17th World Congress on Engineering Asset Management (WCEAM)
Ho Chi Minh City, Vietnam 18 –20 October 2023
Sustainable Management of Engineered Assets in a Post Covid-19 World: Industry 4.0, Digital Transformation, Society 5.0 and Beyond

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1Paper No.
001

Abstract
Title: Road User-Oriented Asset Management
Road infrastructure assets facilitate transportation of people and goods. The assets deteriorate over time;hence, it is essential to monitor and assess the condition of road networks and infrastructure so that timely
intervention can be implemented to maintain high levels of service. However, the convention on roadassessment seems to be derived from legacy and narrowly focused practice of monitoring only the pavement
condition, with ramifications on suboptimal and unsustainable interventions. The stakeholders, especially theroad users, need to be involved in the decision-making process. This approach is known as user-oriented andservice-based approach, in which the requirements and expectations of the prime stakeholders, that is, theroad users, are prioritized and included in the decision-making processes of road asset management. Given
that the perceptions and priorities of stakeholders vary in different jurisdictions, this paper discusses users’
involvement in assessing the condition of road infrastructure in a case study jurisdiction

2006

Title: OPTIMISING SOLAR AND BATTERY ENERGY STORAGE SYSTEMS USING YEARLY INTEVAL POWER DATA
Renewable sources of power generation can be cheaper than fossil-based power generation when engineered
correctly. Existing solar/battery energy storage systems (BESS) have established sizing practices that obtaindata from; peak demand records provided by energy retail companies, software modelling that applies provenrenewable asset generation profiles, and average base load power usage recorded from energy management
systems. Rarely is asset control factored into the sizing of a renewables system, and dynamic power shifting ofasset loads is not practiced nor incorporated into existing battery control systems. This exposes systems toopen loop inefficiencies which can degrade lithium and lead-acid based batteries exponentially. To
demonstrate what is required to optimise the sizing of solar/BESS installations, this paper presents a numericalmodel that factors solar, power grid importation using BESS, to reduce grid power charges. The results showthat sizing of solar and/or BESS must simulate yearly power interval data impacts from solar generation andbattery discharging/charging to optimise the size and cost of a system.

17th World Congress on Engineering Asset Management (WCEAM)
Ho Chi Minh City, Vietnam 18 –20 October 2023
Sustainable Management of Engineered Assets in a Post Covid-19 World: Industry 4.0, Digital Transformation, Society 5.0 and Beyond

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3Paper No.
007

Abstract
Title: VALVE REGULATED LEAD-ACID BATTERY DEGREDATION MODEL FOR INDUSTRY APPLICATIONS
The demand for battery energy storage systems (BESS) is exponentially growing due to a global focus onsustainability and emissions reductions. VRLA batteries have been used extensively in standby BESS
applications due to their wide availability and low cost. However, these batteries are highly susceptible toextreme degradation and loss of life when applied to baseload power variability. This makes the lead-acidbattery chemistry unviable in large BESS systems. This paper will demonstrate the battery whole of life impact
from irreversible sulphation, active mass degradation, temperature, and state of charge. Furthermore, thispaper presents a numerical degradation model that uses base load power requirements to size the batteries
and determine the extent of degradation at end-of-life conditions. Thereby providing industry with a low
computational cost battery degradation model that is uniquely suitable for industry applications.

4009

Title: Integrated Decision-Making Framework in Industrial Asset Management for Assessing and Managing
Emerging Risks.
Major challenges for the most used traditional assessment methods of safety risks are the growing complexity
and uncertainty of modern systems driven by the digital era which inexorably leads to a rise in emerging risks.
These methods for assessing and managing safety risks have their own limits and might not char-acterize all
aspects that affect sociotechnical system safety in the context of new emerging risks. Thus, new tools areneeded for the new problems. Hence, the need of building comprehensive decision support methodologies
arises from those threats associated with the complexity inherent to industry 4.0 and uncertainty associatedwith natural disasters, in conjunction with new organizational risks as well as biases in human logic. On thesegrounds, this paper aims at developing an Integrated De-cision-Making Framework in Industrial AssetManagement for Assessing and Man-aging Emerging Technology Risks as well as Extreme, Rare and Disruptive
Events. This should account both for traditional and new emerging risk safety management. In this regard, we
have chosen a duo of concepts that we consider the best ap-proaches, namely, the Functional ResonanceAnalysis Method (FRAM) and the System-Theoretic Accident Model and Processes (STAMP). These methods
are much more efficient than the conventional ones to engineer complexity and uncer-tainty in modern sociotechnical systems. In fine, to reveal the usefulness of this framework for identifying and managing industrial

17th World Congress on Engineering Asset Management (WCEAM)
Ho Chi Minh City, Vietnam 18 –20 October 2023
Sustainable Management of Engineered Assets in a Post Covid-19 World: Industry 4.0, Digital Transformation, Society 5.0 and Beyond

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asset risks, forthcoming targets will be devoted to performing a case study dealing with a complex sociotechno-logical system. The latter is dubbed LineDrone, a Hydro-Quebec1 robotic platform designed forinspecting and maintaining energized transmission lines.

