Med-Tech Innovation Materials
property databases to perform structured searches for materials that meet their specification.
Pros and cons of the traditional approach These typical approaches have many advantages. They get the job done quickly, which is a critical factor when time-to-market is important. They produce workable results. Furthermore, relying on what has been used before is low risk: regulatory or qualification problems seem less likely and it does not require new expertise. For many medical device organisations materials innovation is not a core competence compared with, for example, developing the therapeutic or engineering aspects of their products. They do not invest in extensive materials teams. Given these facts and the strict regulatory environment, it is unsurprising that designers are often satisfied with a relatively conservative approach to materials selection. But this approach has disadvantages. Most obviously, you cannot be sure that you have made the best selection. You cannot have full confidence in your choice. Your product may be sub-optimal in performance or cost, and it may lose out to a more innovative competitor. Also, without a systematic selection process it can be hard to explain and justify a material selection at a later date. This leads to problems if you need to refine product design. In particular, if you must replace the material, for example, due to a supply or regulatory issue, then you have to start from scratch in your analysis. In general, anything that diminishes the “auditability” of design is a negative for medical device manufacturers.
Even using materials databases does not solve these Figure 1: A
performance index for minimum volume limited by stiffness plotted against the index for minimum cost
problems. Although databases offer a more quantitative and auditable approach, they often contain incomplete data and focus on searching for materials with specific properties, rather than exploring the combinations of properties that determine materials performance. Designers can miss viable options, or produce results that meet their primary search criteria, but introduce additional problems, for example, toxicity or limitations on the processing route. Database searches often create the illusion of an exhaustive, systematic, auditable approach, without delivering the reality.
Rational selection
So how can we meet these three criteria: an exhaustive search; a systematic, repeatable method; and auditability in a manner that is quick, low risk and viable for organisations without large materials teams? Methodologies for rational materials selection are not
new. Professor Mike Ashby of Cambridge University first published the standard text on the subject, “Material Selection in Mechanical Design,” in 1992. His method divides design requirements into • Function: What does the component do? • Constraints: What essential conditions must be met? • Objectives: What variables then remain to be minimised or maximised? Typically, there are many constraints and a few objectives. Rational selection takes the “universe” of available materials, screens it based on the constraints, then ranks the remaining materials against the objectives. A formula known as a “performance index” can be used for ranking. This gives the combination of properties to minimise or maximise and thereby optimise a specific objective for a given design scenario; for example, to minimise the volume of a beam in bending for a given stiffness. Indices can be complicated and non-intuitive, but they have been derived for a wide range of standard design situations. In theory, all the designer need do is pick the right index for each of the design objectives and work out which material provides the best trade-off between them.
Imagine that we need to choose a material for the handles of some electrosurgical forceps. The function of the handles is to enable a surgeon to hold and manipulate the forceps. The handles must not deflect too much, therefore, must be relatively stiff. In engineering terms, we could think of them as short beams limited by stiffness. Now we specify some constraints: the material must be biocompatible, sterilisable by steam autoclave, tough so that it does not fracture easily, an electrical insulator, and so on. Then we establish some objectives; we can vary volume and cost somewhat, but prefer both to be small. Figure 1 shows the performance index for minimum volume for a beam limited by stiffness plotted against the index for minimum cost. Only materials that passed all constraints are shown. The best choices are towards the bottom left of the graph.
The first thing to note is that there is no clear winner. First, the designer must decide how to weight volume versus cost. But the graph makes it easy to see that glass fibre polyarylamide is a good compromise. Second, the designer can see the “landscape” of possible materials and explore alternatives. Third, the rational method has already screened out materials that do not meet the constraints of the application, therefore we can avoid problems due to properties not related to our design objectives. Finally, consider what would have happened in a more straightforward database search. We would probably have searched for the minimum “cost per kilo” rather than the more subtle “cost per unit of function” studied here. We would have found it hard to construct a search that explores the impact of modifying the handle design,
www.med-techinnovation.com November/December 2011 ¦ 19
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