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Cyber-Physical Business Systems Modelling: Advancing Industry 4.0.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Cyber-Physical Business Systems Modelling: Advancing Industry 4.0./
作者:	Medoh, Chuks Nnamdi.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2019,
面頁冊數:	207 p.
附註:	Source: Dissertations Abstracts International, Volume: 82-09, Section: B.
Contained By:	Dissertations Abstracts International82-09B.
標題:	Standard deviation. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28278434
ISBN:	9798569991624

Cyber-Physical Business Systems Modelling: Advancing Industry 4.0.
Medoh, Chuks Nnamdi.

Cyber-Physical Business Systems Modelling: Advancing Industry 4.0. - Ann Arbor : ProQuest Dissertations & Theses, 2019 - 207 p.

Source: Dissertations Abstracts International, Volume: 82-09, Section: B.

Thesis (D.Phil.)--University of Johannesburg (South Africa), 2019.

This item must not be sold to any third party vendors.

The dynamic digital age drives contemporary multinationals to focus on delivering world-class business solutions with the use of advanced technology. Contemporary multinationals relate to a present-day business primarily engaged to generate profits. These complex multinationals offer value through the manufacture, sale, and management of products and services. Disruptive strategies in operations driven by emerging technological innovations demand continuous business improvements. These insightful opportunities are inclusive of operations, enterprise systems, engineering management, and research. Business sustainability is a strategic priority to deliver exceptional digital solutions. The Fourth Industrial Revolutions (4IR) offer significant technological advancements for total business sustainability. The underlying 4IR technologies include Cyber-Physical Systems (CPS). The collective challenges of a large global business are not easy to predict. CPS protocols deliver sustainable prospects required to integrate and model physical systems in real-time driven by the 4IR implementations. The goal of this thesis is to develop a model (CPS) suitable for self-predicting and to determine ideal operational practice driven by technologies of the 4IR. The model (CPS) seeks a novel tool effective for comprehensive business evaluation and optimisation. The competence of the anticipated tool includes suitability to collaborate current operations and predict the impact of change on a complex business. The model (CPS) development is driven by technological problem-solving competencies of engineering management and beyond centred on a mixed-method approach. This thesis adopts business processes as a basis for the constitution of the model (CPS). The model data is captured in Visio, validated and subsequently modelled in Accuprocess. The model is tested via two business cases; a single and multiple simplified relationships with the baseline validated. The validated model (CPS) is then adopted to determine the impact of changes on the business. The eighteen change variables are extracted from literature. These variables are defined mathematically and a factorial experimental protocol is adopted to determine the relationship between these variables and its impact on the business (via the CPS). The factorial experimental protocol is constituted and the model is run repetitively with the factorial constraints. The resultant output of the factorial is a multivariable equation representing the impact of each of the change variables on the business. The model (CPS) articulates four databases; (1) Business processes delivering a digital prototype of a real-world modern multinational, (2) Business process modelling tools for configuration, testing, and analysis of the developments, (3) Business process variables comprising factors with significant influences on business executions, (4) Optimisation database for comparative efficient validation of the model (CPS) outputs. An initial study conducted indicates simulation methods and Design of Experiments (DOE) statistical techniques as basic differentiators for performing predictive analytics. Both approaches are crucial navigators for randomising decision-nodes of process steps and constitute experimental metrics for quantification. The Taguchi method is decisive for streamlining the number of experimental runs of large input factors and interactions. The key outputs of the investigative scenarios are optimal operational practices for current and future business demand. The results introduce an innovative approach to business analysis tools and decision-support to determine relationships between variables and impact to the business. Proof that modelling a complex business as a CPS to provide a comprehensive input and systems dynamic of a complex business for predictive capability is possible. The results deliver a singular equation effectively representing the business response for comprehensive factors impacting operations set a statistical significance of 95%. This provides clarity that the most significant variables impacting a business can be evaluated with the impacts reduced to simple correlations. The singular equation implies that any modern business without prepositioning process steps can substitute associated experimental values to predict business demand. The outputs introduce a viable alternative to existing business models with reduced efforts and advancements to implementing business obligations. This offers a shift from traditional analysing methods incapable of self-predicting in real-time. The results provide a validated and generic model (CPS) for detailed business evaluation, optimisation, and sustainability requiring moderate skill competencies.

