scholarly journals Legal Considerations for Using Digital Twins in Additive Manufacture – A Review of the Literature

2021 ◽  
Author(s):  
Jenny Clementson ◽  
Jason Teng ◽  
Paul Wood ◽  
Chris Windmill
Keyword(s):  
Industry 4.0 ◽  
Data Privacy ◽  
Product Liability ◽  
Legal Issues ◽  
Additive Manufacture ◽  
Review Of The Literature ◽  
Digital Twins ◽  
New Business ◽  
And Control ◽  
Governance Arrangements

Rapid technological change presents new opportunities and reveals new risks, challenging existing governance arrangements. The fusion of Industry 4.0 technologies combines with Additive Manufacturing (AM) to create new business solutions. Legal issues with AM are well documented, for example Daly[1] explores the interaction of 3D printing with the law, identifying Intellectual Property, Product Liability and Data Privacy as areas of importance. However, this technology fusion has also enabled improved real-time digital representation, monitoring, simulation and control of the physical delivered through applications of Digital Twin. Such Digital Twins are prevalent in manufacturing and in AM can potentially provide assurance that a printed item meets specified requirements. However, additional legal considerations are emerging. This paper illustrates these by examining the attributes of “Digital Twins in Additive Manufacture Use Cases” revealed through literature.

scholarly journals Digital Twins Collaboration for Automatic Erratic Operational Data Detection in Industry 4.0

2021 ◽  
Vol 11 (7) ◽  
pp. 3186
Author(s):  
Radhya Sahal ◽  
Saeed H. Alsamhi ◽  
John G. Breslin ◽  
Kenneth N. Brown ◽  
Muhammad Intizar Ali
Keyword(s):  
Industry 4.0 ◽  
Manufacturing Systems ◽  
Interaction Mechanism ◽  
Semantic Knowledge ◽  
Smart Manufacturing ◽  
Data Detection ◽  
Workflow Model ◽  
Digital Twins ◽  
Potential Failure ◽  
Operational Data

Digital twin (DT) plays a pivotal role in the vision of Industry 4.0. The idea is that the real product and its virtual counterpart are twins that travel a parallel journey from design and development to production and service life. The intelligence that comes from DTs’ operational data supports the interactions between the DTs to pave the way for the cyber-physical integration of smart manufacturing. This paper presents a conceptual framework for digital twins collaboration to provide an auto-detection of erratic operational data by utilizing operational data intelligence in the manufacturing systems. The proposed framework provide an interaction mechanism to understand the DT status, interact with other DTs, learn from each other DTs, and share common semantic knowledge. In addition, it can detect the anomalies and understand the overall picture and conditions of the operational environments. Furthermore, the proposed framework is described in the workflow model, which breaks down into four phases: information extraction, change detection, synchronization, and notification. A use case of Energy 4.0 fault diagnosis for wind turbines is described to present the use of the proposed framework and DTs collaboration to identify and diagnose the potential failure, e.g., malfunctioning nodes within the energy industry.

Datenmacht

2021 ◽  
Author(s):  
Simon Deuring
Keyword(s):  
Case Studies ◽  
Legal System ◽  
Industry 4.0 ◽  
Technological Development ◽  
Free Market ◽  
Balance Of Power ◽  
Cost Reductions ◽  
New Business ◽  
The Law

Data shifts the balance of power in the economy dramatically. However, digitisation also offers a multitude of opportunities: the development of new business areas, cost reductions and personalised offers. The increasing speed of technological development forces the legal system to tread on thin ice. Is the key in a regulated or free market? The book shows risks and opportunities of both options, as well as the strengths and weaknesses in European and national law. By using the latest case studies and entering new areas of the law, the book explores the question of how the Industry 4.0 should be designed.

Recorded Business Meetings and AI Algorithmic Tools: Negotiating Privacy Concerns, Psychological Safety, and Control

2021 ◽  
pp. 232948842110370
Author(s):  
Peter W. Cardon ◽  
Haibing Ma ◽  
Carolin Fleischmann
Keyword(s):  
Social Contract ◽  
Data Privacy ◽  
Psychological Safety ◽  
Two Dimensions ◽  
Management Control ◽  
Privacy Concerns ◽  
Business Meetings ◽  
Control Versus ◽  
Algorithmic Analysis ◽  
And Control

Artificial intelligence (AI) algorithmic tools that analyze and evaluate recorded meeting data may provide many new opportunities for employees, teams, and organizations. Yet, these new and emerging AI tools raise a variety of issues related to privacy, psychological safety, and control. Based on in-depth interviews with 50 American, Chinese, and German employees, this research identified five key tensions related to algorithmic analysis of recorded meetings: employee control of data versus management control of data, privacy versus transparency, reduced psychological safety versus enhanced psychological safety, learning versus evaluation, and trust in AI versus trust in people. More broadly, these tensions reflect two dimensions to inform organizational policymaking and guidelines: safety versus risk and employee control versus management control. Based on a quadrant configuration of these dimensions, we propose the following approaches to managing algorithmic applications to recording meeting data: the surveillance, benevolent control, meritocratic, and social contract approaches. We suggest the social contract approach facilitates the most robust dialog about the application of algorithmic tools to recorded meeting data, potentially leading to higher employee control and sense of safety.