5011

Title: Condition-based Inspection for Rail Track Geometry Degradation
Maintaining railway infrastructure is critical for ensuring the safety and comfort of passengers. However,planning and executing operation & maintenance (O&M) activities are complicated by the fact that railways
are typically comprised of hundreds-to-thousands of kilometers of linearly distributed assets. One of the key
degradation modes of rail infrastructure is deformation of track geometry caused by repeating loading, andfrequent inspection and maintenance activities are therefore required to ensure the safety of rail operations.
The maintenance action for track geometry deterioration mitigation is typically tamping, the timing of which isplanned using periodic inspection activities via measurements from track recording vehicles (TRV). While TRVs
can collect the geometry data of rail tracks quickly, they typically used to inspect thousands of kilometers ofrail. Railway operators therefore need methods efficiently planning inspection operations to maximize thesafety of the network. In this paper, the authors’ previous study is extended to in-clude to analyze thepotential benefits of implementing dynamic inspection — i.e. Condition-Based Inspection (CBI) — for trackgeometry. The key concept and ad-vantage of CBI is that next inspection time is scheduled according to thecurrent inspected conditions. The policy of maintenance following inspections in this work is the same asprevious study. The developed CBI is applied with the same real case study of Queensland Rail (Brisbane,
Australia) and benchmarking with current pe-riodic inspection planning.

6015

Title: An analysis of fault induced impulse signals using a Maximum Correlation Kurtosis Deconvolution and
an improved synchro squeezing transform
Abstract Fault induced impulse vibration signals from practical industrial cases often contaminated by strong
background noise, which can largely affect the accuracy of fault diagnosis. Furthermore, the condition
monitoring signal usually contains non-stationary features due to a changing speed during a machine
operation. In order to suppress the noise interference and to enhance the energy of the characteristic

17th World Congress on Engineering Asset Management (WCEAM)
Ho Chi Minh City, Vietnam 18 –20 October 2023
Sustainable Management of Engineered Assets in a Post Covid-19 World: Industry 4.0, Digital Transformation, Society 5.0 and Beyond

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Paper No.

7016

Abstract
frequency component generated by a faulty part, a signal processing technique using a combination of
Maximum Correlation Kurtosis Deconvolution (MCKD) and Time-reassigned local maximum synchrosqueezing
transform (TLMSST) is proposed in this study. Under this approach, MCKD is applied first to improve the signalto-noise ratio (SNR) of a noisy signal. TLMSST is then employed to produce an energy concentrated timefrequency (TF) distribution of the characteristic defect signal components from the de-noised non-stationary
signal. The time interval between two successive frequency representations in the time frequency distribution
is then used to determine the characteristic defect frequency for bearing fault diagnosis. The effectiveness ofthe proposed technique is validated using a simulated impulse signal and an experimental bearing defect signal
acquired under varying speed condition. The result shows that the proposed technique can effectively extract
the fault features from a non-stationary signal contaminated by strong noise.
Title: An Efficient Predictive Analytics Framework
for Asset Management
With access to new data and technology, asset management has evolved, incorporating algorithms, machinelearning and artificial intelligence to analyze large volumes of asset data and identify trends that may not beapparent to human analysts relying on conventional technology. However, modern asset management focuses
more on sustainability and social responsibility, as investors seek to invest in assets that align with thesevalues. Therefore, these systems also emphasize sustainability and social responsibility, as well as optimizing
asset management practices. They are characterized by data-driven, technology-enabled, and socially
responsible investment strategies that maximize asset performance while reducing risks.
The chapter focuses on the need for contemporary asset managers to have exposure to AI-driven predictive
analytics solutions to address the challenges faced in their specialized industry. It explains how predictive
analytics models can control the three pillars of any asset or infrastructure- risk, cost, and performance- whilestaying in tune with asset management's financial and social responsibility elements. The authors explain how
asset custodians can utilize a Predictive Analytics Framework invented by Tigernix in various industries,
including water, wastewater, road, mechanical, reusable energy, community infrastructure etc.