ISBN: 9798569991624Subjects--Topical Terms:

3560390
Standard deviation.
Subjects--Index Terms:

Business processes

Cyber-Physical Business Systems Modelling: Advancing Industry 4.0.
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300 $a 207 p.
500 $a Source: Dissertations Abstracts International, Volume: 82-09, Section: B.
500 $a Advisor: Telukdarie, Arnesh.
502 $a Thesis (D.Phil.)--University of Johannesburg (South Africa), 2019.
506 $a This item must not be sold to any third party vendors.
520 $a The dynamic digital age drives contemporary multinationals to focus on delivering world-class business solutions with the use of advanced technology. Contemporary multinationals relate to a present-day business primarily engaged to generate profits. These complex multinationals offer value through the manufacture, sale, and management of products and services. Disruptive strategies in operations driven by emerging technological innovations demand continuous business improvements. These insightful opportunities are inclusive of operations, enterprise systems, engineering management, and research. Business sustainability is a strategic priority to deliver exceptional digital solutions. The Fourth Industrial Revolutions (4IR) offer significant technological advancements for total business sustainability. The underlying 4IR technologies include Cyber-Physical Systems (CPS). The collective challenges of a large global business are not easy to predict. CPS protocols deliver sustainable prospects required to integrate and model physical systems in real-time driven by the 4IR implementations. The goal of this thesis is to develop a model (CPS) suitable for self-predicting and to determine ideal operational practice driven by technologies of the 4IR. The model (CPS) seeks a novel tool effective for comprehensive business evaluation and optimisation. The competence of the anticipated tool includes suitability to collaborate current operations and predict the impact of change on a complex business. The model (CPS) development is driven by technological problem-solving competencies of engineering management and beyond centred on a mixed-method approach. This thesis adopts business processes as a basis for the constitution of the model (CPS). The model data is captured in Visio, validated and subsequently modelled in Accuprocess. The model is tested via two business cases; a single and multiple simplified relationships with the baseline validated. The validated model (CPS) is then adopted to determine the impact of changes on the business. The eighteen change variables are extracted from literature. These variables are defined mathematically and a factorial experimental protocol is adopted to determine the relationship between these variables and its impact on the business (via the CPS). The factorial experimental protocol is constituted and the model is run repetitively with the factorial constraints. The resultant output of the factorial is a multivariable equation representing the impact of each of the change variables on the business. The model (CPS) articulates four databases; (1) Business processes delivering a digital prototype of a real-world modern multinational, (2) Business process modelling tools for configuration, testing, and analysis of the developments, (3) Business process variables comprising factors with significant influences on business executions, (4) Optimisation database for comparative efficient validation of the model (CPS) outputs. An initial study conducted indicates simulation methods and Design of Experiments (DOE) statistical techniques as basic differentiators for performing predictive analytics. Both approaches are crucial navigators for randomising decision-nodes of process steps and constitute experimental metrics for quantification. The Taguchi method is decisive for streamlining the number of experimental runs of large input factors and interactions. The key outputs of the investigative scenarios are optimal operational practices for current and future business demand. The results introduce an innovative approach to business analysis tools and decision-support to determine relationships between variables and impact to the business. Proof that modelling a complex business as a CPS to provide a comprehensive input and systems dynamic of a complex business for predictive capability is possible. The results deliver a singular equation effectively representing the business response for comprehensive factors impacting operations set a statistical significance of 95%. This provides clarity that the most significant variables impacting a business can be evaluated with the impacts reduced to simple correlations. The singular equation implies that any modern business without prepositioning process steps can substitute associated experimental values to predict business demand. The outputs introduce a viable alternative to existing business models with reduced efforts and advancements to implementing business obligations. This offers a shift from traditional analysing methods incapable of self-predicting in real-time. The results provide a validated and generic model (CPS) for detailed business evaluation, optimisation, and sustainability requiring moderate skill competencies.
590 $a School code: 2140.
650 4 $a Standard deviation. $3 3560390
650 4 $a Simulation. $3 644748
650 4 $a Design specifications. $3 3683440
650 4 $a Manufacturing. $3 3389707
650 4 $a Research & development--R&D. $3 3554335
653 $a Business processes
653 $a Business process variables
653 $a Contemporary multinationals
653 $a Cyber-physical systems
653 $a Design of experiments
653 $a Fourth industrial revolution
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793 $a English
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