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The existing approach of SE to design of Socio-Economic Systems is an algorithmic method completed only through several iterative processes. Such an approach which depends on skill, knowledge, attitude, and experience (SKAE) of members of the design team is considered heuristic and does not give a formal theoretical framework to systems designers....

## Contexts in source publication

**Context 1**

... and comprehensive approach. However, the iterative nature of the problem solving set of processes which are selectively used to accomplish SE tasks; poses a problem in most cases. As a solution, particularly for the case of "Physical or Mechanical Systems", the "V-model" is a used; which is a classical approach of representing the SE process ( Fig. 1) ...

**Context 2**

... propose a model to estimate the amount of costs the system owners need to pay because of the any failure in satisfying the customers' FRs, we use the so called "Taguchi's loss function" as (14): (14) where L: represents the vector which its i th (i=1,2,3, .., n) element shows the cost imposed on the system because of failure to meet the FR i (i=1,2,3, .., n). K: represents the vector which its i th (i=1,2,3, .., n) element is the constant related to the FR i (i=1,2,3, .., n). ...

**Context 3**

... propose a model to estimate the amount of costs the system owners need to pay because of the any failure in satisfying the customers' FRs, we use the so called "Taguchi's loss function" as (14): (14) where L: represents the vector which its i th (i=1,2,3, .., n) element shows the cost imposed on the system because of failure to meet the FR i (i=1,2,3, .., n). K: represents the vector which its i th (i=1,2,3, .., n) element is the constant related to the FR i (i=1,2,3, .., n). FR: represents the vector which its i th (i=1,2,3, .., n) element is the FR i (i=1,2,3, .., n) has to be successfully fulfilled. ...

**Context 4**

... represents the vector which its i th (i=1,2,3, .., n) element is the constant related to the FR i (i=1,2,3, .., n). FR: represents the vector which its i th (i=1,2,3, .., n) element is the FR i (i=1,2,3, .., n) has to be successfully fulfilled. T FR : represents the vector which its i th (i=1,2,3, .., n) element is the target value of the FR i (i=1,2,3, .., n). ...

**Context 5**

... represents the vector which its i th (i=1,2,3, .., n) element is the constant related to the FR i (i=1,2,3, .., n). FR: represents the vector which its i th (i=1,2,3, .., n) element is the FR i (i=1,2,3, .., n) has to be successfully fulfilled. T FR : represents the vector which its i th (i=1,2,3, .., n) element is the target value of the FR i (i=1,2,3, .., n). ...

**Context 6**

... represents the vector which its i th (i=1,2,3, .., n) element is the FR i (i=1,2,3, .., n) has to be successfully fulfilled. T FR : represents the vector which its i th (i=1,2,3, .., n) element is the target value of the FR i (i=1,2,3, .., n). Knowing FRs' behaviors in real-world operation vary in certain limits (Not stochastic), we need to concentrate our efforts to develop suitable "mathematical expectations of the variables under consideration. ...

**Context 7**

... represents the vector which its i th (i=1,2,3, .., n) element is the FR i (i=1,2,3, .., n) has to be successfully fulfilled. T FR : represents the vector which its i th (i=1,2,3, .., n) element is the target value of the FR i (i=1,2,3, .., n). Knowing FRs' behaviors in real-world operation vary in certain limits (Not stochastic), we need to concentrate our efforts to develop suitable "mathematical expectations of the variables under consideration. ...

**Context 8**

... Var (FR): represents "the Variance-Covariance Matrix of the vector FR, VCM FR . And, Bias: represents "the vector which its i th (i=1,2,3, .., n) element is the systematic deviation of the FR i (i=1,2,3, .., n) from its predefined target value, T FRi . ...

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Systems engineering (SE) and SE management is the objective of all SE efforts, which defines the transformation of specific customer needs into a system product, service, or enterprise systems. Enterprise systems of systems engineering apply systems engineering fundamentals to the design of an enterprise. It is created by knowledge, principles, and...

## Citations

... Unit and integration tests find defects in individual components and the interfaces between components. System tests demonstrate that components are compatible, interact correctly, and transfer the correct data at the right time through their interfaces [13]. ...

... The V-Model as a Systems Engineering process[13]. ...