17th World Congress on Engineering Asset Management (WCEAM)
Ho Chi Minh City, Vietnam 18 –20 October 2023
Sustainable Management of Engineered Assets in a Post Covid-19 World: Industry 4.0, Digital Transformation, Society 5.0 and Beyond

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017

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Understanding the full-scale implementation of IIoT and AI capabilities will guide the reader in comprehending
the actual outcome of using the Predictive Analytics Framework.
Title: Real-Time Monitoring and Analysing Environmental Conditions in The Workspace with IoT Components
and AWS Cloud Services
Ensuring a high-quality workplace is crucial in today's business world to enhance employee satisfaction andproductivity. To create a safe and comfortable working environment, it is essential to have noise detection andair quality control measures in place. However, relying solely on basic human senses and interactions to do so
may not be effective and could lead to exposure to toxicity before employees are aware of it. Therefore, in our
research, we aim to address the need for technological intervention in the monitoring and analysis of theenvironmental conditions in office spaces. The main goal of the research is to develop an efficient and userfriendly solution. To elaborate, the project creates an Internet of Things (IoT)ecosystem consisting of various
strategically placed sensors along with Arduino microcontrollers to collect data on environmental factors suchas indoor air quality, temperature, humidity, and noise levels. The data collected by the sensors are processedby the microcontrollers, before being sent to AWS Cloud Services for storage and visualization. The systemutilizes the secure and scalable infrastructure of the AWS Cloud Services, using Amazon Internet of Thing andAWS DynamoDB for connection and data storage respectively. The system also creates a website built byReactJS and NodeJS to display real-time data analysis and visualization through a user-friendly interface. Via
the website, users can also set thresholds for environmental factors and receive alerts when these thresholds
are exceeded. The system also integrates with other AWS services such as Amazon API Gateway, Amazon S3
and Amazon Cognito for website building, deployment, and user access control. In general, our project
proposes a practical and effective solution for monitoring and analyzing environmental conditions in theworkspace.

9

23

Title: Maintenance Process Improvement Model by Integrating LSS and PM Optimisation
In order to manage service adequately and improve the maintenance process, a guideline model is an
important tool that can be used to reach high performance. This paper proposes a new model for vehicle fleet

17th World Congress on Engineering Asset Management (WCEAM)
Ho Chi Minh City, Vietnam 18 –20 October 2023
Sustainable Management of Engineered Assets in a Post Covid-19 World: Industry 4.0, Digital Transformation, Society 5.0 and Beyond

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maintenance management that integrates LSS and PM optimization activities to improve maintenances
efficiency and effectiveness. This model bridges the service gaps between maintenance providers andcustomers and balances the requirements of maintenance managers, deliveries and customers by taking thebenefits of the Lean speed and the Six Sigma high quality principle, as well as the optimisation process balance.
Moreover, the TPM application within the Lean strategy which allows the organisations to develop advanced
techniques in maintenance analysis and to be more technical in its approach to problem solving inmaintenance. This combination can enhance the management performance of organisations, continuously
raise the efficiency and effectiveness of enterprise management, and improve service quality and reliability.

10

024

Title: Big data as assets: Risk management framework
The utilization of big data has become increasingly prevalent in various domains and is widely recognized as avaluable resource for many organizations. Despite its numerous benefits, the effective management of big data
involves addressing numerous challenges, including the potential risks associated with its collection, storage,
and processing. Despite the criticality of risk management in big data management, asignificant gap exists in terms of adequate attention and resources allocated to this aspect. This gap is primarily
due to the reliance on the expertise and experience of the data management team to manage the risk, which
often results in inconsistencies and inefficiencies.
To address this issue, this research paper proposes a unified framework for risk management in managing big
data. The framework is designed from the perspective of asset management, considering the value andsignificance of big data as a valuable organizational asset. This approach enables a comprehensive
understanding of the potential risks associated with big data management and facilitates the development ofeffective strategies for managing these risks.
Overall, this framework provides a structured and holistic approach to big data risk management, enablingorganizations to proactively address potential risks and mitigate their impact on organizational operations andperformance. By adopting this framework, organizations can enhance their big data management practices andmaximize the value and benefits derived from this valuable resource.

