Project and portfolio management system design for a renewables development company

Atmospheric CO2 levels have been strongly linked to climate change, and a significant amount of emissions is produced by the energy sector. Thus, decarbonising electric energy production by shifting from fossil-based production to renewable energy sources poses a great potential for emission reductions. This requires the development and installation of a lot of new capacity in renewable energy technologies, including wind power. As a result of EU mandated emission reduction targets, Finland has been experiencing a ‘wind power boom’ over the past decade or so. The renewable energy industry’s growth has resulted in new challenges in managing and organizing work related to wind farm development projects. This case study investigates from a systems thinking perspective how an organization’s project management practices can be improved and made more resilient to strong growth of the organization. The specific context of the project business under investigation is Finnish onshore wind farm development projects. The research is done by familiarising with relevant literature on project management and systems engineering as well as with the case company and its ways in managing an increasingly complex project portfolio. The study suggests that building a modular and dynamic management system with a user centred focus will benefit rapidly growing companies in managing both their work and growth. Additionally, we observed that such a system improves the flow of information within an organization, aiding strategic decision making and project and portfolio control. A systems engineering solution would also benefit companies experiencing more moderate growth, as it would increase organizational transparency and provide an incentive to identifying and defining workflows and best practices within the organization. We propose that the findings of this case study could be generalised to any small-to-medium size growth company that is managing project-based work

A stochastic shape and orientation model for fibres with an application to carbon nanotubes

Methods are introduced for analysing the shape and orientation of planar fibres from greyscale images of fibrous systems. The sequence of image processing techniques needed for segmentation of fibres is described. The identified fibres were interpreted as deformed line segments for which two shape and two orientation parameters are estimated by the maximum likelihood method. The methods introduced are shown to perform quite well for simulated systems of deformed line segments with known properties. They were applied to TEM images of carbon nanotubes embedded in polycarbonate