Configuration Space Exploration for Digital Printing Systems

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Abstract

Within the printing industry, much of the variety in printed applications comes from the variety in finishing. Finishing comprises the processing of sheets of paper after being printed, e.g. to form books. The configuration space of finishers, i.e. all possible configurations given the available features and hardware capabilities, are large. Current control software minimally assists operators in finding useful configurations. Using a classical modelling and integration approach to support a variety of configuration spaces is suboptimal with respect to operatability, development time, and maintenance burden. In this paper, we explore the use of a modeling language for finishers to realize optimizing decision making over configuration parameters in a systematic way and to reduce development time by generating control software from models. We present CSX, a domain-specific language for high-level declarative specification of finishers that supports specification of the configuration parameters and the automated exploration of the configuration space of finishers. The language serves as an interface to constraint solving, i.e., we use low-level SMT constraint solving to find configurations for high-level specifications. We present a denotational semantics that expresses a translation of CSX specifications to SMT constraints. We describe the implementation of the CSX compiler and the CSX programming environment (IDE), which supports well-formedness checking, inhabitance checking, and interactive configuration space exploration. We evaluate CSX by modelling two realistic finishers. Benchmarks show that CSX has practical performance (<1s) for several scenarios of configuration space exploration.

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APA

Denkers, J., Brunner, M., van Gool, L., & Visser, E. (2021). Configuration Space Exploration for Digital Printing Systems. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 13085 LNCS, pp. 423–442). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-92124-8_24

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