17th World Congress on Engineering Asset Management (WCEAM)
Ho Chi Minh City, Vietnam 18 –20 October 2023
Sustainable Management of Engineered Assets in a Post Covid-19 World: Industry 4.0, Digital Transformation, Society 5.0 and Beyond

BOOK of ABSTRACTSNo
11Paper No.
025

Abstract
Title: Dynamic RUL based CBM Scheduling. A Simulation Model for the Railway Sector.
This paper uses a System Dynamics model to analyze the maintenance scheduling problem of a fleet of assetsthat is subjected to a CBM (Condition-Based Maintenance) program for critical components under amaintenance 4.0 environment.
The paper explores the implications of different CBM capacity levels modelling a cost function. Cost function
factors considered are cost of lost RUL, cost of CBM capacity, cost of overdue CBM and cost of asset
unavailability due to overdue CBM. Empirically, the paper shows how capacity can be optimized to minimize
this cost function. Once all different possibilities to schedule CBM activities are modeled, together with thecost of the selected CBM strategy, the paper compare results with those obtained for a base case where theorganization could detect anomalies in components but not schedule CBM activities according to their RUL
limitations and the maintenance organization capacity constraints. The paper demonstrates the different
benefits of this opportunistic CBM task scheduling, according to assets stops for their predetermined PM
activities. The tool that is developed has been tested in the railway sector, for a fleet of trains. Interesting
results are obtained for different strategies, and they are discussed to understand possible implications ofchanges in the different factors and parameters of the problem.

12

026

Title: Digital Twin Models in CBM Apps. Functionality
Description & Features Analysis.
The goal of digital twins (DT) is to replicate physical equipment and systems in the digital world by effectively
integrating data, models, and decision support systems, promising a step change in productivity andsustainable performance.
Despite recent developments in DT solutions, several issues remain to be addressed before the benefits of thistechnology for maintenance can be realized. For example, it is necessary to generate a better conceptual basis,
to facilitate the functional description of the applications, etc. This paper contributes to explain, in a practicalway, the functionality and structure of these applications within digital configurations for maintenancemanagement. It proposes a generic framework for the functional description of a DT designed for intelligent
maintenance and, in addition, lists a series of characteristics that must be fulfilled when developing these17th World Congress on Engineering Asset Management (WCEAM)
Ho Chi Minh City, Vietnam 18 –20 October 2023
Sustainable Management of Engineered Assets in a Post Covid-19 World: Industry 4.0, Digital Transformation, Society 5.0 and Beyond

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13

027

14

030

Abstract
tools, according to the relevant scientific literature. This article is an excerpt from different contributions of theauthors on this topic.
Title: Blockchain technology adoption and the sustainability of smallholder farmer’s agri-food production
under climate change
Climate change is causing the risk of crop yield uncertainties and adversely affecting the livelihood welfare
improvement of smallholder farmers. The main objective of this study is to explore how blockchain technology
adoption can enhance the resilience of smallholder farmers’ agri-food production under climate change, andhow smallholder farmers should work collectively with wholesalers and policymakers to achieve livelihood
welfare improvement through blockchain technology adoption. A thorough review of historical developments
and existing integration trends among facilitators and barriers that can influence smallholder farmers’
behavioural intentions to adopt blockchain technology along with future research directions outlined in themain literature was conducted. We also propose the sustainable system-of-systems (SSoS) approach toillustrate how smallholder farmers can work collectively with wholesalers and policymakers to achieve
livelihood welfare improvement, in terms of social, economic, and natural capital, through blockchain
technology adoption. This work establishes a knowledge base on research topics, issues of integration andsynergies with a concentration on the potential for blockchain technology adoption to the sustainability ofsmallholder farmer’s agri-food production under climate change.
Title: Setting the decision-making framework for municipal asset management
Asset management by municipalities is characterized by a large variety of assets serving the needs of manydifferent stakeholders. Given that the stakeholders may have conflicting values, asset management is not only
balancing costs, perfor-mance and risk but also balancing different stakeholder needs. This increased complexity is further enhanced by the limited space in an urban environment, notwith-standing the competition
for resources with non-asset departments. To deal with these challenges, many municipalities use a form ofcompartmentalization, limiting the scope of decisions. However, any compartmentalization introduces
inefficien-cies and may even result in net destruction of value because of missed interests. A way to addressthese challenges is to have a uniform decision making framework based on a broad view on stakeholders

17th World Congress on Engineering Asset Management (WCEAM)
Ho Chi Minh City, Vietnam 18 –20 October 2023
Sustainable Management of Engineered Assets in a Post Covid-19 World: Industry 4.0, Digital Transformation, Society 5.0 and Beyond

