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Digital transformation of commercial print production brings new opportunities including exploitation of embedded sensing and computing power that enable real-time communication during various phases of the production chain, and dynamic reconfiguration of production flow. Simulation based modeling can help to exploit these opportunities at both strategic(More)
Before ICC profiles, a device-independent page description document would encode all color in a device independent CIE space like CIELAB. When the document was to be printed, the press person would measure a target and create a color transformation from the CIE coordinates to device coordinates. For office and consumer color printers, the color(More)
On-demand digital printing is an example of emerging personalized manufacturing services. It provides unique opportunities to automate the printing process, enhance productivity, and better utilize resources such as equipment, servers and IT infrastructure. In this work, we present a unified solution approach to solve an important optimization problem in(More)
We present a high-performance and real-time production scheduling algorithm for digital print production based on a dynamic incremental evolutionary algorithm. The optimization objective is to prioritize the dispatching sequence of orders and balance resource utilization. The scheduler is scalable for realistic problem instances and it provides solutions(More)
An enterprise service-level performance time series is a sequence of data points that quantify demand, throughput, average order-delivery time, quality of service, or end-to-end cost. Analytical and predictive models of such time series can be embedded into an enterprise information system (EIS) in order to provide meaningful insights into potential(More)
On-demand digital print service is an example of a real-time embedded enterprise system. It offers mass customization and exemplifies personalized manufacturing services. Once a print order is submitted to the print factory by a client, the print service provider (PSP) needs to make a real-time decision on whether to accept or refuse this order. Based on(More)
Accurate predictions of both process-execution time and process status are crucial for the development of an intelligent enterprise information system (EIS). We have developed new automated learning-based process-execution time-prediction and process status-prediction methods that can be embedded into an EIS. Process-execution time prediction is a(More)
— On-demand digital-print service offers mass cus-tomization and exemplifies personalized manufacturing services. We describe a real-time and online optimization technique based on genetic algorithms (GA) for print factory workflow optimization. We have simulated digital-print factory manufacturing activities as a heterogeneous, concurrent and integrated(More)