Axiomatic Design/Design Patterns Mashup: Part 1 (Theory)

Thomas, John; Mantri, Pam

doi:10.1016/j.procir.2015.08.010

Cited by 8 publications

(5 citation statements)

References 7 publications

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“…7. Cynefin & Knowledge Hierarchy [46][47] Cynefin is unique in emphasizing distinct and discernable managerial realms and heuristics ( Fig. 7) where either reductionism (i.e., the whole is the sum of its parts) or holism (i.e., the whole is more than the sum of its parts) is the dominant operative.…”

Section: Cynefinmentioning

confidence: 99%

Axiomatic Cloud Computing Architectural Design

Thomas

Mantri

2019

MATEC Web Conf.

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Modern cloud computing makes available a plethora of scalable cloud computing offerings. The cloud is increasingly becoming the backbone of the highly complex modern knowledge-economy that includes Social, Mobile, IoT, Big-Data and AI. Knowledge-based products and services follow fat-tail distributions such as the power-law that poses major opportunities and challenges for the designer. The Axiomatic Designer is uniquely positioned in designing for the de-novo situations that the fat-tailed distributions expose. Also, the cloud frees-up the architectural decision-making away from the legacy compatibility-burden, and towards various cloud-native (i.e., de-novo/solution-neutral) as well as hybrid (on-prem/cloud & cloud/cloud) architectures. Further more, the competitive landscape around the cloud is not static; it is adaptive and evolving rapidly. Here again, Axiomatic Design (AD) is uniquely positioned in rising upto the various de-novo challenges This, however, requires contributions from frameworks such as Knowledge-as-Heterarchically-Hierarchical (KA|h|H), Stigmergy, Complex Adaptive Systems (CAS), Cynefin, Boyd’s OODA-Loop Theory of asymmetric fast-transients, Axiomatic-Maturity-Diagram (AMD), as well as Weick’s Loose-Coupling approach to help unify and strengthen the Axiomatic approach. This paper unifies the above approaches in order to tackle the architectural challenges of cloud computing.

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Section: Cynefinmentioning

confidence: 99%

Axiomatic Cloud Computing Architectural Design

Thomas

Mantri

2019

MATEC Web Conf.

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“…Particularly outstanding, Hafiz et al [12] sum up 96 such patterns without which it is very difficult for system analysts to identify and integrate cybersecurity requirements. Thomas et al [13] build on this work in order to make these (bottom-up) design patterns usable in AD (top-down). We applied their unique approach to our case study.…”

Section: Sfa and Ad For Integrated Safety/security Designmentioning

confidence: 99%

An architectural approach to the integration of safety and security requirements in smart products and systems design

Riel

Kreiner

Messnarz³

et al. 2018

CIRP Annals

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Assuring functional safety and IT security is rapidly becoming an essential key challenge to the design of any connected smart product and industrial manufacturing system. This paper proposes an architectural approach to the integrated consideration of functional safety and IT security requirements in the design process of smart products and the (Industrial) Internet of Things (IIoT). Based on Axiomatic Design and Signal Flow Analysis, it shows that such requirements have related impacts on system architectural design choices rendering integrated design necessary to meet the desired risk reduction levels effectively and efficiently. A case study in the automotive domain is presented in order to illustrate and validate the proposed approach.

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“…The creative mashup between two diametrically opposed design methodologies (i.e., the top-down Axiomatic approach vs. the bottom-up Design Patterns approach) was discussed in [69][70]. Thus, the top-down V-approach was juxtaposed with the bottom-up Λapproach to create the N-model.…”

Section: Axiomatic Design For Complex Adaptive Systemsmentioning

confidence: 99%

Complex Adaptive Blockchain Governance

Thomas

Mantri

2018

MATEC Web Conf.

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The blockchain revolution upholds the decentralizing ideal of “control nothing.” It is natural that such a pursuit would face issues of governance that demand reasonable control; control that is both operational as well as adaptive in nature. Eliminating middlemen and handing over controls to a trusted system of trustless agents does not thereby bestow trust across time. This is especially true when relentless change is the order of the day. Issues of governance rise up when blockchain systems (especially those that have embedded smart contracts) are forced to operate increasingly away from their original intent. Smart contracts need governance when beset with the problem of the unknown-unknowns. Guided by the axiomatic approach, this paper looks at the paradoxical issue of blockchain governance from a Complex Adaptive Systems (CAS) perspective that helps frame the fundamental problem of decentralization. The objective is to solve the Blockchain Governance Kernel Design. Real-life examples are used to illustrate the findings.

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Axiomatic Design/Design Patterns Mashup: Part 1 (Theory)

Cited by 8 publications

References 7 publications

Axiomatic Cloud Computing Architectural Design

Axiomatic Cloud Computing Architectural Design

An architectural approach to the integration of safety and security requirements in smart products and systems design

Complex Adaptive Blockchain Governance

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