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15

031

16

035

Abstract
interest. In this paper we describe the ap-proach that was followed by the city of Rotterdam including theresults. Starting point in this approach were active policy documents. These were translated into a set of
guiding principles and a value framework using state of art insights. The re-sults were validated within theasset management organization with hands-on pilots on actual cases. Key elements in the approach werecommunication and collabora-tion with the entire organization and its partners. Given the encounteredenthusiasm Rotterdam is now planning the large scale rollout of this new framework.
Title: Determination of the exact economic time for the component replacement using condition-based
maintenanceIn most industrial assets, determining the preventive interval is a task carried out by the maintenanceengineer. In non-critical assets, the optimization process of the interval must consider the costs of operationand maintenance, as well as the income generated by its operation. The result is the economic determination
optimal moment to perform preventive intervention (PM). Mathematically, an expression can be found that
relates these variables to the failure occurrence process.
However, when the equipment is critical to the business, it is necessary to avoid the occurrence of failure. For
this purpose, investment is made in techniques that determine asset degradation (CBM). In this case, not only
must the failure occurrence process be controlled, but the degradation of the asset must also be analyzed. To
determine the economically optimal moment for the preventive replacement of a component subject to CBM,a semi-Markovian model has been developed. The model considers degradation as a Wiener process andintegrates it with the failure occurrence process, adjusted to a Weibull distribution. The result is twomathematical formulas to determine the interval for preventive replacement, optimizing costs, income,degradation and failure distribution, and the optimal degradation threshold.
Title: Machine learning model for predictive maintenance of modern manufacturing assets
Predictive maintenance is considered a powerful practice for manufacturing assets, facilitating theidentification of potential failure occurrences. By proactively addressing such failures, manufacturers can avoid
unplanned downtime and allocate necessary resources for required maintenance activities. Machine Learning(ML) methods have emerged as a promising tool for preventing equipment failures in Predictive Maintenance17th World Congress on Engineering Asset Management (WCEAM)
Ho Chi Minh City, Vietnam 18 –20 October 2023
Sustainable Management of Engineered Assets in a Post Covid-19 World: Industry 4.0, Digital Transformation, Society 5.0 and Beyond

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038

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applications. However, the effectiveness of Predictive Maintenance applications is largely determined by the
Machine Learning techniques utilized. In this research, we adapted the cross-industry standard process fordata mining to develop a predictive maintenance model for a unique, large, and complex manufacturing asset,
utilizing various machine learning techniques. Specifically, we applied Random Forest, Support Vector
Machines, K-Nearest Neighbors, extreme Gradient Boost, and Logistic Regression algorithms to the asset
failure records. Following the fitting of all models, Random Forest emerged as the best-performing model
based on the recall parameter. Additionally, an exploratory data analysis process was conducted on the data toderive insights into the failure pattern of the machine.
Title: Modelling Traffic Conditions in Developing Urban Areas: A Combined Approach of Explainable Artificial
Intelligence and Mobile Crowdsourcing
Traffic congestion remains a persistent and challenging issue in major urban centers, particularly in developing
countries where transportation infrastructure struggles to keep pace with rapidly growing demand. This paper
proposes innovative solutions to address this issue by introducing mobile crowd-sourcing based approaches for
traffic condition estimation. Scalable framework is outlined for the efficient collection, integration, and analysisof traffic-related data contributed by mobile crowds. Furthermore, the paper addresses critical issues related
to reliably predicting traffic conditions where prediction interpretation is unavailable, utilizing an machinelearning model backed by Explainable Artificial Intelligence. By leveraging the explain ability of the model,
valuable insights can be extracted to enhance traffic conditions and improve overall social welfare.
Title: Compressive and Shear Loading Test for aConcrete Cylinder with Concrete Joint
Concrete must be placed at a site within the time interval prescribed in the code, so that several batches ofconcrete must be integrated after hardened. However, a defect of the concrete joint, what we called, “Coldjoint” could beoccurred. When the condition that is better than cold join, for example, a combination of amuch smaller gap and color difference would be observed, the judge to repair would be complicated, because
of insufficient test data.

17th World Congress on Engineering Asset Management (WCEAM)
Ho Chi Minh City, Vietnam 18 –20 October 2023
Sustainable Management of Engineered Assets in a Post Covid-19 World: Industry 4.0, Digital Transformation, Society 5.0 and Beyond

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In this paper, to evaluate the material strength with concrete joint, 64 pieces of concrete cylinder specimen
with time interval of zero to three hour were made and compressive and shear loading test was performed.
Test results were examined and reached several conclusions.
We examined the test data of the compressive, shear and frictional stress. They were decreased following
increasing of the time interval of the concrete placement. However, the shear stress was 1.12 times of theshort term of allowable shear stress in all specimen. On the other hand, the average load was decreased to
88% from 0.5 to 3.0 of T. Therefore, the loading test should be performed when the concrete joint wasobserved.

