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The LIINES is happy to announce that our recent paper entitled: “Symmetrica: Test Case for Tansportation Electrification Research” has been published in the journal Infrastructure Complexity. Written by Prof. Amro M. Farid, this paper presents a test case for electric vehicle integration studies.
Electrified transportation has emerged in recent years as a means to reduce CO2 emissions and support energy efficiency. For this trend to succeed in the long term, electric vehicles must be integrated into the infrastructure systems that support them. Electric vehicles couple two such large systems; the transportation system and the electric power system into a nexus.
Electric vehicle integration, much like solar PV and wind integration years ago, has been fairly confined to small fleets of tens of vehicles. Such small pilot projects do not present a significant technical challenge. Their large scale adoption, however, must be carefully studied to avoid degrading overall infrastructure performance. Transportation electrification test cases serve to study infrastructure behavior well before reaching a full deployment of electric vehicles. Such a test case would resemble those often used in power systems engineering to serve methodological development in the design, planning, and operation of such systems.
The arguments for a test case to study the transportation electricity nexus are five-fold. First, a standardized test case is required to test, and compare analytical methods. In power systems, test cases served an essential role in the maturation of power flow analysis, stability studies, and contingency analysis. The transportation-electricity nexus will ultimately also require similar assessments. Secondly, using real data from critical infrastructure may be imprudent. For example, real data may reveal weak points in a power system which may be exploited by unauthorized personnel. Thirdly, a test case serves to support fundamental understanding by broadening intuition development. For the transportation-electricity nexus, understanding the effect of increasingly interdependent dynamics, will result in new requirements for optimization and control for its planning and operation. Naturally, this new found intuition serves the fourth reason of methodological development. A test case serves facilitates the design, planning, and operation of the system before it is built. Unexpected behaviors may be identified in an early stage and can subsequently be avoided or mitigated. Finally, the privacy of personal data is protected through using a test case. Transportation simulation requires microscopic data (tracking each vehicle through a full day’s events), which raises grave privacy and ethical concerns if real data is used.
To address these needs, the proposed test case includes three structural descriptions: a transportation system topology, an electric power topology, and a charging system topology. Additional data includes transportation demand and charging demand. The test case consists of a number of desirable characteristics, including completeness, functional heterogeneity, moderate size, regular topology, regular demand data, realism, and objectivity. The figure below shows the three topologies; a fully detailed description test casenamed ‘Symmetrica’ is available in the paper.
The transportation electrification test case can potentially be used for research within planning and operation management applications. A recent study (Al Junaibi et al. 2013) showed that the planning of the charging system as the couple of two infrastructure systems highly impacts the overall performance of the transportation electrification nexus. Matching the spatial layout of charging infrastructure to the demand for electrified transportation is key a infrastructure developent challenge. Furthermore, investment costs to upgrade power lines and transformers must be matched to the expected adoption of electric vehicles, providing an interesting starting point for return-on-investment and operations research methods. Using operation management applications such as charging station queue management or vehicle-2-grid stabilization could optimize the integration of electric vehicles within the nexus. Opportunities such as these present rich applications areas which have the potential to significant reduce the extra expenditure in infrastructure investments.
In depth materials on LIINES electrified transportation systems research can be found on the LIINES websitte.
Journal Paper accepted at IEEE Transactions on Industrial Informatics – An Axiomatic Design of a Multi-Agent Reconfigurable Mechatronic System Architecture
The LIINES is pleased to announce the acceptance of the paper “An Axiomatic Design of a Multi-Agent Reconfigurable Mechatronic System Architecture” to the IEEE Transactions on Industrial Informatics. The paper is authored by Prof. Amro M. Farid and Prof. Luis Ribeiro.
Recent trends in manufacturing require production facilities to produce a wide variety of products with an increasingly shorter product lifecycle. These trends force production facilities to adjust and redesign production lines on a more regular basis.
Reconfigurable manufacturing systems are designed for rapid change in structure; in both hardware and software components to address the required changes in production capacity and functionality.
Qualitative methods have recently been successful in achieving reconfigurability through multi-agent systems (MAS). However, their implementation remains limited, as an unambiguous quantitative reference architecture for reconfigurability has not yet been developed.
A design methodology based on quantitative reconfigurability measurement would facilitate a logical, and seamless transition between the five stages of the MAS design methodology, as shown below.
