scholarly journals Agile Service Engineering in the Industrial Internet of Things

2018 ◽  
Vol 10 (10) ◽  
pp. 100 ◽  
Author(s):  
Thomas Usländer ◽  
Thomas Batz
Keyword(s):  
Internet Of Things ◽  
Business Models ◽  
Smart Manufacturing ◽  
Interaction Patterns ◽  
Functional Requirements ◽  
Industrial Internet Of Things ◽  
Service Engineering ◽  
Analysis And Design ◽  
Information Models ◽  
Industrial Internet

The emerging Industrial Internet of Things (IIoT) will not only leverage new and potentially disruptive business models but will also change the way software applications will be analyzed and designed. Agility is a need in a systematic service engineering as well as a co-design of requirements and architectural artefacts. Functional and non-functional requirements of IT users (in smart manufacturing mostly from the disciplines of mechanical engineering and electrical engineering) need to be mapped to the capabilities and interaction patterns of emerging IIoT service platforms, not to forget the corresponding information models. The capabilities of such platforms are usually described, structured, and formalized by software architects and software engineers. However, their technical descriptions are far away from the thinking and the thematic terms of end-users. This complicates the transition from requirements analysis to system design, and hence the re-use of existing and the design of future platform capabilities. Current software engineering methodologies do not systematically cover these interlinked and two-sided aspects. The article describes in a comprehensive manner how to close this gap with the help of a service-oriented analysis and design methodology entitled SERVUS (also mentioned in ISO 19119 Annex D) and a corresponding Web-based Platform Engineering Information System (PEIS).

Industrial internet of things for smart manufacturing applications using hierarchical trustful resource assignment

Work ◽  
2021 ◽  
pp. 1-11
Author(s):  
Duan Pingli ◽  
Bala Anand Muthu ◽  
Seifedine Nimer Kadry
Keyword(s):  
Internet Of Things ◽  
Manufacturing Industry ◽  
Production Systems ◽  
Intelligent Manufacturing ◽  
Smart Manufacturing ◽  
The Internet ◽  
Resource Assignment ◽  
Industrial Internet Of Things ◽  
Assignment Method ◽  
Industrial Internet

BACKGROUND: The manufacturing industry undergoes a new age, with significant changes taking place on several fronts. Companies devoted to digital transformation take their future plants inspired by the Internet of Things (IoT). The IoT is a worldwide network of interrelated physical devices, which is an essential component of the internet, including sensors, actuators, smart apps, computers, mechanical machines, and people. The effective allocation of the computing resources and the carrier is critical in the industrial internet of Things (IIoT) for smart production systems. Indeed, the existing assignment method in the smart production system cannot guarantee that resources meet the inherently complex and volatile requirements of the user are timely. Many research results on resource allocations in auction formats which have been implemented to consider the demand and real-time supply for smart development resources, but safety privacy and trust estimation issues related to these outcomes are not actively discussed. OBJECTIVES: The paper proposes a Hierarchical Trustful Resource Assignment (HTRA) and Trust Computing Algorithm (TCA) based on Vickrey Clarke-Groves (VGCs) in the computer carriers necessary resources to communicate wirelessly among IIoT devices and gateways, and the allocation of CPU resources for processing information at the CPC. RESULTS: Finally, experimental findings demonstrate that when the IIoT equipment and gateways are valid, the utilities of each participant are improved. CONCLUSION: This is an easy and powerful method to guarantee that intelligent manufacturing components genuinely work for their purposes, which want to integrate each element into a system without interactions with each other.

scholarly journals Security Issues and Software Updates Management in the Industrial Internet of Things (IIoT) Era

Sensors ◽  
2020 ◽  
Vol 20 (24) ◽  
pp. 7160
Author(s):  
Imanol Mugarza ◽  
Jose Luis Flores ◽  
Jose Luis Montero
Keyword(s):  
Internet Of Things ◽  
Business Models ◽  
Service Providers ◽  
Leading Edge ◽  
Cyber Attacks ◽  
Industrial Internet Of Things ◽  
Safety Standards ◽  
Security Issues ◽  
Industrial Internet ◽  
Software Updates

New generation Industrial Automation and Control Systems (IACS) are providing advanced connectivity features, enabling new automation applications, services and business models in the Industrial Internet of Things (IIoT) era. Nevertheless, due to the extended attack surface and increasing number of cyber-attacks against industrial equipment, security concerns arise. Hence, these systems should provide enough protection and resiliency against cyber-attacks throughout their entire lifespan, which, in the case of industrial systems, may last several decades. A sound and complete management of security issues and software updates is fundamental to achieve such goal, since leading-edge security countermeasures implemented in the development phase may eventually become out-of-date. In this article, a review of the IEC 62443 industrial security standard concerning the security maintenance of IIoT systems and components is given, along with guidelines for the implementation of such processes. As concluded, the security issues and software updates management shall jointly be addressed by the asset owner, service providers and product suppliers. These security processes should also be compatible with the safety procedures established by safety standards.