19041

Title: Unlocking the potential of Construction 4.0 for Asset Management: factors for success in Ca Mau andTra Vinh provinces, Vietnam
This study seeks to evaluate the feasibility of using Construction 4.0 (C4.0) technologies for asset management
in a developing context, with a particular focus on the Vietnamese provinces of Ca Mau and Tra Vinh. The
research employed the Fuzzy Delphi methodology and gathered data from construction experts, includ-ing
government officials, consultants, contractors, and clients.
The findings indicate that using C4.0 technology to manage buildings and infra-structure has the potential tocontribute to facility management and sustainable de-velopment in developing nations such as Vietnam. The
study proposes a framework and highlights critical success factors, such as collaboration, data sharing,
operation planning, support software, and project member participation for C4.0 adoption. This study has
significance for policymakers, industry experts, and academic re-searchers working towards applying digitaltechnologies for asset management in developing countries.

20

042

Title: Digital Transformation for Construction Facility Management in Developing Countries: A review of BIM
applications
This review article provides insights on utilizing digital technologies to manage facilities in developing
countries. Through the adoption of digital models, the construction owners can gain key benefits such as

17th World Congress on Engineering Asset Management (WCEAM)
Ho Chi Minh City, Vietnam 18 –20 October 2023
Sustainable Management of Engineered Assets in a Post Covid-19 World: Industry 4.0, Digital Transformation, Society 5.0 and Beyond

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043

Abstract
better facility operation and maintenance, better collaboration, enhanced safety and security, and effective
space management.
Despite the potential benefits, the review also identifies significant challenges to the adoption of digital models
in developing countries, including the lack of skilled personnel, infrastructure, and governmental support.
These challenges have hin-dered not only the widespread diffusion of digital tools, but also facility management practices in construction. The review contributes to the literature on digital transformation inconstruction by providing an overview of Building Information Modelling for facility management in developing
countries.
Title: Understanding Opinions and Emotion s of Generative Artificial Intelligence Assets using the Gartner
Hype Cycle and KKübler Ross Change Curve
Asset management today encompasses not just on-premises properties but also cloud services. Companies
have been adopting software services like Office 365 or Google Apps and managing them as assets for over a
decade. Adopting those services into their businesses often required time, both technically and manageriallyand psychologically. It is well known that for digital transformation projects to be successful, organizations andtheir workers must be ready in advance. It is now the age of Generative Artificial Intelligence (AI) services suchas ChatGPT, Bing AI, and Microsoft Office Copilot. Understanding the opinions and emotions about such assets
in organizations will aid in the consolidation of our theories of technology acceptance and will guide businesses
in their technology adoption. Based on Gartner Hype Cycle and Kübler-Ross Change Curve, this study
hypothesises that the process of adopting generative AI services into organisations will go through stages oftechnology trigger, the peak of inflated expectations, the trough of disillusionment, the slope ofenlightenment, and the plateau of productivity, while at the same time passing through the feeling of shock,denial, frustration, depression, experiment, decision and integration. Using the sentiment and emotion
analysis approach, this study collected a significant number of tweets from Twitter, and then quantize theircontents into sentiment scores and emotions to assess these hypotheses. Prior research has shown the binary
sentiment landscape at a single point in time but not the range of sentimental scores and multilevel emotions

17th World Congress on Engineering Asset Management (WCEAM)
Ho Chi Minh City, Vietnam 18 –20 October 2023
Sustainable Management of Engineered Assets in a Post Covid-19 World: Industry 4.0, Digital Transformation, Society 5.0 and Beyond

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over some time, and consequently could not demonstrate the complete process of hyping and adopting as
envisioned by the Gartner Hype Cycle and Kübler-Ross Change Curve. Additionally, previous research examined
the adoption of new technology from the perspective of information seekers, but not from the perspective of
information creators. Furthermore, because generative AI services have just recently been released for publicuse, there is still a gap in our knowledge of their receptive and adaptive responses. Theoretically, this study
contributed to the empirical confirmation of the Gartner Hype Cycle and Kübler-Ross Change Curve in
implementing generative AI services. In practice, it aids organizations in the process of planning theimplementation of new generative AI assets together with their managerial and psychological training toincrease company-wide productivity.

