PhD Projects


Work Package 1
This WP deals with how variation from the functional requirement specification, affects the perceived quality of the product.  The design team along with the marketing department must try to specify the desired nominal values for functional performance in the form of a functional requirement.  Theoretically there will be an optimal value for the Functional Performance which will correspond to the highest level of perceived quality for the user.   Methods must be adopted so that the specified functional requirement can be as close to the optimal as possible.  Furthermore, it is important to know how any deviation from this specified value affects the user’s perception of quality.

Work Package 2
This WP deals modelling and optimising how variations in the product (the design parameters) affect the functional performance.  For example, how variations in the diameter of a pen lid (design parameter) affect the press-on force (the function performance).  Of course, there are multiple design parameters that relate to each functional requirement and thus it is also the task in work package 2 to understand how the variation in each design parameter is summed to a cumulative effect on the functional performance.

Work Package 3
This WP concerns process capability.  Each design parameter will be affected by a number of process variables such as feed rate, temperature, material variation, mould width, cooling rate etc.  Using similar techniques to those produced in WP2, in order to model how each process variable will affect the design parameter and how they are combined to give an overall tolerance window for a process.  This WP will also look at creating a Process capability data base so that the designers can begin to design to current process capabilities rather than specifying undesirable processes or using too much time on robust design when we are well within the limits of the current process capabilities.

Work Package 4
This WP ties the programme together with the aim to enable the project management to make investment decisions (time and money) on design changes and process capability improvements, based on the effects on quality loss.  By monetising the quality loss in the market, it will be possible to decide when it is work making investments to tighten up production tolerances and to what extent, and also when and to what extent it is better to invest in another design iteration to increase the product’s robustness.

Additional research requirements of the programme

Every project will have a deliverable to suggest suitable indicators (ideally both quantitative and leading) and to evaluate the effectiveness and accuracy of the indicators.

Case Studies
Every project will be supported with case studies at Novo Nordisk involving observation, analysis and experimentation proving the applicability of the theory, methods, tools and indicators medical device design and development.

Software and analytical methods
In order to take both the research and the implementation to the next level, state of the art software solution will be sort to enable Probabilistic Simulation, Sensitivity/Robustness Analysis, Reliability Analysis, Fatigue Life Prediction, Multi-Objective Optimisation.  At least one member of the programme will be an expert in such analytical approaches and the use of the software.