And this in turn, saves cost and time of producing and using multiple parts. Spending an appropriate amount of time at this phase greatly reduces the risk that we will have to repeat the DoE because of unsatisfactory results. These are ranked in order of likely impact.
We also sort and evaluate all the possible input variables that could influence the process outputs.
In the planning phase we build a map of the process by fixing the acceptance criteria as reference for the optimization of the working parameters.
Modelling: where the optimal working point is found, and process margins are verified.Screening: where we begin to understand how the process works and identify the key parameters to be controlled.Planning: in which the process map and test plan are engineered.The execution of a DoE, as described in this article, goes through three main phases, each of them has its own specific purpose and target: A titanium (or aluminium) horn engages the upper part and combination of pressure and ultrasonic vibrations heat the material in contact between top and bottom halves, welding the parts together
Top part is placed on top, free to move vertically. In our example, all the analysis has been done with support of minitab software.įig.1 Design details: simplified overview or the product and cross-section of the welding areaįig.2 Principle of the Ultrasonic Welding technology of plastics: Bottom part is kept in a stable position on a nest, not free to move. The design has a double V-joint shape, thin walls and no containment for the material melted during the process (see. The design does not allow for flashes of molten material (cosmetic restriction) and requires high mechanical strength. In the example below, we will examine how DoE was performed for an ultrasonic welding on an external shell of a small circular object made in polyoxymethylene (POM). This DoE approach brings considerable advantages over traditional methods like ‘one variable at a time’ (OVAT) or ‘trial and error, and is even more valid when there are complex or challenging design requirements. This approach means that we study and validate the relationship between multiple process input variables and key output variables, in a structured way to swiftly identify the optimal point at which the process outputs (within margins) satisfy the product requirements and remain stable over time. One of the most useful and proven approaches we take at Flex is based on a structured and analytical method called ‘design of experiment’ or DoE. Better analysis helps us speed the process between design and manufacturing to meet those all-important time-to-market expectations of consumers and patients. Today, we must also use analytical methods to ensure consistent production quality, and accurately predict future device performance. This is especially true for medical device makers.Ī reliance on a process engineer’s expertise is no longer enough to meet long-term reliability and performance objectives.
A high bar for device manufacturers to sustain.Īs the pace of technological change quickens, and feature packed devices become smaller, manufacturers face ever-more complex assembly processes.
The rapid evolution of portable electronic devices like mobile phones has primed consumers to expect frequent feature enhancements and regular technical advances in other devices. That’s a predicted growth of $300 billion from 2020 levels. Lower cost, more availability, ease of use and compelling new features like connectivity and storage are set to drive the market to over one Trillion USD by 2027 according to a recent report by Fortune Business Insights. In the last few years there has been a dramatic increase in the variety and volume of consumer electronic devices.