Show simple item record

dc.rights.licenseRestricted to current Rensselaer faculty, staff and students in accordance with the Rensselaer Standard license. Access inquiries may be directed to the Rensselaer Libraries.
dc.rights.license
dc.contributorHahn, Juergen
dc.contributorKopsaftopoulos, Fotis
dc.contributorPlawsky, Joel L., 1957-
dc.contributor.advisorBequette, B. Wayne
dc.contributor.authorGhosh, Sambit
dc.date.accessioned2022-05-25T13:07:02Z
dc.date.issued2021-08
dc.identifier.urihttps://hdl.handle.net/20.500.13015/5003
dc.descriptionAugust 2021
dc.descriptionSchool of Engineering
dc.description.abstractIndustry 4.0 and Smart manufacturing paradigms aim to make manufacturing processes flexible, enabling the human-in-the-loop to make better decisions and develop the workforce. The dissertation presents the concept of a Smart Control Room (SCR) that is envisioned to play a key role in manufacturing plants and organizations. Three major aspects of the SCR are presented in detail. A key role of the SCR is to use high-fidelity plantwide models to assist operators in better decision making and forecasting. The development of a rigorous plantwide flowsheet of the Vinyl Acetate Monomer process in Aspen Dynamics and MATLAB is presented. Key improvements of the MATLAB nonlinear model, specifically for the distillation column are discussed. A simulated study of the distillation column startup is also presented. Operator training for various levels of expertise during complicated plant operations is an area where automation algorithms can play a key role. To explore this, the development of a Human-in-The-Loop Supervisory Model Predictive Control (HiTL MPC) algorithm is presented. Using a single-input single output example, it is shown that the algorithm is able to accept human suggested inputs and based on degrees of cooperation, the final control output is computed. The successful performance of the algorithm with a multi-input multi-output example using the VAM upstream flowsheet is also demonstrated, with switching of manual and automatic input pairs occurring during the process. The data arising out of a process plant is hierarchical and networked in nature. To understand this, a novel graph theoretic and Graph Signal Processing based approach is discussed in detail. The filtering and predictive performance of the tool is also presented with the use of industrial data of a cryogenic air separation unit.
dc.languageENG
dc.language.isoen_US
dc.publisherRensselaer Polytechnic Institute, Troy, NY
dc.relation.ispartofRensselaer Theses and Dissertations Online Collection
dc.subjectChemical engineering
dc.titleHuman-in-the-loop and graph theoretic aspects of a smart control room
dc.typeThesis
dc.typeElectronic thesis
dc.rights.holderThis electronic version is a licensed copy owned by Rensselaer Polytechnic Institute (RPI), Troy, NY. Copyright of original work retained by author.
dc.description.degreePhD
dc.relation.departmentDept. of Chemical and Biological Engineering


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record