Abstract

Laboratory environments are controlled more and more by automated systems. Written procedures and lab journals are replaced by workflow description languages and electronic notebooks, which not only describe the processes but are used also for the control of the entire workbench, data acquisition, and documentation. Dynamic scheduling is needed in such an environment. Multiple samples with different procedures are processed in parallel, competing for the instruments. The whole environment may be also underlaid by optimization strategies like throughput or minimum sample processing time. The modeling of all components interacting on the workbench—samples, devices, sensors, results, database systems, and so on—needs to rely on concepts building a consistent framework. This article gives a set of terms and definitions used in a dynamic scheduling environment. It describes most of these entities in detail, including their functionality and attributes as well as their logical and physical interactions. It also describes concepts such as workflows with activities and constraints, functional libraries, hidden transport, and dynamic execution. Maintenance, calibration, and error management also are included. Finally, it discusses how the entities interact with the different components in the scheduling system.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.