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Architecting Networked Engineered Systems

Abstract

In this monograph we address the challenges in architecting networked engineered systems that are anchored in the Industry 4.0 construct. Global markets, rapidly evolving technologies, and changing customer preferences have all given rise to distributed manufacturing connected by internet technologies. While digitization helps in connecting erstwhile distributed systems and enables the use of digital models of physical processes in design and analysis, it does not automatically translate into the design of “smart” systems.

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Correspondence to Jelena Milisavljevic-Syed .

Glossary

AI

Artificial Intelligence

CAD

Computer-Aided Design

cDSP

Compromise Decision Support Problem

Cloud Computing

Cloud computing—virtualization of software and hardware resources allowing for networked resources to be accessed as a service in a ubiquitous way and on the basis of pay-as-you-go pricing Schaefer (2017)

Cloud-based Design and Manufacturing (CBDM)

A cyber-physical integration and control of manufacturing machines with CAD, CAE, ERP, and MES systems across one enterprise as a vertical integration. CBDM is a precursor for extending IoT and IoS Schaefer (2017)

Computational Complexity

Mathematical model of high complexity that requires extensive computational resources to instantiate

CRM

Customer Relations Management

DFDM

Design for Dynamic Management

Digital Platform

Provides decision support for engineers/designers, collaboration between different users from different domains and trains them how to understand the impacts of design decisions in order to speed up the design process and facilitate the creation of quality cost-effective designs

Digital Thread

Refers to the communication framework that allows a connected data flow and integrated view of the asset’s data throughout its lifecycle across traditionally siloed functional perspectives

Digital Twin

Refers to computerized companions of physical assets that can be used for various purposes. Digital twins use data from sensors installed on physical objects to represent their near real-time status, working condition or position

DOM

Dynamic Operability Model

ERP

Enterprise Resource Planning

FDIA

Fault Detection, Identification, and Accommodation

Low-Level Controls

Refer to control of machines and processes based on desired output and actual output. Low-Level Controls are characterized by real-time operation and take corrective actions based on real-time measurements (data). In contrast, High-Level Controls act on information and abstractions of data and deal with system level functionality as opposed to actual outputs

Health 4.0

A tactical deployment, and managerial model for healthcare inspired by the Industry 4.0

High-Level Decision Making

Enterprise level decision making

Industry 4.0

Industry 4.0 is the subset of the fourth industrial revolution that concerns industry. Industry 4.0 describes the trend towards automation and data exchange in manufacturing technologies and processes that include cyber-physical systems (CPS), the internet of things (IoT), industrial internet of things (IIOT), cloud computing, cognitive computing and artificial intelligence (Wikipedia)

Inspection Stations

Inspection Machines

Inspection System

Control System

IoP

Internet of People

IoS

Internet of Services

IoT

Internet of Things

MMP

Multistage Manufacturing Process

NES

Networked Engineered Systems

RIS

Reconfiguration of the Inspection System

RMS

Reconfigurable Manufacturing System

RMT

Reconfiguration of Machine Tools

SF

Smart Factory

Smart Manufacturing

Digitized Manufacturing

SoV

Stream of Variation model

SSOM

Steady-State Operability Model.

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Milisavljevic-Syed, J., Allen, J.K., Commuri, S., Mistree, F. (2020). Closure. In: Architecting Networked Engineered Systems . Springer, Cham. https://doi.org/10.1007/978-3-030-38610-8_7

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  • DOI: https://doi.org/10.1007/978-3-030-38610-8_7

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-38609-2

  • Online ISBN: 978-3-030-38610-8

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