Improving software quality is one of the desired goals of software development teams. More so, financial companies must ensure the quality of the software product to guarantee financial transactions. For this reason, this study, based on the Design Science Research (DSR) approach, establishes the research question: Does implementing a test management framework in the development process improve the quality of the software product? The paper aims to answer this question we propose a software testing framework based on the processes described in the ISO/IEC/IEEE 29119–2 standard and the documentation templates of the ISO/IEC/IEEE 29119–3 standard, which became the technical guide for the evaluation of the developed software. Furthermore, we evaluated the framework through a case study applied in a financial company in Ecuador; we also publish the testing framework artifacts in a Zenodo open data repository. The principal results show an increase in bug detection in the range of 77% to 100%, reduction of defect density in the range of 95% to 0%, and a 12.5% reduction of previously reported software failures in production environments.

... Applying such a technique to the propulsion system, we need to somehow correlate performance parameters to the so-called DPs. It is noted that the above-mentioned principles are in line with the so-called axiomatic design theory [22]. ...

Remote sensing satellites propulsion subsystem preliminary design based on performance sizing is discussed. The process is a fairly complicated one considering a variety of operational as well as performance requirements. This research aims to reduce the number of iterations required by the current practice to reach a compromise. It is based on a rapid-sizing method that helps lessen lengthy iteration cycles. The proposed technique, similar to such class of preliminary design processes, leads to an acceptable approximation that must be properly conveyed to other disciplines involved for further elaborations. With proper selection of design and performance parameters together with fundamental relations, design boundaries are established; while the role of boundaries is to limit the design space, and to minimize the number of design cycles as a result. With the help of a suitable case-study, we demonstrate the effectiveness of the approach. Further investigations might be necessary for the cases where a greater number of uncertainties are involved.

... 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). ...

... 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). ...

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.

... 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. ...

... 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]. ...

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.

... Two axioms stand at the basis of this method [11, 12]. It can be mathematically demonstrated that designs following these axioms are better designs, in the sense of less complexity and less costs [13, 14]. AD assumes that designing systems requires input from different domains. ...

Abstract This paper applies and discusses the principles of Axiomatic Design for changing IT architecture in health care. It presents three case studies positioned in the field of Enterprise architecture that explore how IT architects, as professionals, manage change and re-design the structure of the IT systems in line with strategic goals. The research approach was to use a light modelling tool, Ampersand, for modelling the Enterprise architecture. Two types of models stand out: Type 1 Strategic IT models in which higher strategic goals are related to requirements for applications and Type 2 Technical management of systems models in which technical risks and risk of system failure in the current IT infrastructure were modelled. To bridge the views of different IT experts in the organization this work uses the customer domain, the functional domain and the physical domain from Axiomatic Design in an extended example in the paper. The V Model is used to bridge the models, and then it is extended with Axiomatic Design principles.

... In order to address and satisfy the identified requirements of the product, there is a wide variety of engineering design approaches to develop a capable product910. However, among all of these existing approaches, the strength of the Axiomatic Design (AD) theory to design an effective product, which is potentially capable of satisfying the customers' requirements, is emphasized [7, 9,1112. According to Suh [7,1314, to design any product or engineering system, the Customers' Attributes (CAs) must be specified into a minimum set of independent requirements usually defined by engineering terms in the functional domain of the product. ...

... Because of this, it is important that all major sources that may significantly cause some variations in the product's FRs are identified. This is, in fact, a good way to find potential factors which can significantly inhibit improvement of the probability of success in satisfying the established FRs [5, 12]. Among all of potential causes which can make considerable variations in the product's FRs, the effect of incapable manufacturing system is critical1819. ...

Utilizing the Axiomatic Design (AD) principles to develop a perfect product, design of a manufacturing system with minimal complexity is required. For the purpose of reducing the manufacturing system complexity, theoretically, it is preferred to integrate multiple Process Variables (PVs) of the product into a single process unit. However, due to significant presence of some active noise factors, this integration practice may result in failing to maintain the independence among some of Functional Requirements (FRs) of the product. This event is the result of statistical causal relationships unintentionally developed among a subset of the integrated PVs. In such a condition, the AD's Independence Axiom cannot be successfully satisfied and reaching a system with minimal complexity is inconceivable, even though an uncoupled or decoupled system design is apparently presented. To mitigate this kind of FRs coupling generated from the PVs integration, this study proposes partial & semi-partial correlation analysis as a statistical solution to identify the most appropriate integration choices where integrating a subset of the PVs is inevitable. Furthermore, based on the Taguchi's loss function, a quantitative criterion is established to fairly compare any two non-ideal manufacturing system designs and choose the one with relatively lower loss. The proposed approach explained in this study is verified based on hypothetical data.

