a fact that almost 80% of all quality issues are repeat issues. That makes me believe that most organizations lack the ability to capture, continuously improve, and leverage performance knowledge from lessons learned so that preventive action can be taken. Additionally, I attribute this problem to the imminent challenge of integrating, tracking, sharing and analysing quality data that comes from many sources and processes within the organization. Most companies still rely on disparate spread sheets manually populated and maintained.
In my opinion, quality management is not just about inspection activities and “after the fact” reviews to implement corrective actions. It’s about enabling and optimizing the quality strategy deployment with real-time actionable intelligence to best predict non conformance production before it happens and immediately invoke behavioural change to correct the problem.
Taking the above points into consideration, I believe that technology can play a very significant role in the Quality Management process; the “trick” is to ensure that only “best-in-class” solutions are implemented, ideally, based on the following evaluation criteria:
- Predictive Quality Management: It should provide all necessary quality information and alerting in real-time, to address quality issues BEFORE they occur.
- Global and Integrated Solution: It must be able to consolidate quality data from disparate sources, standardize it, analyze it and display it through interactive role-based dashboards for different staff categories involved in the quality management process. Also share this information globally to learn “best practices” site to site.
- Quality Continuous Improvement: Find a solution that enhances quality planning through improved visibility of previous and existing quality issues, permitting the “never ending” cycle of quality improvement and permitting to allocate resources where changes are most needed
- Compliance of Batch Manufacturing Quality “current Good Manufacturing Practice – cGMP”: Batch consistency, validation, documentation and traceability will allow you to demonstrate that all the steps required by the defined procedures and instructions were in fact taken, and that the quality of your product was as expected.
I would love to hear your comments regarding this posting. Any insight provided about the challenges you are facing in your quality management process will be very valuable for me.
