Process Signature Verification for Device Manufacturing
Medical Device & Diagnostic Industry MagazineMDDI Article Index Originally Published MDDI September 2005Process Verification
September 1, 2005
Medical Device & Diagnostic Industry Magazine
MDDI Article Index
Originally Published MDDI September 2005
Process Verification
Regulating manufacturing processes in the medical device industry is challenging. But process signature verification can help manufacturers get a handle on problems before they get out of control.
Laura Dierker and Nathan Sheaff
Table I. Sample processes and measured parameters. |
Most medical device manufacturers still produce and test in batches, counting on their process guidelines to ensure product quality. But unless all the variables can be controlled—from operator hand strength to ambient temperature to component alignment—it is impossible to guarantee that a process step is truly consistent.
It is possible to develop this consistency, but doing so hinges on understanding the physical effects of a manufacturing process. Characterize those well, and for most manufacturing processes, it will be clear whether a step has been successful or whether potential defects have been introduced.
For years, the automotive industry has used a technique of evaluating the physical signatures during an in-line manufacturing process to determine the success or failure of a particular process. This technique could also work well for medical device manufacturing.
The Link to Regulation
Before reviewing the process itself, it is worth drawing a link to the new regulatory environment that has come about with the acceptance of ISO 14971:2000. This standard extends the concept of risk management to “all stages in a medical device life cycle,” including manufacturing. Risk management techniques now include the concept of detectability (the ease with which a fault can be detected) in evaluating risk.
The ability to detect possible faults or problems is intrinsic to removing them from a product. Perhaps most important, manufacturing is the only safe place in which to monitor detectability. According to Mike W. Schmidt of Strategic Device Compliance Services (Cincinnati, OH):
Process FMEA [failure mode and effects analysis] introduces a third term into the calculation. During manufacture, when a defect that could result in harm is detected, action can be taken to either repair the defect immediately or impound the product until it is repaired. In these circumstances, the use of detectability to figure the RPN [risk priority number] is completely appropriate. The time lag between detection during manufacture and the actual use, where the harm typically occurs, is substantial.
However, detection of a hazard during use of the device may not assure that the harm will be avoided. An example of how detection can be virtually irrelevant to preventing harm would be as follows: The pin is pulled from a hand grenade with a 10-second fuse. After waiting eight seconds, the grenade is tossed into the room. It is detected, and then everyone in the room is dead. Detection in fact was irrelevant to the prevention of harm.
While the example is extreme, it shows that considering detectability as equivalent to severity and probability in determining the base RPN value is inappropriate when use [of the device] is involved.1
In other words, a problem must be detected while there is still time to do something about it, and the best place for that is during the manufacturing process.
Process Signature Verification
Process Signature Verification is an in-process monitoring method in which the signature for each part undergoing a manufacturing process is used to provide an objective evaluation of the success of that process. It can verify that the process adheres to specifications, and it can determine the presence or absence of identified failure modes or defects.
Process Signature Verification is based on the fact that physical variables change during a process, and that those variables can indicate the success or failure of that process.
Temperature, pressure in a cavity, physical dimension, angle of a part position, force used to couple parts, flow rates of liquids, change in electrical characteristics, and many other variables help determine whether a process has been completely and successfully reproduced (see Table I).
Process Signature Verification is itself a series of three steps:
• Collect a detailed data set while monitoring a process. This data set is the process signature.
• Apply a detailed mathematical algorithm (predeveloped during an experiment) to identify correct behavior versus out-of-spec behavior.
• Provide the results (pass/fail/
observed values as required) and store the information for records or future analysis.
What Is a Process Signature? Every person has a unique signature. This signature is made up of lines, curves, and squiggles and represents one person's name. No two people have the same signature, but one person's signature may vary over time. A process also has a signature. It is made up of the changes in physical characteristics that occur during that process. The data recorded as that process proceeds in time are known as a waveform. One process for a particular type of part will generate a unique waveform, which is the process signature.2
You can tell a lot from people's signatures. Are they happy? Are they sick? Have there been any major disruptions in their life? You can learn even more from a manufacturing process signature. Was the process successful? Did it vary? What went wrong? The signature tells a story. For instance, in Figure 1, the quick dip in the downward curve over the blue area shows that two pieces coming together were misaligned and had to slip back together. This may cause problems downstream.
How Does Signature Analysis Work? True signature analysis software systematically decomposes a signature curve into identifiable characteristics, typically through analysis of separate portions of the curve.
Figure 1. A process signature. |
The characteristics analyzed are those deemed to be most appropriate by scientific and process engineering staff, but are limited only by the availability of appropriate sensing equipment.
For example, each colored section of the curve in Figure 2 identifies a separately analyzed portion of a standard leak test. Each portion of the curve gives different information. In addition, each triangle identifies specific points whose placement and dimensions add to the evaluation of the process success. For example, leak-test studies have revealed the presence of rotating and damaged O-ring seals, bent or folded tubing, and part defects through proper analysis of a leak-test signature.
With appropriate analysis, even a simple test can yield significant process and component information. In implementation, a detailed data set is collected, and specifically determined features of the waveform are used to characterize the process.
Figure 3 shows an example of a classic press-fitting curve in which more than 60 significant characteristics and behaviors can be used to aid in analysis.
Figure 2. Components of a standard leak-test curve. |
Getting Value Out of Process Signatures. There are several ways to derive value from implementing Process Signature Verification in medical device manufacturing:
• It can provide objective evidence of process compliance to specifications. A well-behaved process will be repeatable and reproducible. The signature of this process will be identical within measurement accuracy. The signature can be used as the specification of expected process results or behavior.
• It can characterize and document the detectability of manufacturing-induced failures or defects. The best signature analysis packages currently available enable analysis of hundreds of curves as a single data set. This powerful analysis helps identify concise, repeatable indicators for even very subtle process effects. It frequently happens that with detailed review, there will be a potential for unknown defects within a process. Although this can be dis-concerting, it is better for you to find these failures than for your customers to find them in use.