HOW THE INDUSTRIAL INTERNET OF THINGS CHANGES BUSINESS MODELS IN DIFFERENT MANUFACTURING INDUSTRIES

2016 ◽  
Vol 20 (08) ◽  
pp. 1640015 ◽  
Author(s):  
CHRISTIAN ARNOLD ◽  
DANIEL KIEL ◽  
KAI-INGO VOIGT
Keyword(s):  
Internet Of Things ◽  
Business Models ◽  
Manufacturing Companies ◽  
Industrial Internet Of Things ◽  
Study Approach ◽  
Current State ◽  
Industrial Internet ◽  
Information And Communication ◽  
Multiple Case ◽  
Industry Sectors

The Industrial Internet of Things (IIoT) poses large impacts on business models (BM) of established manufacturing companies within several industries. Thus, this paper aims at analyzing the influence of the IIoT on these BMs with particular respect to differences and similarities dependent on varying industry sectors. For this purpose, we employ an exploratory multiple case study approach based on semi-structured expert interviews in 69 manufacturing companies from the five most important German industries. Owing the lack of previous research, our study contributes to the current state of management literature by revealing the following valuable insights with regard to industry-specific BM changes: The machine and plant engineering companies are mainly facing changing workforce qualifications, the electrical engineering and information and communication technology companies are particularly concerned with the importance of novel key partner networks, and automotive suppliers predominantly exploit IIoT-inherent benefits in terms of an increasing cost efficiency.

A Survey on Industrial Information Integration 2016–2019

2020 ◽  
Vol 05 (01) ◽  
pp. 33-163 ◽  
Author(s):  
Yong Chen
Keyword(s):  
Internet Of Things ◽  
Information Integration ◽  
Smart Grids ◽  
Web Of Science ◽  
Smart Manufacturing ◽  
Future Research ◽  
Industrial Internet Of Things ◽  
Physical Systems ◽  
Industrial Internet ◽  
Industrial Information Integration

Industrial information integration engineering (IIIE) is a set of foundational concepts and techniques that facilitate the industrial information integration process. In recent years, many applications of the integration between Internet of Things (IoT) and IIIE have become available, including industrial Internet of Things (IIoT), cyber-physical systems, smart grids, and smart manufacturing. In order to investigate the latest achievements of studies on IIIE, this paper reviews literatures from 2016 to 2019 in IEEEXplore and Web of Science. Altogether, 970 papers related to IIIE are grouped into 27 research categories and reviewed. The results present up-to-date development of IIIE and provide directions for future research on IIIE.

THE INFLUENCE OF THE INDUSTRIAL INTERNET OF THINGS ON BUSINESS MODEL DESIGN: A QUALITATIVE-EMPIRICAL ANALYSIS

2016 ◽  
Vol 20 (08) ◽  
pp. 1640014 ◽  
Author(s):  
SVEN M. LAUDIEN ◽  
BIRGIT DAXBÖCK
Keyword(s):  
Internet Of Things ◽  
Business Model ◽  
Business Models ◽  
Technological Development ◽  
Industrial Internet Of Things ◽  
Firm Level ◽  
Manufacturing Firm ◽  
Model Research ◽  
Industrial Internet ◽  
Depth Analysis

The Industrial Internet of Things is recently a widely discussed phenomenon. However, business level effects of this phenomenon are by now underresearched. We tackle this research gap by presenting an in-depth analysis of business model changes manufacturing firms employ to adequately react to this technological development. Against the background of a multiple-case study we identify and characterise three archetypes of business models manufacturing firm implement in order to benefit from opportunities provided by the Industrial Internet of Things. Furthermore, we present insights on how firms innovate their extant business model in this context. Thereby, our study considerably contributes to business model research and additionally bolsters up a strategic firm level perspective on the Industrial Internet of Things.

scholarly journals Emerging Technologies in Manufacturing

2020 ◽  
Vol 1 (2) ◽  
Keyword(s):  
Artificial Intelligence ◽  
Economic Development ◽  
Internet Of Things ◽  
Manufacturing Industry ◽  
Emerging Technologies ◽  
Smart Manufacturing ◽  
Industrial Internet Of Things ◽  
Profound Impact ◽  
The Core ◽  
Industrial Internet

Manufacturing is the way of transforming resources into products or goods which are required to cater to the needs of the society. It constitutes the foundation of any nation’s economic development. This paper reviews emerging technologies in manufacturing. These technologies include artificial intelligence, smart manufacturing, robotics, automation, 3D printing, nanotechnology, industrial Internet of things, and augmented reality. The use of these technologies will have a profound impact on the manufacturing industry. They have the potential to transform manufacturing as we know it. They should be at the core of any manufacturing upgrading effort.

