Manufacturing operations frequently face inventory imbalances caused by demand fluctuations, rescheduling, or changes in engineering requirements, issues that are particularly pronounced in the electronics industry. This sector exhibits fast product life cycles and high variability, which cause excess stock to depreciate rapidly in value. Manufacturing as a Service (MaaS) is emerging as a distributed production paradigm in which manufacturing resources are shared through networked providers~\cite{EU_MaSS}. While MaaS is mainly applied in the context of providing flexible, scalable, and on-demand access to manufacturing capabilities across distributed providers, its underlying principles can also be extended to material sharing and excess-inventory exchange. Within such ecosystems, companies are no longer limited to their internal inventories. Instead, they can request, offer, or exchange excess stock across the network, thereby reducing the risks of shortages, improving material availability, and limiting waste. In this work, we investigate an optimization-based decision-support model as a first step toward coordinated supply-demand matching, enabling independent companies to redeploy excess or non-critical inventories and expiring materials to partners facing shortages.