Digital Twins: Review and Challenges

2021 ◽  
Vol 21 (3) ◽  
Author(s):  
Maria G. Juarez ◽  
Vicente J. Botti ◽  
Adriana S. Giret
Keyword(s):  
Computer Science ◽  
Industry 4.0 ◽  
Multi Agent System ◽  
Agent System ◽  
Digital Twin ◽  
Digital Twins ◽  
Science Approach ◽  
Multi Agent ◽  
Current Operating

Abstract With the arises of Industry 4.0, numerous concepts have emerged; one of the main concepts is the digital twin (DT). DT is being widely used nowadays, however, as there are several uses in the existing literature; the understanding of the concept and its functioning can be diffuse. The main goal of this paper is to provide a review of the existing literature to clarify the concept, operation, and main characteristics of DT, to introduce the most current operating, communication, and usage trends related to this technology, and to present the performance of the synergy between DT and multi-agent system (MAS) technologies through a computer science approach.

scholarly journals A Modular Digital Twinning Framework for Safety Assurance of Collaborative Robotics

2021 ◽  
Vol 8 ◽  
Author(s):  
J.A. Douthwaite ◽  
B. Lesage ◽  
M. Gleirscher ◽  
R. Calinescu ◽  
J. M. Aitken ◽  
...  
Keyword(s):  
Testing Strategy ◽  
Modular Architecture ◽  
Industrial Case Study ◽  
Safety Assurance ◽  
Physical Environments ◽  
Digital Twins ◽  
The Creation ◽  
Hardware Platforms ◽  
And Control

Digital twins offer a unique opportunity to design, test, deploy, monitor, and control real-world robotic processes. In this paper we present a novel, modular digital twinning framework developed for the investigation of safety within collaborative robotic manufacturing processes. The modular architecture supports scalable representations of user-defined cyber-physical environments, and tools for safety analysis and control. This versatile research tool facilitates the creation of mixed environments of Digital Models, Digital Shadows, and Digital Twins, whilst standardising communication and physical system representation across different hardware platforms. The framework is demonstrated as applied to an industrial case-study focused on the safety assurance of a collaborative robotic manufacturing process. We describe the creation of a digital twin scenario, consisting of individual digital twins of entities in the manufacturing case study, and the application of a synthesised safety controller from our wider work. We show how the framework is able to provide adequate evidence to virtually assess safety claims made against the safety controller using a supporting validation module and testing strategy. The implementation, evidence and safety investigation is presented and discussed, raising exciting possibilities for the use of digital twins in robotic safety assurance.

scholarly journals Supply chain resilience and industry 4.0: a evaluation of the Brazilian northeast automotive OEM scenario post COVID-19

2021 ◽  
Vol 3 (1) ◽  
Author(s):  
Milton C. Soares ◽  
Cristiano V. Ferreira ◽  
Thiago B. Murari
Keyword(s):  
Supply Chain ◽  
Product Quality ◽  
Automotive Industry ◽  
Industry 4.0 ◽  
Future Outlook ◽  
Control Plan ◽  
Quality Planning ◽  
Planning And Control ◽  
Brazilian Northeast ◽  
And Control

AbstractCOVID-19 outbreak has heavily impacted the manufacturing industry, including Brazilian Automotive Industry. The effects of COVID-19 created restrictions in several industry processes as supply chain. On the other hand, several industry 4.0 technologies is able to support the industry supply chain activities in the COVID 19 scenarios, as well it may contributed for the automotive industry recovery and it will define the next steps of this industry. A supply chain is a network between a company and its suppliers to produce and distribute a specific product to the final buyer. Industry 4.0 is related to the technology development and the digitalization process that improve significantly productivity. Considering the automotive process, an important reference model is described in Advanced Product Quality Planning and Control Plan, that is a manual that communicate the guidelines of the product quality planning and control plan for internal and external suppliers. In this scenario, this paper evaluated the current situation and the future outlook for the adoption of Industry 4.0 technologies in the automotive OEM post-pandemic scenario on the point of view of automotive specialists. The results of this research provide an overview of the current situation and the future outlook for the usage of Industry 4.0 technologies by the Brazilian Northeast automotive OEM, from the perspective of manufacturing engineering experts on APQP.

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