Design and Development of IIoT Dashboard for Overall Equipment Effectiveness Monitoring of CNC Machine Tools

2021 ◽  
Vol 9 (12) ◽  
pp. 1603-1612
Author(s):  
Shreyas S
Keyword(s):  
Internet Of Things ◽  
Machine Tools ◽  
Performance Indicator ◽  
Numerical Control ◽  
Cnc Machine Tools ◽  
Smart Manufacturing ◽  
Key Performance Indicator ◽  
Cnc Machine ◽  
Industrial Internet Of Things ◽  
Industrial Internet

Abstract: Smart Manufacturing systems are regarded as the fourth revolution in the manufacturing industry, which is shaped by widespread deployment of sensors and Internet of Things. The present work constitutes of ‘Development of Industrial Internet of Things (IIoT) Dashboard for ‘Overall Equipment Effectiveness’ (OEE) Monitoring of CNC Machine Tools’ for a legacy CNC machine which is converted to smart machine. Data fetched from the CNC controllers through OPCUA is sent to the connected cloud database which will be imported into PowerBI desktop and the data has been classified and processed according to the requirement to develop a data modelling architecture of OEE, the Working status of the machine is visualized by Creating Monitoring and Performance charts and graphs of different design in Microsoft PowerBI Desktop. The Advanced visualizations constitutes od various features along with different analysing capabilities that results is creating reports which enumerates the state of OEE as a Key Performance Indicator (KPI). As Microsoft Power BI pertains a set of pre-established steps for data processing, the situation designated may constitute a limitation to automatic data refresh, leading to a do-over to verify, the specific interval of time, the conformity of data so they can be imported into the system. Keywords: Industrial Internet of Things (IIoT), Open Platform Communications United Architecture (OPCUA), Computer Numerical Control (CNC), Overall Equipment Effectiveness (OEE), Key Performance Indicator (KPI).

Reconceptualizing value innovation for Industry 4.0 and the Industrial Internet of Things

2019 ◽  
Vol 34 (6) ◽  
pp. 1203-1209 ◽  
Author(s):  
Paul Matthyssens
Keyword(s):  
Internet Of Things ◽  
Industry 4.0 ◽  
Business Models ◽  
Industrial Internet Of Things ◽  
Value Innovation ◽  
Content Type ◽  
Innovation Research ◽  
Industrial Internet ◽  
Challenges And Opportunities ◽  
New Research

Purpose Starting from the foundations of value innovation, this paper aims to give an idea of the key drivers and barriers – internal and external to the company – and to provide insight into proven capabilities underscoring the ability to create a flow of new value initiatives. These thoughts are then confronted with the present challenges of Industry 4.0 and the Industrial Internet of Things (IIoT). The confrontation leads to the identification of five capabilities for future-proof value innovation. Design/methodology/approach Literature review based upon the work of the author with more than two decades of experience within value innovation research is included. The review is supplemented with recent literature and an overview of the challenges of Industry 4.0/IIoT, which leads into a confrontation of the present status of value innovation with future requirements. Findings Value innovation remains important specifically for established companies facing path-breaking digital disruption of their existing business models provoked by Industry 4.0 and IIoT. Five key capabilities are suggested to rejuvenate value innovation and prepare it for the Industry 4.0 challenge: capabilities for designing, adapting and marketing product service systems; capabilities for blending digital strategy and processes with value offerings; capabilities for designing and mobilizing ecosystems and integrating these into a value-based IIoT platform; capabilities for combining and integrating technological and value innovation approaches; and capabilities for linking value creation to value capturing. Research limitations/implications This paper is more of a “viewpoint” than an empirically based paper presenting new research findings. It is based on expert judgment and confrontation with extant literature. The outlook indicating five key capabilities needs further empirical corroboration. Practical implications The overview of barriers and the “toolkit” for value innovation (Figure 1) and the five capabilities for future value innovation are expected to be managerially relevant. Originality/value The paper highlights the concept of value innovation, as discussed over the past decades, and links it to recent challenges and opportunities imposed by Industry 4.0 and the IIoT. The concept of value or strategic innovation is still valid but needs a re-conceptualization in view of these developments. The paper provides five capabilities business marketers should develop to perform value innovation in an Industry 4.0 environment.

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