Virtual Machines in a Chemical Analytical Laboratory

Research output: ThesisDoctoral Thesis

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Abstract

Chemical analytical laboratory equipment is prevalent in a number of industries such as chemical manufacturing plants, oil and gas refining, Research and Development, and many others. Challenges specific to these laboratories include aged and often unsupported operating systems and hardware, a lack of parts for aging PCs, and vendor warnings stating that any updates to the operating system or the installation of antivirus software, may render the laboratory software inoperable.

This research validates the use of selected media converters in either point to point (serial to USB) or multipoint (serial to IP) configurations which can be successfully implemented without data modification by media converters to ensure that correct data and the ability to safely control equipment can be accomplished. Using tested configurations of selected media converters along with mixes of operating systems and virtual machines, combinations are identified for prospective use in chemical laboratories as well as other industrial applications. Finally, flow diagrams are provided to assist in determining whether utilizing virtual machines in the stated environment is achievable or appropriate.

This research is based upon two phases of testing to identify whether the use of laboratory equipment with either USB connections or serial ports (DE-9) can utilize combinations of media converters, thin clients, thick clients, and virtual machines to replace aging and often unsupported PCs. The results of this research identified both successful and unsuccessful tested environments which can assist in addressing said challenges. In addition, a high level set of flow diagrams were created that can be used as a tool to assist in determining whether utilizing virtual machines in the stated environment is feasible or even desirable.
Original languageEnglish
QualificationDoctor of Information Technology
Awarding Institution
  • Charles Sturt University
Supervisors/Advisors
  • Zia, Tanveer, Advisor
Award date31 Jul 2017
Publisher
Publication statusPublished - 2017

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