It is a well-known fact that collaborative supply chain management and planning reduces overall costs. Nevertheless it is not being exploited due the fact that partners are reluctant to share the necessary, but sensitive data. This is due to inherent risks associated with exposing this private data. This project proposes to use secure computation to overcome this data sharing problem in supply chain management and enable the secure collaboration and interoperation of supply chain partners to gain the advantages of knowledge-based collaborative supply chain planning, forecasting, benchmarking and management. We are extending existing techniques to more elaborate theoretical settings: first for the use case of an airplane manufacturing organization where several mutually distrustful SMEs need to collaborate in a partially integrated supply chain and second inter-enterprise where all companies in the supply chain are interoperating. We start by defining the requirements and necessary computations for each of the two use cases. We then extend the theoretical results to cover the cases of these computations if they do not exist already. Such a result is a protocol enabling this computation as part of a tool for generating the new knowledge of the computation result and managing the existing knowledge of the collaborating partners, such that it remains private. Based on the theoretical foundation we want to develop prototypes to evaluate the practical performance of the protocols. In parallel to the technical implementation track, the business track needs to identify the obstacles for the technology to be exploited. We need to identify the criteria for user acceptance of the technology and a benefit distribution model needs to be developed, such that all partners in the supply chain share the profit in a fair manner. The results of the business and technical track are combined when it comes to building the demonstration of the results.