22

044

Title: Battery Refurbishment Technologies in the World: A Review
The increasing demand for batteries in various industries has resulted in the problem of battery waste. An
industry 4.0 will need to tackle this kind of envi-ronmental problem. With the need for a more sustainable
solution, battery refur-bishment technologies have emerged as a way to reduce the environmental impact ofbattery waste, conserve resources, and save costs. In this review, we will discuss the existing battery
refurbishment technologies in the world, including their ad-vantages and disadvantages.

046

Transformer architecture for botnet detection
Botnets, networks of compromised computers controlled by malicious actors, pose a significant threat to
cybersecurity. Traditional signature-based methods for botnet detection are effective for known botnets but
struggle to identify new and evolving threats. Machine learning based approaches have been proposed toaddress this limitation; however, they often require manual feature engineering and may fail to capturecomplex patterns of botnet behavior. In this paper, we propose a novel approach for botnet detection basedon the transformer architecture, which has achieved state-of-the-art performance in natural language
processing tasks. Our transformer-based model processes raw network traffic data and automatically learns
meaningful representations for botnet detection, eliminating the need for manual feature engineering. We
conduct extensive experiments on real-world network traffic datasets, demonstrating the effectiveness of our23

17th World Congress on Engineering Asset Management (WCEAM)
Ho Chi Minh City, Vietnam 18 –20 October 2023
Sustainable Management of Engineered Assets in a Post Covid-19 World: Industry 4.0, Digital Transformation, Society 5.0 and Beyond

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approach in accurately detecting various types of botnets, including previously unknown threats. Our approach
outperforms baseline methods and exhibits robustness to adversarial evasion techniques. The proposedtransformer-based model represents a significant advancement in the field of botnet detection and has thepotential to enhance the security of networks against evolving cyber threats.
Keywords: botnet · cybersecurity · transformer
PREDICTING OPTIMISATION OPPORTUNITIES FOR CLINICAL SPACE UTILISATION
Can machine learning be used to predict optimisation opportunities for clinicalspace utilisation? This research seeks to demonstrate the capacity of machine learning on 2.78 million clinicaloccupancy data points to support future optimisation of clinical space utilisation. Increasing clinical space
utilisation leads to reduced infrastructure expansion and/or reconfiguration. Previous research demonstrated
the capacity of Internet of Things (IoT) technology to identify low historic occupancy periods; future utilisation
prediction remained a challenge. Machine learning algorithms are applied to 24 months of historical occupancy
data previously gathered by privacy-preserving IoT devices in a live public-healthcare environment. Predicteddata was visualised via. graphical interface, and user-manipulated through time and location filters. Preliminary
results demonstrate the capacity for machine learning to identify future optimisation opportunities for clinicalspace utilisation, achieving accuracies of 82% using a ‘K Nearest Neighbours’ algorithm. The resultant datadashboard combined human experience/intuition with model predictions supporting dynamic exploration of
future clinical occupation patterns. Previous research demonstrated the capacity of IoT devices to support
identification of historic occupancy gaps. This research demonstrates improved capacity for resource planningto improve consumer experience, reduce reliance on more intensive/expensive downstream services, andlower healthcare costs.
Application of Industry 4.0 technological advancements in teleoperation of industrial robots
Technology development in Industry 4.0 era results in a progressive inte-gration of robotic systems into
manufacturing processes. This study implements the advancements in industrial automation, Internet ofThings (IoT), and Virtual Reality (VR) to develop an approach for real-time teleoperation of industrial robots in
re-mote working environment where human access is limited. The proposed frame-work addresses the current

17th World Congress on Engineering Asset Management (WCEAM)
Ho Chi Minh City, Vietnam 18 –20 October 2023
Sustainable Management of Engineered Assets in a Post Covid-19 World: Industry 4.0, Digital Transformation, Society 5.0 and Beyond

