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Search Publications by: Peter O. Denno (Fed)

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Displaying 1 - 25 of 85

A Human-centered Framework to Update Digital Twins

July 13, 2023
Author(s)
Peter O. Denno, Deogratias Kibira
Developing a digital twin (DT) involves establishing (1) a predictive capability (a model) relevant to the application, (2) means to collect data from the physical counterpart, and (3) means to apply the collected data to the model. Ideally, with these

Architecture Definition in Complex System Design Using Model Theory

October 4, 2022
Author(s)
Charles Dickerson, Michael Wilkenson, Eugenie Hunsicker, Siyuan Ji, Mole Li, Yves Bernard, Graham Bleakley, Peter O. Denno
Architecture Definition, which is central to system design, is one of the two most used technical processes in the practice of model-based systems engineering. In this paper a fundamental approach to architecture definition is presented and demonstrated

Towards Operational Use of Unit Manufacturing Process Models

July 25, 2019
Author(s)
Amogh Kulkarni, William Z. Bernstein, David Lechevalier, Daniel Balasubramanian, Gabor Karsai, Peter O. Denno
Unit Manufacturing Processes (UMP) are models that capture succinct definitions of individual manufacturing steps in a manufacturing system. They are used to facilitate model composition and reuse. However, mainly due to their textual nature, they are

Standards-based integration of advanced process control and optimization

October 28, 2018
Author(s)
Guodong Shao, Hasan Latif, Carla Martin, Peter O. Denno
Integration of process control with optimization is critical to Smart Manufacturing (SM). Oftentimes, however, the process control solutions from one vendor do not interoperate with the optimization solutions of another. Incompatibilities among the

Dynamic Production System Identification for Smart Manufacturing Systems

June 12, 2018
Author(s)
Peter O. Denno
Knowledge of process requirements, system capacities, and system reliability are the premises on which control policies are formulated. In dynamic manufacturing environments, engineering change to the product, the process, and the production equipment can

An Analytical Framework for Smart Manufacturing

March 25, 2018
Author(s)
Peter O. Denno, Amogh Kulkarni, Daniel Balasubramanian, Gabor Karsai
Smart manufacturing is an emerging paradigm for the next generation of manufacturing systems. One key to the success of smart manufacturing is the ability to use the production data for defining predictive and descriptive models and their analyses. However

A DOMAIN DRIVEN APPROACH TO METAMODELING IN ADDITIVE MANUFACTURING

September 6, 2017
Author(s)
Peter O. Denno, Yan Lu, Paul Witherell, Sundar Krishnamurty, Ian Grosse, Douglas Eddy
Recent studies have shown advantages to utilizing metamodeling techniques to mimic, analyze, and optimize system input-output relationships in Additive Manufacturing (AM). This paper addresses a key challenge in applying such metamodeling methods, namely

Production System Identification with Genetic Programming

September 6, 2017
Author(s)
Peter O. Denno, Charles Dickerson, Jenny Harding
Modern system identification methodologies use artificial neural nets, integer linear programming, genetic algorithms, and swarm intelligence to discover system models. Paring genetic programming, a variation of genetic algorithms, with Petri nets seems to

INVESTIGATING GREY-BOX MODELING FOR PREDICTIVE ANALYTICS IN SMART MANUFACTURING

August 8, 2017
Author(s)
Peter O. Denno, Yan Lu, Paul Witherell, Sundar Krishnamurty, Ian Grosse, Douglas Eddy
This paper develops a grey-box modeling approach that combines manufacturing knowledge-based (white-box) models with statistical (black-box) metamodels to improve model reusability and predictability. A white-box model can utilize different types of

Smart Production Systems: Architecture and Application to multi-job manufacturing

June 28, 2017
Author(s)
Pooya Alavian, Peter O. Denno, Semyon Meerkov
Smart Production Systems (SPS) are manufacturing systems capable of self-diagnosing and providing the operation management with an advice concerning performance improvements, along with rigorously quantified outcomes of their potential deployment. This

Networked Engineering Notebooks for Smart Manufacturing

September 8, 2016
Author(s)
Peter O. Denno
A goal of the industrial internet is to make information about manufacturing processes and resources available wherever decision making may be required. Agile use of information is a cornerstone of data analytics, but analytical methods more generally

Investigating predictive metamodeling for additive manufacturing

August 21, 2016
Author(s)
Zhuo Yang, Douglas Eddy, Sundar Krishnamurty, Ian Grosse, Peter O. Denno, Felipe F. Lopez
Additive manufacturing processes offer significant commercial advantages due to unique and advanced process capabilities. Production of metal parts can involve trial and error. This is often due to limited understanding of variability in properties and the

Implementing the ISO 15746 Standard for Chemical Process Optimization

July 3, 2016
Author(s)
Guodong Shao, Peter O. Denno, Albert T. Jones, Yan Lu
Integrating advanced process control solutions with optimization (APC-O) solutions, within any factory, enables more efficient production processes. Currently, vendors who provide the software applications that implement control solutions are isolated and

A domain-specific language for model composition and verification of multidisciplinary models

March 22, 2016
Author(s)
Peter O. Denno, Anantha Narayanan Narayanan, Amogh Kulkarni, Daniel Balasubramanian, Gabor Karsai
Complex, engineered products and manufacturing processes often necessitate integrated analysis that cuts across physical domains and engineering disciplines. When the domain-specific models that contribute to the overall analysis process are available then

A domain-specific language for model composition and verification of multidisciplinary models

March 21, 2016
Author(s)
Peter O. Denno, Anantha Narayanan Narayanan, Amogh Kulkarni, Daniel Balasubramanian, Gabor Karsai
Complex, engineered products and manufacturing processes often necessitate integrated analysis that cuts across physical domains and engineering disciplines. When the domain-specific models that contribute to the overall analysis process are available then