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The purpose of the cases is twofold. First, they are intended to demonstrate how one can go about improving system quality, reliability and robustness by designing against the effects of random variability. Therefore, they are written in a manner that tries to communicate the thinking that went into developing the models used to analyze the case. Second, they are to provide examples to Robustica users on how to best use the software. Therefore, each case comes with an accompanying workbook that holds the model that was developed for the case. These models can be used with both the full version or trial version of Robustica.
We are always looking for more cases and we also want to help improve the way uncertainty is dealt with. Therefore, if you have a problem you would like considered please tell us about it; we can help you and share more knowledge with the greater community.
In the future there will be more cases, but currently there are two main categories: technical and commercial. Please take a look at any case that interests you and if you would like to find out more about how uncertainty management might be of help to you, please contact us.
A spring manufacturer is approached by a client who uses the springs in flow meters. There is a growing market for cost effective and accurate flow meters, and the flow meter company would like to take advantage of it. To do this, the flow meter company needs to improve the consistency of their product: can the spring manufacturer help with high quality springs, but at the same price? This case highlights the needs to be certain of the actual source of random variability and how it propagates through a system.
To date, snap fasteners have been a single application device. However, with the introduction of 'take back' schemes, appliance manufacturers now need to give thought to recycling, and disassembly. Is it possible to design a snap fasteners that will reliably keep the appliance together in everyday use but still disassemble easily enough for recycling? This case highlights the need to ensure that the nature of the random variability is properly known. It also highlights the significant benefit that can be gained by considering the effects of random variability prior to implementing a design.
New venture financing
Terry and Morgan have a number of financing options presented to them when they decide to buy the company the work for. However, there is risk and uncertainty associated not only with the venture itself but also with each of the financing strategies that they are considering. They must find the financing strategy that is most robust against the uncertainty associated with the venture and that also maximizes their the returns. This case shows the type of model that is needed for Robustica to be used for such problem and it also highlights the use of Monte Carlo when the results from Robustica must be verified. The author would like to acknowledge the influence of the HBS case Clarion Optical (case number: 9-393-116) on the development of this case.