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.

Supply chain networks are formed out of complex interactions amongst several companies whose aim is to produce and deliver goods to the customers at the time and place specified by them. Computing the total lead time for customer orders entering such a complex network of companies is an important exercise. In this paper, we present analytical models for evaluating the average lead times of make-to-order supply chains. In particular, we illustrate the use of fork-join queueing networks to compute the mean and variance of the lead time. The existing literature on approximate methods of analysis of fork-join queueing systems assume heavy traffic and require tedious computations. We present two applications of a tractable approximate analytical method for lead time computations in a class of fork-join queueing systems. For the case where the arrivals are deterministic and service times are normally distributed, we present an easy to use approximate method. Specifically, we illustrate the use of the above method in setting service levels in assemble-to-order type supply chains.