The Experts below are selected from a list of 36366 Experts worldwide ranked by ideXlab platform
Dirk Schaefer - One of the best experts on this subject based on the ideXlab platform.
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combining mathematical programming and sysml for Automated Component sizing of hydraulic systems
Journal of Computing and Information Science in Engineering, 2010Co-Authors: Aditya A Shah, Christiaan J J Paredis, Roger Burkhart, Dirk SchaeferAbstract:In this paper, we present a framework for Automated Component sizing to extend a designer's ability to evaluate a particular configuration during the architecture exploration phase of a design process. Component sizing is a hard problem to solve, both from a computational and modeling aspect. This is because of competing objectives, requirements from multiple disciplines, and the need to find a good solution quickly for the architecture being considered. In current approaches, designers rely on heuristics and iterate over the multiple objectives and requirements until a satisfactory solution is found. To improve on this state of practice, we introduce advances in the following two areas: (a) solving the problem efficiently so that all of the imposed requirements are satisfied simultaneously and the solution obtained is mathematically optimal and (b) modeling a Component sizing problem in a manner that is convenient to designers. An acausal, algebraic, equation-based, declarative modeling approach using mathematical programming (GAMS) is taken to solve these problems more efficiently. The object management group systems modeling language (OMG SysML™) is used to model Component sizing problems in order to facilitate problem formulation, model reuse and automatic generation of low-level code that can be solved using GAMS and its solvers. This framework is demonstrated by applying it to an example of a hydraulic log splitter. Based on this initial example, we discuss two advantages of this framework—total time taken in solving multiple scenarios for a given configuration and the graphical representation of a problem in SysML.
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combining mathematical programming and sysml for Automated Component sizing of hydraulic systems
ASME 2010 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, 2010Co-Authors: Aditya A Shah, Christiaan J J Paredis, Roger Burkhart, Dirk SchaeferAbstract:In this paper, we present a framework that improves a designer’s capability to determine near-optimal sizes of Components for a given system architecture. Component sizing is a hard problem to solve because of competing objectives, requirements from multiple disciplines, and the need for finding a solution quickly for the architecture being considered. In current approaches, designers rely on heuristics and iterate over the multiple objectives and requirements until a satisfactory solution is found. To improve on this state of practice, we introduce advances in the following two areas: a) Formulating a Component sizing problem in a manner that is convenient to designers and b) Solving the problem efficiently so that all of the imposed requirements are satisfied simultaneously and the solution obtained is mathematically optimal. An acausal, algebraic, equation-based, declarative modeling approach using mathematical programming (GAMS) is taken to solve these problems more efficiently. In addition the Systems Modeling Language (OMG SysML™) is used to formulate Component sizing problems to facilitate problem formulation, model reuse and the automatic generation of low-level code that can be solved using GAMS and its solvers (BARON). This framework is demonstrated by applying it to an example of a hydraulic log splitter.Copyright © 2010 by ASME
Christian Bartelt - One of the best experts on this subject based on the ideXlab platform.
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knowledge driven architecture composition case based formalization of integration knowledge to enable Automated Component coupling
IEEE International Conference on Software Architecture Workshops, 2017Co-Authors: Fabian Burzlaff, Christian BarteltAbstract:Using languages with formalized semantics for automating Component integration is a well-established research area. As a consequence, independently developed software systems can interact without the need for manual integration effort in a "plug-and-play" manner. However, such dynamic adaptive system architectures are not widely used in Industrial IoT scenarios. Practitioners mostly rely on informal, domain-specific standards as formal interface specifications tend to become highly complex quickly. Nonetheless, this results in high manual integration efforts as integration knowledge cannot be reused. Thus, interface specification should be tailored towards its case-based requirements. Interface specifications should only be created and persisted evolutionary after specific integration tasks with knowledge management techniques. The resulting knowledge-driven architecture composition enables integration knowledge reusability and can ultimately automate Component integration.
Burzlaff Fabian - One of the best experts on this subject based on the ideXlab platform.
