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Parallel and distributed computing infrastructures are increasingly being embraced in the context of manufacturing applications, including real-time scheduling. We present the design and implementation of one such framework that can work on the Internet, with applications in manufacturing. The architecture, DPAC (distributed and parallel computing framework), has the goal of harnessing the Internet's vast, growing computational capacity for ultra-large, coarse-grained parallel applications. The idea is to bring together diverse, heterogeneous, geographically distributed computing environments in order to attack large-scale computing problems. We present a scalable and fault-tolerant architecture in DPAC and the results of running performance experiments. DPAC is implemented on the interoperable, increasingly secure, and ubiquitous platform Java. The unique feature of DPAC is that it frees application developers from concerns about complex interprocess communication and fault tolerance among Internet-worked hosts and supports piecework and branch-and-bound computational models. We describe an implementation and present case studies showing the effectiveness in solving complex combinatorial optimization problems in the context of manufacturing systems.