Andy Jobson has been working in the medical manufacturing industry for 15 years, and every year he sees stricter FDA regulations and higher risk associated with product recalls. As quality director of Moll Industries, a contract manufacturer specializing in drug delivery and surgical instruments and devices, he says defects due to a manufacturing glitch are unacceptable to him as well as to his customers, their patients, and, of course, the FDA.
"If there is ever a defect in a manufacturing device and it causes harm to a patient, there is an FDA sequence of events that will happen, up to and including a recall," Jobson says. "And if it gets to the stage that they find a particular manufacturing process was at fault, ignorance is not an excuse."
Jobson knows firsthand what it feels like to be caught up in an FDA probe. Last year, one of his customers recalled a product for a defect that, in the course of an FDA investigation, was found to have resulted from a weakness within Moll's manufacturing process.
After finding the root cause and correcting the problem using failure mode and effect analysis (FMEA) software from Dyadem International, Moll implemented a comprehensive quality planning and management system that enables the company to make process changes in order to avoid producing a similar defect in the future.
As a result of that incident, the company not only tracks quality processes along the production line, but also has built a risk analysis template that includes a provisional flow diagram illustrating the manufacturing process design. Now, the company builds quality into its early manufacturing design and can flag anything that might cause a product defect down the line — even before it hits production.
While Moll is managing all of the quality data associated with the defect detection process, there are new products that Dyadem and others now offer that serve as a single repository of design and manufacturing data, including change management, risk assessment, hazard analysis, and data transfer and validation. This type of hub is part of an emerging technology trend in the medical device industry centered on quality lifecycle management (QLM).
Until recently, quality management (QM) applications were delivered in solution silos, such as corrective and preventive action (CAPA) software, traceability functionality within manufacturing execution systems (MES), FMEA applications, and even via the basic quality principles as defined by the ISO 9000 standard for QM systems. But quality can't be effectively managed in isolation, because each process impacts the next. Therefore, quality data has to flow from product design conception, to manufacturing, and out to field service. And, more important, quality management must extend to the entire supply chain, including outsourcing contractors, because everyone involved in making the product — even if it is a small component — is accountable.
"Within the medical device industry, supplier quality has always been a big thing, but the challenge has been having the capability to manage multiple [entities]," says Simon Jacobson, a senior research analyst at AMR Research. "It gets down to creating a bill of compliance that travels with the product from supplier to supplier and to the customer for complete traceability, and having an audit trail that provides the appropriate documentation to drive it forward, as well as to understand the compliance procedures, and, if there is a failure, to investigate the root cause."
The problem is that so many different data models are generated from the variety of systems used to design, plan for, and produce a product — for example, PLM, ERP, and MES. Each of these systems defines quality based on its functional role, causing confusion.
"Data quality is a broad and scary term that means so many things to many different people," says Stephen Arnett, CEO of DataNet Quality Systems, a quality control software vendor.