Page 1 of 11
Archives of Business Research – Vol. 12, No. 12
Publication Date: December 25, 2024
DOI:10.14738/abr.1212.18103.
Sheladiya, C., Shafighi, N., & Hajibashi, A. A. (2024). Digital Twin Development for the Automotive Industry. Archives of Business
Research, 12(12). 142-152.
Services for Science and Education – United Kingdom
Digital Twin Development for the Automotive Industry
Chirag Sheladiya
Najla Shafighi
Anahita Amini Hajibashi
ABSTRACT
This study explores Digital Twin Development for the Automotive Industry which
aims to bridge the divide between automotive and digital engineering. Results,
which were analyzed using demographic and regression analyses, indicate that
there are significant correlations between control accuracy and protection level,
but not with data integrity and privacy, and real-time monitoring effectiveness.
Keywords: Digital Twins technology, Digital engineering, Automotive Industry, Data
Integrity, Digitalization, and Automation.
INTRODUCTION
A Digital Twin (DT) is a virtual model that is intended to precisely replicate a physical system
by capturing performance data through sensors. This data is transmitted to a digital replica,
which allows for simulations that can provide valuable insights for enhancing the original
system. Due to their complexity and expense, DTs are not indispensable for all products, despite
the valuable advantages they offer. Industries that specialize in niche products are more likely
to implement DTs. The demand for DT technology is anticipated to rise as the market expands,
which is indicative of its increasing use in a variety of sectors. (Loaiza and Cloutier 2022a).
The transformational potential of Digital Twin development (DTD) in the automotive industry
is the primary focus of this study, with an emphasis on the improvement of vehicle design,
manufacturing, and maintenance. In real-time, DT technology provides a revolutionary
approach to the simulation, analysis, and optimization of vehicle performance. By incorporating
DT into existing systems, the research addresses challenges such as data management
complexity, high costs, and scalability. The study endeavors to enhance efficiency, reduce costs,
and expedite innovation in automotive manufacturing by investigating innovative approaches.
This will offer valuable insights to industry stakeholders who are actively attempting to
leverage digital technologies for a competitive advantage. (Brahme, & Shafighi, 2022)
The automotive industry is undergoing a rapid evolution, and the integration of DT presents
both opportunities and challenges. DTs are essential for the improvement of real-time
monitoring, control, and optimization in complex AS as virtual replicas of tangible assets. Their
integration has the potential to enhance operational efficiency and decision-making processes;
however, it necessitates sophisticated methodologies to guarantee seamless interaction
between digital and physical systems. Sophisticated AI algorithms and analytics are required
to provide real-time insights due to the vast quantity of data produced by DTs. Additionally, it
Page 2 of 11
143
Sheladiya, C., Shafighi, N., & Hajibashi, A. A. (2024). Digital Twin Development for the Automotive Industry. Archives of Business Research, 12(12).
142-152.
URL: http://doi.org/10.14738/abr.1212.18103
is imperative to safeguard data privacy and preserve trust by safeguarding these digital
systems from cyber threats. The study aims to resolve these multifaceted concerns by
investigating the effective integration of DT into AS, identifying advanced AI techniques for data
analysis, and establishing comprehensive security measures to protect digital twin
environments (DTE). The aim can be achieved by answering the following research questions:
1. How can Digital Twins be dynamically integrated into existing Automation systems to
enhance Real-time monitoring, control, and optimization in the automotive industry?
2. What advanced AI algorithms and analytics techniques are most effective for extracting
actionable insights from the vast amount of data generated by Digital Twins, enabling
Predictive maintenance, anomaly detection, and optimization of automation processes?
3. How can Digital Twins be secured against cyber threats and unauthorized access to
sensitive data, ensuring the privacy and integrity of information transmitted and stored
within the twin environment?