Previous work on the reconfigurability of automated manufacturing systems has shown that reconfigurability depends primarily on architectural decisions made in stages 1, 2, 3, and 5. Operational performance of the manufacturing system after the reconfiguration is also important, but is often overlooked by the existing literature. As a result, it’s not clear:
- The degree to which existing designs have achieved their intended level of reconfigurability.
- Which systems are quantitatively more reconfigurable.
- How these designs may overcome their inherent design limitations to achieve greater reconfigurability in subsequent design iterations.
In order to address the previously mentioned issues with existing design methodologies, this paper develops a multi-agent system reference architecture for reconfigurable manufacturing systems driven by a quantitative and formal design approach, directly in line with the above Figure.
The paper uses Axiomatic Design for Large Flexible Engineering Systems to support a well-conceptualized architecture, which is necessary for excellent production system performance. Additionally, Axiomatic Design highlights potential design flaws at an early conceptual stage. This results in the first formal and quantitative reference architecture based on rigorous mathematics.
About the Author
Wester C.H. Schoonenberg completed his B.Sc. in Systems Engineering and Policy Analysis Management at Delft University of Technology in 2014. After his bachelors’ degree, Wester started his graduate work for the LIINES at Masdar Institute, which he continues as a doctoral student at Thayer School of Engineering at Dartmouth College in 2015. Currently, Wester is working on the integrated operation of electrical grids and production systems with a special interest in Zero Carbon Emission Manufacturing Systems.
Journal Paper Accepted at Journal of Enterprise Transformation – Axiomatic Design Based Human Resources Management for the Enterprise Transformation of the Abu Dhabi Healthcare Labor Pool
Journal Paper Accepted at the Journal of Intelligent Manufacturing: Measures of reconfigurability and its key characteristics in intelligent manufacturing systems
The LIINES is pleased to announce that the Journal of Intelligent Manufacturing has accepted our paper entitled: “Measures of reconfigurability and its key characteristics in intelligent manufacturing systems”. The paper is authored by Amro M. Farid and was published in October 2014.
Many manufacturing challenges arise with the global trend of increased competition in the marketplace. Production processes must deal with shorter product lifecycles and mass-customization. Consequently, production systems need to be quickly and incrementally adjusted to meet the ever-changing products. Reconfigurable manufacturing systems have been proposed as a solution that facilitates changing production processes for highly automated production facilities.
Much research has been done in the field of reconfigurable manufacturing systems. Topics include: modular machine tools and material handlers, distributed automation, artificially intelligent paradigms, and holonic manufacturing systems. While these technological advances have demonstrated robust operation and been qualitatively successful in achieving reconfigurability, there has been comparatively little attention devoted to quantitative design methodologies of these reconfigurable manufacturing systems and their ultimate industrial adoption remains limited.
Measuring reconfigurability of manufacturing systems quantitatively has been a major challenge in the past, since a quantitative reconfigurability measurement process was non-existent. Earlier work developed a measurement method that extracts measurables from the production shop floor. When this was established, basic measures of reconfiguration potential and reconfiguration ease were developed, based on axiomatic design for large flexible engineering systems and the design structure matrix respectively.
Reconfiguration of a production process can be split up in four steps: Decide which configuration, Decouple, Reorganize, and Recouple. The larger the number of elements in the system, the more configurations are made possible. This is measured using the reconfiguration potential measure, based on axiomatic design for large flexible engineering systems.
Production processes contain multiple interfaces within themselves. Multiple layers of control can be distinguished, that have to work together to coordinate the physical components. These interfaces are the main determinants for the reconfiguration ease measure.
This paper combines these techniques to define a quantitative measure for reconfigurability and its key characteristics of integrability, convertibility and customization. The intention behind this research contribution is that it may be integrated in the future into quantitative design methodologies for reconfigurable manufacturing systems, which may be easily adopted by industrial automation and production companies.
About the author: Wester Schoonenberg completed his B.Sc. in Systems Engineering and Policy Analysis Management at Delft University of Technology in 2014. After his bachelors’ degree, Wester started his M.Sc. at Masdar Institute of Science & Technology. Currently, Wester is working on the integrated operation of electrical grids and production systems with a special interest in the demand side management of industrial facilities.
LIINES Website: http://amfarid.scripts.mit.edu