Integrated Natural Resource Conservation and Development (INRCD) Projects are efforts at worldwide locations to promote economic development of local communities consistent with conservation of natural resources. This umbrella term includes Integration Conservation and Development Projects (ICDPs) introduced by the World Wide Fund to combine social development and conservation s through the use of socio-economic investments, and the Integrated Natural Resource Management (INRM) research and development efforts that have employed a systems approach for quantitative modeling and optimization. In the spirit of the INRCD framework, we describe the development of a system-level agriculture and energy model comprising engineering and economic models for crop, irrigation, and energy subsystem designs for a community in Central Uganda. The model architecture is modular allowing modifications for different system configurations and project locations. We include some initial results and discuss next steps for system optimization, refining model assumptions, and modeling community social benefits as drivers of such projects.

Combinatorial Design such as configuration design, design optioneering, component selection, and generative design, is common across engineering. Generating solutions for a combinatorial design task often involves the application of classical computing solvers that can either map or navigate design spaces. However, it has been observed that classical computing resource power-law scales with many design space models. This observation suggests classical computing may not be capable of modelling our future design space needs.

To meet future design space modelling needs, this paper examines quantum computing and the characteristics that enables its resources to scale polynomially with design space size. The paper then continues to present a combinatorial design problem that is subsequently represented, constrained and solved by quantum computing. The results of which are the derivation of an initial set of circuits that represent design space constraints. The study shows the game-changing possibilities of quantum computing as an engineering design tool and is the start of an exciting new journey for design research.

The increased demand for customer-adapted product solutions shows an increasing trend of product variety, leading to an increased internal variety and therefore -costs. The concept of modularization provides apossible solution to this challenge by developing modular kits. Nevertheless, modularization methods to not lead to one individual modular kit, but to several alternatives. The decision of which alternative to implement can be crucial to the applying companys succes. During this decision-making both customer- and company perspectives need to be taken into account. This contribution is to present a simulation-based approach to support the decision making by using a model-based configuration system. Furthermore, as classical decision-making processes are based upon historical data, future aspects are usually not taken into account. In order to counteract this situation, this contribution intends to simulate as well future aspects impacting the modular product architecture. In this case, the simulation is used in order to evaluate the individual performances of a Design-for-Variety product architecture as opposed to a Design-for-Future-Robustness by applying this method to the example of customer-individual laser machines.

With an increasing demand for product individualisation leading to increased product architecture complexity and -costs, modular kits are one common measure to cope with this issue. The management of such a modular kit as well as the methodical determination of a specific product variant is key to the manufacturer's success. As multiple influence factors need to be taken into account when configuring product variants, we propose a multi-dimensional geometric optimisation algorithm, allowing for prioritising varying customer demands and thereby determining the ideally balanced product variant.

The challenges related to product structures, which go hand in hand with megatrends such as individualization, can be met with the modularity of product structures. With the help of various modularization methods, modular product structures are created with regard to different goals. There are many references to the effects of modular product structures on life phases and economic targets in the literature. These effects were collected in previous research in a generic impact model. Since there is a lot of information about the effects, such models become very comprehensive and thereby difficult to handle. For this reason, the impact model is consistently generated using SysML. The adaptation to company scenarios is possible through the use of simulations with which, for example, company-related and product-related boundary conditions can be controlled by means of a User Interface.