... In fact, since an unhealthy manufacturing system with different kinds of vulnerabilities may cause quality degradation for the product through making a series of considerable variations in the product's specifications, design of a sound manufacturing system may considerably pave the way for reaching a high quality product45678. From the Axiomatic Design (AD) theory, a manufacturing system is, in fact, an engineering system intended to support the product's PVs9101112. Therefore, from this view, any technical problem for supporting the PVs is considered a serious obstacle for satisfying both DPs and FRs of the product. ...

... Therefore, from this view, any technical problem for supporting the PVs is considered a serious obstacle for satisfying both DPs and FRs of the product. That is, design of a capable manufacturing system should be regarded as one of the most critical steps in developing a high quality product1213. With respect to design of a sound manufacturing system based on the principles of the AD theory, part 1 of this work proved that integration of the product's PVs on a single process entity is a good way for reaching system designs with relatively lower complexity provided that no serious " noise © 2015 The Authors. ...

In this part of the work, to illustrate the strength of the " partial and semipartial correlation analysis, as the proposed solution described in detail in part 1, we consider design problem of the manufacturing system of a given product based on a set of hypothetical data and show how to explore the most appropriate integration choices in which the (causal) dependencies of the concerned PVs are minimal. Based on the results of this study, we emphasize that incorporating the identified sensitive PVs into the integration process will eventually lead to coupling among a subset of the product's FRs and isolation of these PVs is recommended as an ideal solution. However, sometimes, in the real world, for some of logical and/or technical reasons; such an ideal solution might be impossible. To deal with such a dichotomy, we use the Design of Experiments (DOE) methodology and offer the idea of controlling the values of the concerned PVs at specific levels to find the most appropriate condition (s) under which the minimal (causal) correlation between the integrated PVs may be achievable. On the basis of this idea, the worthwhile information the manufacturing system designers require to detect the safe levels at which the PVs can be integrated is achievable.

Purpose
Conventional powder bed fusion systems, with their high costs, proprietary nature and restrictive fees, limit research opportunities. This study aims to unveil an affordable, open-source hardware, open-source software laser-based metal powder bed fusion system. Recognizing the distinction between DIY and open-source hardware is crucial for widespread acceptance.
Design/methodology/approach
The authors present a comprehensive system architecture using object process methodology for functions and architecture, a design structure matrix to model system dependencies and classical technical drawing exploded views for select subsystems. Modularization enables high adaptability, fostering potential adoption.
Findings
The fully open system enables unrestricted research, mirroring common industrial metal laser-based powder bed fusion (L-PBF) systems. While “open” systems are available for purchase, they remain closed-source, lacking source code and technical drawings sharing, hindering contribution and co-development. The authors’ is the pioneering and sole open-source metal L-PBF system, boasting 1,500+ print hours. A series of industrial and academic adopters are currently implementing the system.
Originality/value
The open system, slicer software and controller offer unique process control, supporting multimaterial printing. The authors shared the design on the OpenAM GitHub page under the CERN-OHL-P v2 Open Source Hardware license. While it is functional for additive manufacturing (e.g. aluminum, tool steel, titanium and stainless steel), the entire process chain is actively evolving, ideal for co-development with the additive manufacturing community.

V-Model and Axiomatic Design are two proven systems engineering methodologies to support the design process of complex systems. Both methodologies originated in the late seventies. The V-Model is the more successful of the two, partly due to its simplicity and straightforwardness. AD is more powerful but also more complex. AD has a clear way of requirements management in domains that represent the customer needs, system functionality, physical execution, and manufacturing processes. Both models are generally seen as independent from each other. Also, in teaching courses they are considered two separate methodologies. In this paper it is investigated what the overleap of the V-Model and Axiomatic Design is, and if there can be defined a continuous learning path for (professional) teaching from V-Model to Axiomatic Design. The overlap appears to be quite substantial, the execution process of the V-Model can be seamlessly mapped on the process of Axiomatic Design, making the V-Model mainly a subset of Axiomatic Design. Axiomatic Design contributes to the V-Model. It improves understanding of the V-Model because Axiomatic Design clarifies artifacts that are not consciously embedded in the v-model but are still present.

Engineering design and concept analysis are examined here. The chapter focuses on inferential engineering designs, concept-knowledge designs, axiomatic design, relational concept analysis and model driven architectures . The inferential design theory is a framework for the integration of multiple conceptual design methods. For different engineering design theories, the dual graded graphs structure is outlined. Relational analysis is presented as a higher level formal concept analysis . Connections of context analysis with Meta-Meta -Model architectures are discussed.