Simulation as a cloud service for short-run high throughput industrial print production using a service broker architecture

Abstract

Evaluating end-to-end systems is uniquely challenging in industrial/commercial printing due to a large number of equipment combinations and customization needed for each customer and application. Moreover any mismatch in capacities may render multi-million dollar investments to zero returns on investment. Simulation can help foresee changes on the shop floor when demand changes. Providing a library of components that can be assembled together is the usual approach used by many simulation vendors which still leaves a simulation engineer in the loop to make it usable. We detail our experiences on implementing a prototype (private) cloud service using service broker architecture and a dynamic model generator. The service broker handles the heterogeneity associated with demand and equipment configurations whereas the dynamic model generator customizes a generic model based on inputs from the user. This helps avoiding rewiring of simulation models on each engagement. The schema and the necessary front and back-end codes all reside in the cloud and, therefore, users pay on a per use basis without worrying about the upgrade/update of software at their end. The service supports multi-tenancy which results in low costs per user and provides sharing of resource information yet restricting access to proprietary workflows and policies. A typical run costs a very small amount, which is affordable for even small-sized PSPs. We show the utility of our work in the context of educational book publishing to evaluate equipment changes needed when the current lumpy order demand stream changes to a highly fragmented demand stream. We also discuss how our work can be extended to several other domains such healthcare, transportation, 3D printing.