Sipke Hoekstra

Development options for the Dutch gas distribution grid in a changing gas market

The Dutch gas distribution grid faces several changes in the near future. Among others, the share of green gas will grow, the interaction with the electricity distribution grid and local heat grids will increase, and the grid will transform from a mono-gas system to a multi-gas system. The gas distribution grid is likely to be expanded with novel components, e.g. blending stations, gas storage sites, and gas compressor stations. Furthermore, these changes require the currently passive gas distribution grid to become a smart gas grid that monitors and controls the gas pressure, gas flow, and gas quality. Therefore, the distribution service operators need to make investments in the gas distribution grid. When looking at for example the introduction of green gas, a decision tree on the optimal green gas supply configuration can be identified. Decisions in this respect consider, among others, the location of several process steps (perform the process step locally at a small scale or centrally at a larger scale) and the addition of components like a gas storage site or a compressor station. Due to the multitude of development options for the gas distribution grid and the fact that the best solution is largely dependent on the local situation and performance criteria (e.g. CO2 emission minimization or cost minimization), a tool is required that can generate situation specific solutions. Each solution generated by the tool should have its own advantages and disadvantages. Generating multiple options and showing the advantage and disadvantage of them provides the distribution service operators insight in the available options and eases the decision making on investments of the gas distribution grid.

Evaluating a computational support tool for set-based configuration of production systems: Results from an industrial case

This paper describes research conducted in the context of an industrial case dealing with the design of re configurable cellular manufacturing systems. Reconfiguring such systems represents a complex task due to the interdependences between the constituent subsystems. A novel computational tool was developed to support the production engineers in (sub) system configuration by enabling to consider multiple alternative configurations simultaneously. The tool was tested by applying it in two realistic system engineering problems and conducting interviews to evaluate its effects. The prototype was found to be an effective and efficient approach to support exploring evaluating and selecting sets of system configurations. The findings suggest that the approach is applicable in practice and represents a means to strategically leverage the flexibility in production system design as well as to improve the efficiency of the engineering process. Hence further research could examine if the approach is useful in additional systems engineering domains.

Exploiting Life Cycle Innovation

Life cycle innovation is achieved by continuous technology insertion in each stage of the life cycle. For capital assets, opportunities for innovation are produced through integration, collaboration and long term partnerships. Such opportunities arise in the acquisition phase, and the client must balance product, process and supply chain decisions. To understand what is missing in the innovation chain, we present a novel life cycle model relating products and capital assets. We then provide a framework that exposes links between the asset and maintenance architectures. We believe both to be fundamental contributions for reducing uncertainty, helping collaboration in complex projects.