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dc.contributor.authorDanishvar, M-
dc.contributor.authorMousavi, A-
dc.contributor.authorDanishvar, S-
dc.identifierORCID iD: Morad Danishvar
dc.identifierORCID iD: Alireza Mousavi
dc.identifierORCID iD: Sebelan Danishvar
dc.identifier.citationDanishvar, M., Mousavi, A. and Danishvar, S. (2022) 'The Genomics of Industrial Process through the Qualia of Markovian Behaviour', IEEE Transactions on Systems Man and Cybernetics: Systems, 52 (11), pp. 7173 - 7184. doi: 10.1109/TSMC.2022.3150398.en_US
dc.description.abstract© Copyright 2022 The Authors. A technique for registering and relating events that cause an observable and definable system state is proposed. Discrete events of system-state transfer are expressed by event tracking and clustering in the form of contiguous quanta of data. This approach is capable of describing typical processes in industrial systems in a chain of codes that contain system input/output parameters. The constituent nodes of the Markovian Processes chain form a series akin to genes in the deoxyribonucleic acid, repeatable and predictable. The process genes are the quanta of information that aligns to represent a chain of activities (process). They describe the causal links between occurring events forming a pattern (pathway) that leads to a well-specified output (e.g., a product with a defect or otherwise). The creation of process genomics requires the knowledge of system observed or latent parameters (state) as well as the state change at specified time intervals (discretization). The process genomics theory is tested in an industrial case study for quality assessment and control of glue dispensing in micro-semiconductor manufacturing. The resulting definitions of the system state and interrelationship of control parameters contribute to the development of the process genes. The outcome of the gene alignment is the geometric interpretation of the glue droplet formation. A predicted or observed droplet within the production tolerance leads to a nondefective product. The principle of creating production genomics is to find and rectify the defect-causing genes or to disrupt the sequences that lead to producing defective products, leading to a zero-defect manufacturing process.-
dc.description.sponsorshipEuropean Union’s Horizon 2020 Research and Innovation Program (Grant Number: 723906) - Zero-defect manufacturing strategies towards on-line production management for European factories.-
dc.format.extent7173 - 7184-
dc.rights© Copyright 2022 The Authors. Published by IEEE. This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see
dc.subjectMarkovian processen_US
dc.subjectmachine learningen_US
dc.subjectdispensing technologyen_US
dc.titleThe Genomics of Industrial Process Through the Qualia of Markovian Behavioren_US
dc.title.alternativeThe Genomics of Industrial Process through the Qualia of Markovian Behaviour-
dc.relation.isPartOfIEEE Transactions on Systems Man and Cybernetics: Systems-
dc.rights.holderThe Authors-
Appears in Collections:Dept of Mechanical and Aerospace Engineering Research Papers

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