Overall activity in deals jumped 11% in North America.
Mistake proofing is used in product, process, and service design and development as well as in ongoing operations and improvement applications. The goal with mistake-proofing is to find and correct mistakes, errors, or omissions as close to the source as possible, when the mistakes cost less to correct than if found later.
A root cause investigation may be formal or informal. Things happen, at work, at home, anywhere. The investigation methodology remains the same. Only the level of documentation changes to fit the situation.
We now test the possible causes against the facts in the IS / IS NOT Diagram to see which ones make sense. This is where the investments made in defining the problem and getting the facts pay off!
The third step of the investigation is to develop a list of possible causes. All too often investigators stumble at this point as they rely solely on the fish-bone diagram.
In this third of a series of articles on conducting a root cause investigation, we explore a second key investment every investigator should make: assuring you have the facts! Unfortunately, investigators are often under tremendous pressure to complete the investigation and assume the information they have is entirely correct. As a result days, or weeks, are wasted going down the wrong path.
In general, there are no short cuts in medical device product development. It is very difficult to leapfrog the iterative design process and develop a single prototype that will hit all the checkboxes – technology, industrial design, usability, proof of concept, manufacturability, etc., all in one go.
In this second of a series of articles on conducting a root cause investigation we explore a key investment every investigator should make: understanding the problem before defining a solution! Unfortunately, investigations often begin by brainstorming possible causes and prioritizing them for further analysis – leading to a trial and error approach resulting in a prolonged, expensive, and often failed investigation. With Step 1 we try to truly understand the performance problem.
While safety and efficacy are prime drivers, a med-tech product’s form and its function have a much deeper and stronger relation than one might assume.
The results of usability testing and expert reviews can be inconsistent across evaluators. How can we make these more reliable?