LITERATURE REVIEW
Implementation of Digital Twin Development
The article offers a thorough examination of the utilization of DTT in the field of industrial
energy management. Digital twin models are categorized in the paper according to their roles
in PM, RTM, and energy optimization. The authors address the important obstacles
encountered in the implementation of energy DT, such as computational complexity, model
accuracy, and data integration. In addition, they investigate the potential of these technologies
to advocate for sustainable industrial practices, reduce operational costs, and enhance energy
efficiency. Advocating for advancements in AI, IoT, and big data analytics to improve the
capabilities and reliability of energy DT in industrial contexts, the research underscores the
future trajectory of these systems. (Yu et al. 2022; Brahme, 2022)
It carefully analyses the variables that affect the implementation of DTT within the process
industry. Key enablers, including advancements in AI, data analytics, and IoT, are identified in
the paper, which enable the optimization of industrial processes, PM, and RTM. Conversely, the
authors emphasize substantial obstacles, such as the excessive costs of implementation, data
privacy concerns, and the integration challenges with existing systems. By consolidating the
results of numerous studies, the review offers a thorough examination of the present state of
digital twin implementation. The paper concludes by proposing future research directions to
address these challenges, underscoring the necessity of collaborative efforts between industry
and academia to completely achieve the potential of DT in the process industry. (Perno et al.
2022)
Protection Level
The review emphasizes the limitations of traditional security methods and underscores the
increasing significance of cybersecurity in safeguarding critical infrastructures. It underscores
the innovative use of DTT to improve the detection and response of threats in real time. The
authors review a variety of studies that illustrate the ability of digital siblings to both simulate
and analyze vulnerabilities, thereby establishing a proactive defense mechanism. There is a
consensus in the literature regarding the potential of DT to enhance cybersecurity resilience,
despite the challenges associated with integration and implementation with existing systems
Page 3 of 11
144
Archives of Business Research (ABR) Vol. 12, Issue 12, December-2024
Services for Science and Education – United Kingdom
In order to propose a comprehensive cybersecurity framework that employs digital siblings,
this review establishes the groundwork. (Masi et al. 2023)
The literature review concentrates on the incorporation of digital twin technologies and
blockchain to improve the security of cyber-physical systems (CPS). Existing vulnerabilities in
CPS and the inadequacy of conventional security strategies are identified in the review. It
examines the methods by which DT provide RTM and simulation capabilities, which, when
combined with the immutable and decentralized nature of blockchains, considerably enhance
situational awareness and security. Various studies are cited by the authors to substantiate the
potential of this integration to offer transparent, scalable, and resilient security solutions,
thereby establishing a strong foundation for their proposed security framework. (Suhail et al.
2022)
Data Integrity and Privacy
The critical role of correspondence measures in the standardization of digital twin technologies
is scrutinized by the authors. This evaluation evaluates a variety of correspondence measures
that guarantee the precision and uniformity of corporeal assets and their digital counterparts.
The authors evaluate the current frameworks, methodologies, and metrics that are employed
to achieve high fidelity in DT, underscoring the necessity of standardized protocols to
encourage scalability and interoperability. The paper offers valuable insights into further
improving the reliability and efficiency of DT by examining current practices and identifying
gaps. This exhaustive review underscores the significance of robust correspondence measures
in the advancement of digital twin standardization, thereby facilitating the development of
more integrated and effective applications across a variety of industries. (Khan et al. 2023) To
improve patient monitoring and security, it examines the integration of DTT with CPS. The
purpose of the literature review study is to investigate the convergence of DT and CPS in order
to generate real-time, virtual representations of patients. This will facilitate the opportune
detection of cyber-attacks and the continuous monitoring of physical health. Existing
frameworks and methodologies are examined by the authors, who emphasize the advantages
of this integration in terms of data security and patient safety. They confront obstacles such as
the complexity of security system implementation in healthcare environments, data privacy,
and interoperability. The paper underscores the potential of CPS-converged DT to transform
patient care by offering a secure, efficient, and comprehensive monitoring solution, thereby
making a substantial contribution to the field of healthcare information technology. (Xing et al.
2024)
Control Accuracy
It proposes a new method for improving the safety of intelligent connected vehicles (ICVs)
through the implementation of a digital counterpart system. The research delineates the
advancement of dynamic safety measurement-control technology, which utilizes real-time data
and synthetic simulations to anticipate and monitor vehicle performances. By employing the
digital counterpart, the system can proactively identify potential safety concerns and execute
corrective measures. The paper illustrates the efficacy of this technology by performing a
variety of case studies and simulations, emphasizing its potential to enhance the safety and
reliability of ICVs. This research is a substantial contribution to the field of intelligent
transportation systems and vehicle safety.(Chen et al. 2021)