We examine how project complexity influences the choice of a project management strategy and present a framework that facilitates managers in selecting a suitable project management strategy. We distinguish the complexity of project domains from two dimensions, the degree of structural complexity and the degree of dynamic complexity, resulting in four generic project types. Four generic project management strategies are identified that match these project types. This complexity framework for project management allows key players to determine a better project management strategy and related practices given its content, the internal context, and the external environment.
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Engineering students have to learn to create robust solutions in professional contexts where new technologies emerge constantly and sometimes disrupt entire industries. The question rises if universities design curricula that enable engineering students to acquire these cognitive skills. The Cynefin Framework (Kurtz & Snowden, 2003; Snowden & Boone, 2007) can be used to typify four complexity contexts a system or organisation can be found in: chaos, complex, complicated and obvious.The Cynefin framework made it possible to create the research question for a case-study: To what extend does the Business Engineering curriculum enable bachelors to find business solutions in the complexity contexts of the Cynefin framework? The results show that 80% of the methods are suitable for complicated contexts and no distinction is made between contexts. This means students are taught to approach most contexts in the same way and are not made aware of differences between the contexts. Making sense of the methods in the curriculum with the Cynefin framework was insightful and suggestions for improvement and further research could be substantiated
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For five decades complex socio-technical systems have been studied in an attempt to understand and prevent the occurrence of accidents. In this paper, the authors define a concept for a System Complexity metric, comprising the total of all direct interactions between the system elements and the tools the controller has to control the system. Subsequently, the human performance of the operator is taken into account to arrive at the Perceived System Complexity. Finally a hypothesis for a relation between the dynamic actually perceived system complexity, and the occurrence of incidents is postulated, which are still to be proven in practice.
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Logistics represents around 10-11% of global CO2 emissions, around 75% of which come from road freight transport. ‘The European Green Deal’ is calling for drastic CO2 reduction in this sector. This requires advanced and very expensive technological innovations; i.e. re-design of vehicle units, hybridization of powertrains and automatic vehicle technology. Another promising way to reach these environmental ambitions, without excessive technological investments, is the deployment of SUPER ECO COMBI’s (SEC). SEC is the umbrella name for multiple permutations of 32 meter, 70 tons, road-train combinations that can carry the payload-equivalent of 2 normal tractor-semitrailer combinations and even 3 rigid trucks. To fully deploy a SEC into the transport system the compliance with the existing infrastructure network and safety needs to be guaranteed; i.e. to deploy a specific SEC we should be able to determine which SEC-permutation is most optimal on specific routes with respect to regulations (a.o. damage to the pavement/bridges), the dimensions of specific infrastructures (roundabouts, slopes) and safety. The complexity of a SEC compared to a regular truck (double articulation, length) means that traditional optimisation methods are not applicable. The aim of this project is therefore to develop a first methodology enabling the deployment of the optimal SEC permutation. This will help transport companies (KIEM: Ewals) and trailer manufactures (KIEM: Emons) to invest in the most suitable designs for future SEC use. Additionally the methodology will help governments to be able to admit specific SEC’s to specific routes. The knowledge gained in this project will be combined with the knowledge of the broader project ENVELOPE (NWA-IDG). This will be the start of broader research into an overall methodology of deploying optimal vehicle combinations and a new regulatory framework. The knowledge will be used in master courses on vehicle dynamics.
The increase in the number and complexity of crime activities in our nation together with shortage in human resources in the safety and security domain is putting extra pressure on emergency responders. The emergency responders are constantly confronted with sophisticated situations that urgently require professional, safe, and rapid handling to contain and conclude the situation to minimize the danger to public and the emergency responders. Recently, Dutch emergency responders have started to experiment with various types of robots to improve the responsiveness and the effectiveness of their responses. One of these robots is the Boston Dynamic’s Spot Robot Dog, which is primarily appealing for its ability to move in difficult terrains. The deployment of the robot in real emergencies is at its infancy. The main challenge that the robot dog operators are facing is the high workload. It requires the full attention to operate the robot itself. As such, the professional acts entirely as a robot operator rather than a domain expert that critically examines and addresses the main safety problems at hand. Therefore, there is an urgent request from these emergency response professionals to develop and integrate key technologies that enable the robot dog to operate more autonomously. In this project, we explore on how to increase the autonomy level of the robot dog in order to reduce the workload of the operator, and eventually help the operator remain domain expert. Therefore, we will explore the ability of the robot to autonomously 3D-map unknown confined areas. The results of this project will lead to new practical knowledge and a follow-up project that will focus on further developing the technologies that increase the autonomy of the robot for eventual deployment in operational environments. This project will also have direct contribution to education through involvement of students and lecturers.
