A New Systems Engineering Model Based on the Principles of Axiomatic Design

Malaek, S.M.; Mollajan, Ali; Ghorbani, Amirhassan; Sharahi, Amir

doi:10.12720/jiii.3.2.143-151

Cited by 9 publications

(7 citation statements)

References 17 publications

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“…Actually, at the leaf level, both FRs and DPs should not need either redesigning or further decomposition. The hierarchies established between FRs and DPs represent, in fact, the product design structure (Suh, 2001;Sharahi et al, 2015).…”

Section: Axiomatic Designmentioning

confidence: 99%

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Estimation of porosity of rocks based upon axiomatic local linear model tree (a lolimot model) approach

Iranmanesh

Mollajan

2020

IJET

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Shear and Compressional Wave Velocities along with other Petrophysical Logs, are considered as upmost important data for Hydrocarbon reservoirs characterization. In this study, porosity of the extracted rocks form concerned wells is interest as it can indicate the oil capacity of the wells of interest. In this study, we employ the principles of Axiomatic Design theory, specially the first (independence) axiom, to more simplify the measurement system. Also, to clarify the strength of Axiomatic Design theory in reducing the complexity of the system and optimizing the measurement system, we utilize the The Lolimot model (LOcal LInear MOdel Tree) as a model from the neural network family and apply it before and after implementing the basic logic of Axiomatic Design (AD) theory. In addition, in order to illustrate strength of the proposed method emphasizing the effectiveness of a method which benefit from both AD theory and Lolimot model together, the existing system used to measure the rock porosity is addressed and actual data related to one of wells located in southern Iran is utilized. The results of the study show that integrating the Axiomatic Design principles with the LOLIMOT method leads to the least complex and most accurate results.

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Section: Axiomatic Designmentioning

confidence: 99%

“…In the simple case of a uniform probability distribution, the information content (I) can be defined as Equation 13, where; usually logarithms of base 2 (x = 2) are used (Suh, 1990(Suh, -2001Malaek et al, 2015).…”

Section: Axiomatic Designmentioning

confidence: 99%

Estimation of porosity of rocks based upon axiomatic local linear model tree (a lolimot model) approach

Iranmanesh

Mollajan

2020

IJET

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“…21 AD has been built on three core perspectives. 22 (1) Design domains AD consists of four domains: customer domain, functional domain, physical domain, and process domain, as displayed in Figure 1. These domains are represented by customer requirements (CRs), functional requirements (FRs), design parameters (DPs), and process variants (PVs), respectively.…”

Section: Ad Principlesmentioning

confidence: 99%

A semantic model for axiomatic systems design

Wang

Zhang

Chengtong

et al. 2017

Proceedings of the Institution of Mechanical Engineers, Part C:

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Design of large-scale engineering systems such as an automobile, satellite, or airplane is a process to satisfy requirements by making various decisions. Design axioms provide system designers with a theoretical background to make right decisions. However, the axiomatic systems design is still hard to be implemented in the real word due to its informal representation for both the human and machine, and few researches focus on formalizing concepts of this process. In order to define axiomatic systems design models to be both user-understandable and machine-readable, this paper combines axiomatic design process with the Semantic Web technology and proposes an axiomatic design semantic representation model, called axiomatic design ontology, which organizes customers’ requirements, functional requirements, design parameters, and design solutions. The class of concepts elements and their semantic relationships are defined by the Web Ontology Language (OWL2). Rules for identifying functional couplings (the Independence Axiom) and selecting the optimal design solution (the Information Axiom) are formally represented and encoded with the Semantic Web Rule Language, which enhances the reasoning capability of the axiomatic design ontology. A framework for capturing systems design semantic information based on the axiomatic design ontology, and aligning it with domain-specific ontologies according to the semantic mapping approach has been developed, by which elaborated design information is captured and shared. Finally, a case study of systems design of a satellite solar wing subsystem is given to demonstrate the proposed axiomatic design ontology-based systems design approach.

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“…FR7 Only once FR1 through FR6 is achieved (the system is designed to become stable), produce products with least time in system-Reduce cost further by reducing Standard Work in Process Inventory and additional waste(s). A variety of writings [27,42,[44][45][46] discuss the successful attributes of manufacturing systems. Figure 2 illustrates how the PDS incorporates the six requirements for system stability [47].…”

Section: Manufacturing System Designmentioning

confidence: 99%

“…Shi et al [26] argued that ADT was a natural choice to take into account the eco-factors in defining the functional requirements and design parameters in the design of an ecofriendly manufacturing system. Malaek et al [27] suggested using well-defined ADT to overcome the shortcomings of other conventional design approaches to eliminate the couplings of "cost" and "complexity" with system requirements. Chen [28] deployed the ADT and lean techniques to improve the efficiency of a production line for a medical company.…”

Section: Introductionmentioning

confidence: 99%

Extension of Manufacturing System Design Decomposition to Implement Manufacturing Systems That are Sustainable

Cochran

Hendricks

Barnes

et al. 2016

Journal of Manufacturing Science and Engineering

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This paper offers an extension of axiomatic design theory to ensure that leaders, managers, and engineers can sustain manufacturing systems throughout the product lifecycle. The paper has three objectives: to provide a methodology for designing and implementing manufacturing systems to be sustainable in the context of the enterprise, to define the use of performance metrics and investment criteria that sustain manufacturing, and to provide a systems engineering approach that enables continuous improvement (CI) and adaptability to change. The systems engineering methodology developed in this paper seeks to replace the use of the word "lean" to describe the result of manufacturing system design. Current research indicates that within three years of launch, ninety percent of "lean implementations" fail. This paper provides a methodology that leaders, managers, and engineers may use to sustain their manufacturing system design and implementation.

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A New Systems Engineering Model Based on the Principles of Axiomatic Design

Cited by 9 publications

References 17 publications

Estimation of porosity of rocks based upon axiomatic local linear model tree (a lolimot model) approach

Estimation of porosity of rocks based upon axiomatic local linear model tree (a lolimot model) approach

A semantic model for axiomatic systems design

Extension of Manufacturing System Design Decomposition to Implement Manufacturing Systems That are Sustainable

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