Zafirov | Model-based systems engineering methods for integrated product design, process planning, and production systems design | Buch | 978-3-95974-068-5 | sack.de

Buch, Englisch, Band 21, 206 Seiten, Format (B × H): 148 mm x 210 mm

Reihe: Schriftenreihe VPE

Zafirov

Model-based systems engineering methods for integrated product design, process planning, and production systems design


1. Auflage 2017
ISBN: 978-3-95974-068-5
Verlag: RPTU Rheinland-Pfälzische Technische Universität Kaiserslautern Landau

Buch, Englisch, Band 21, 206 Seiten, Format (B × H): 148 mm x 210 mm

Reihe: Schriftenreihe VPE

ISBN: 978-3-95974-068-5
Verlag: RPTU Rheinland-Pfälzische Technische Universität Kaiserslautern Landau


Abstract
This thesis on model-based systems engineering methods for integrated product design, process
planning, and production systems design has the main goal of seamless integration between
product and production systems engineering processes, methods, and engineering artifacts.
This goal is achieved with the introduction of an integrated engineering process and an integrated
modeling approach. Thereby, the integrated engineering process can be realized with
the use of interdisciplinary systems modeling as an enabler. Regarding the modeling approach,
an architecture framework (AF) for model-based design is proposed. It serves as a common
base for describing products and production systems, while still making possible the explicit
differentiation between the two.
Contemporary trends such as the Internet of Things (IoT) as well as established design methodologies
in product and production systems engineering comprise the research foundation of
this work. Thereby, design methodologies and factory planning methodologies are the two
prominent topics in the discussion on the current state of the art in the context of this thesis.
Addressing the problem statement, the analysis of design methodologies starts with an overview
of systems engineering and model-based systems engineering, which are existing paradigms
that directly address gaps in engineering processes or traceability gaps along chains of interdependent
design results. A review of existing design processes follows. Thereby, both disciplinespecific
and interdisciplinary methodologies serve as sources for the analysis. The analysis concludes
by identifying a common pattern regarding the process steps and the engineering artifacts
(i.e. modeling concepts) across design methodologies, regardless of the engineering discipline.
The analysis of factory planning methodologies discusses different classifications of manufacturing
processes and derives one common classification that applies in the context of this thesis.
This classification serves as input for the synthesis part of the thesis (esp. for the modeling
taxonomy of the architecture framework). Furthermore, a comparison of different approaches
for manufacturing process planning identifies a common pattern, which follows a path from
information on the product, through identifying respective manufacturing processes to build it,
and right up to the manufacturing resources that carry out these processes (i.e. the PPR process
chain). The analysis in factory planning methodologies moves on to modeling methods and tool
support according to the Computer-Integrated Manufacturing (CIM) and Digital Factory (DiFa)
paradigms. It concludes with the realization that abstract systems modeling is not new to the
manufacturing domain and can serve to bridge the gap between product and production systems
design processes and modeling formalisms.
The analysis part of the thesis identifies the engineering process of manufacturing process planning
as the connecting link between product design and production systems design processes.
Hence, mainly manufacturing process planning is addressed in the synthesis of an integrated
engineering process for product and production systems design. According to this process,
product and production systems design have shared activities across their phases of concept
design. The utilization of multidisciplinary system models on both sides enables this engineering
process integration.

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