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Knowledge-driven architecture composition
2021Co-Authors: Burzlaff FabianAbstract:Service interoperability for embedded devices is a mandatory feature for dynamically changing Internet-of-Things and Industry 4.0 software platforms. Service interoperability is achieved on a technical, syntactic, and semantic level. If service interoperability is achieved on all layers, plug and play functionality known from USB storage sticks or printer drivers becomes feasible. As a result, micro batch size production, individualized automation solution, or job order production become affordable. However, interoperability at the semantic layer is still a problem for the maturing class of IoT systems. Current solutions to achieve semantic integration of IoT devices’ heterogeneous services include standards, machine-understandable service descriptions, and the implementation of software adapters. Standardization bodies such as the VDMA tackle the problem by providing a reference software architecture and an information meta model for building up domain standards. For instance, the universal machine technology interface (UMATI) facilitates the data exchange between machines, Components, installations, and their integration into a customerand user-specific IT ecosystem for mechanical engineering and plant construction worldwide. Automated Component integration approaches fill the gap of software interfaces that are not relying on a global standard. These approaches translate required into provided software interfaces based on the needed architectural styles (e.g., client-server, layered, publish-subscribe, or cloud-based) using additional Component descriptions. Interoperability at the semantic layer is achieved by relying on a shared domain vocabulary (e.g., an ontology) and service description (e.g., SAWSDL) used by all devices involved. If these service descriptions are available and machine-understandable knowledge of how to integrate software Components on the functional and behavioral level is available, plug and play scenarios are feasible. Both standards and formal service descriptions cannot be applied effectively to IoT systems as they rely on the assumption that the semantic domain is completely known when they are noted down. This assumption is hard to believe as an increasing number of decentralized developed and connected IoT devices will exist (i.e., 30.73 billion in 2020 and 75.44 billion in 2025). If standards are applied in IoT systems, they must be updated continuously, so they contain the most recent domain knowledge agreed upon centrally and ahead of application. Although formal descriptions of concrete integration contexts can happen in a decentralized manner, they still rely on the assumption that the knowledge once noted down is complete. Hence, if an interoperable service from a new device is available that has not been considered in the initial integration context, the formal descriptions must be updated continuously. Both the formalization effort and keeping standards up to date result in too much additional engineering effort. Consequently, practitioners rely on implementing software adapters manually. However, this dull solution hardly scales with the increasing number of IoT devices. In this work, we introduce a novel engineering method that explicitly allows for an incomplete semantic domain description without losing the ability for Automated IoT system integration. Dropping the completeness claim requires the management of incomplete integration knowledge. By sharing integration knowledge centrally, we assist the system integrator in automating software adapter generation. In addition to existing approaches, we enable semantic integration for services by making integration knowledge reusable. We empirically show with students that integration effort can be lowered in a home automation context
Aditya A Shah - One of the best experts on this subject based on the ideXlab platform.
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combining mathematical programming and sysml for Automated Component sizing of hydraulic systems
Journal of Computing and Information Science in Engineering, 2010Co-Authors: Aditya A Shah, Christiaan J J Paredis, Roger Burkhart, Dirk SchaeferAbstract:In this paper, we present a framework for Automated Component sizing to extend a designer's ability to evaluate a particular configuration during the architecture exploration phase of a design process. Component sizing is a hard problem to solve, both from a computational and modeling aspect. This is because of competing objectives, requirements from multiple disciplines, and the need to find a good solution quickly for the architecture being considered. In current approaches, designers rely on heuristics and iterate over the multiple objectives and requirements until a satisfactory solution is found. To improve on this state of practice, we introduce advances in the following two areas: (a) solving the problem efficiently so that all of the imposed requirements are satisfied simultaneously and the solution obtained is mathematically optimal and (b) modeling a Component sizing problem in a manner that is convenient to designers. An acausal, algebraic, equation-based, declarative modeling approach using mathematical programming (GAMS) is taken to solve these problems more efficiently. The object management group systems modeling language (OMG SysML™) is used to model Component sizing problems in order to facilitate problem formulation, model reuse and automatic generation of low-level code that can be solved using GAMS and its solvers. This framework is demonstrated by applying it to an example of a hydraulic log splitter. Based on this initial example, we discuss two advantages of this framework—total time taken in solving multiple scenarios for a given configuration and the graphical representation of a problem in SysML.
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combining mathematical programming and sysml for Automated Component sizing of hydraulic systems
ASME 2010 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, 2010Co-Authors: Aditya A Shah, Christiaan J J Paredis, Roger Burkhart, Dirk SchaeferAbstract:In this paper, we present a framework that improves a designer’s capability to determine near-optimal sizes of Components for a given system architecture. Component sizing is a hard problem to solve because of competing objectives, requirements from multiple disciplines, and the need for finding a solution quickly for the architecture being considered. In current approaches, designers rely on heuristics and iterate over the multiple objectives and requirements until a satisfactory solution is found. To improve on this state of practice, we introduce advances in the following two areas: a) Formulating a Component sizing problem in a manner that is convenient to designers and b) Solving the problem efficiently so that all of the imposed requirements are satisfied simultaneously and the solution obtained is mathematically optimal. An acausal, algebraic, equation-based, declarative modeling approach using mathematical programming (GAMS) is taken to solve these problems more efficiently. In addition the Systems Modeling Language (OMG SysML™) is used to formulate Component sizing problems to facilitate problem formulation, model reuse and the automatic generation of low-level code that can be solved using GAMS and its solvers (BARON). This framework is demonstrated by applying it to an example of a hydraulic log splitter.Copyright © 2010 by ASME
Fabian Burzlaff - One of the best experts on this subject based on the ideXlab platform.
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knowledge driven architecture composition case based formalization of integration knowledge to enable Automated Component coupling
IEEE International Conference on Software Architecture Workshops, 2017Co-Authors: Fabian Burzlaff, Christian BarteltAbstract:Using languages with formalized semantics for automating Component integration is a well-established research area. As a consequence, independently developed software systems can interact without the need for manual integration effort in a "plug-and-play" manner. However, such dynamic adaptive system architectures are not widely used in Industrial IoT scenarios. Practitioners mostly rely on informal, domain-specific standards as formal interface specifications tend to become highly complex quickly. Nonetheless, this results in high manual integration efforts as integration knowledge cannot be reused. Thus, interface specification should be tailored towards its case-based requirements. Interface specifications should only be created and persisted evolutionary after specific integration tasks with knowledge management techniques. The resulting knowledge-driven architecture composition enables integration knowledge reusability and can ultimately automate Component integration.