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challenges in robot’s posture perception by presenting the potential of VR to enhance the user's spatialawareness and intuition of control-ling robots. The real-time robot control is conducted by tracking user handmove-ment via VR controllers and the feedback signal from the robot is recorded for sys-tem monitoring. In
addition, the intermediary cloud server is utilised for data transfer between stations via the Internet. The
practical experiments with an indus-trial robot are conducted and investigated to verify the system
performance. The proposed system is to be implemented in supporting engineering technicians to ef-fectively
monitor and manage robots in the automation line.
Keywords: Robotics, Virtual reality, Teleoperation.
Lessons learnt from building an Enterprise Resource Planning (ERP) system using serverless cloudarchitectureThis paper presents findings from a case of building a large-scale enterprise resource planning system using
serverless cloud services. It is suggested that serverless could be a solution to overcome the innovation andresource shortage challenges faced by small technology start-ups. Serverless provided these firms with aflexible, scalable, and cost-effective infrastructure that leverages cloud computing technologies. By adopting aserverless design, start-ups can focus on developing their core business applications, rather than worrying
about the underlying infrastructure. Findings from this study provides lessons for small start-ups to optimize
their resources and minimize costs, while still achieving high levels of scalability and performance. The paper
also highlights the benefits of the serverless design and provides practical examples of how it can be
implemented in small tech start-ups.

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Smart camera for asset management: a novel hybrid solution of edge and cloud computingThis paper presents a novel approach for asset management using a smart camera system that utilizes bothedge and cloud computing. The proposed system is designed to monitor and track assets in real-time,
providing valuable insights into their status and location. By combining the processing power of edge

17th World Congress on Engineering Asset Management (WCEAM)
Ho Chi Minh City, Vietnam 18 –20 October 2023
Sustainable Management of Engineered Assets in a Post Covid-19 World: Industry 4.0, Digital Transformation, Society 5.0 and Beyond

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Abstract
computing with the scalability of cloud computing, the system can handle large amounts of data while still
providing low latency responses. The smart camera system can be used in a variety of applications such as
logistics, manufacturing, and retail, where real-time tracking and management of assets is critical for
operational efficiency.
The results of the study demonstrate the effectiveness of the proposed system in improving asset
management and reducing operational costs.
A Comparative Study Regarding Information Quality of Data Acquisition Methods for Gravel Road Condition
Measurement
Gravel roads connect rural areas to urban centres, providing essential access for residents and entrepreneurs.
Maintaining these roads at an acceptable level of service is cru-cial for improved ride quality and efficient andsafe transportation of goods and services. They have a high deterioration rate compared to paved roads.
Currently, visual windshield inspections are the primary approach to evaluate the state of gravel roads byconducting, but they are unreliable and susceptible to human judgement errors. Technological advancements,
particularly sensor technology, have presented opportunities for improved condition moni-toring and datacollection for gravel roads. However, the quality of information varies for various available technologies,
consequently affecting the condition assessment results. For effective decision-making, high-quality
information is required. This paper investigates and compares the information quality of the data collectedusing smartphone sensors and an In-tegrated Circuit Piezoelectric (ICP) accelerometer from three gravel roads.
The empirical analysis is based on the hypothesis that the quality of information from the smartphone and ICP
sensors are comparable. Statistical properties and the instantaneous power for eight (8) frequency bands ofthe data from the Smartphone and ICP (resampled) sensors for RT1, RT2 and RT3 were compared. The power
spectral density (PSD) was also compared. The results from the ICP sensor yield higher-quality information thansmartphone sensors and can be complemented by video recordings and visual windshield inspections forbetter maintenance decision-making. Assessing the condition of gravel roads using methods that offer highqual-ity information is vital to efficient decision-making and is achieved by using objective and automated dataacquisition methods based on sensor technology.

17th World Congress on Engineering Asset Management (WCEAM)
Ho Chi Minh City, Vietnam 18 –20 October 2023
Sustainable Management of Engineered Assets in a Post Covid-19 World: Industry 4.0, Digital Transformation, Society 5.0 and Beyond

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63

Abstract
Developing New Method for Optimizing the Maintenance Strategy of Electrical Mobile Working Machines
And Reduce Operating And Maintenance Costs, using Markov Decision Process
Abstract
As a way to contribute to resolving the current climate issues, automobile industries invest heavily in thedevelopment of electrical working machines (loaders, drilling and bolting rigs and haul trucks). A key aspect ofthese new technologies that should be addressed is their maintenance management, as the existing
maintenance models are mainly focused on fuel engine driving machines. As a result, it is necessary to develop
a maintenance strategy to optimize availability of heavy electrical working machines and reduce operating andmaintenance costs.
After examining the existing maintenance strategies and maintenance planning for fuel engines, this paper
presents a new maintenance method that optimizes the maintenance strategies of electrical mobile working
machines using Markov decision processes. Based on the machine’s condition and the maintenance costs, an
optimal cost-effective maintenance policy is determined, which includes the appropriate maintenance action
to be taken. A Markov Decision Process is applied to the study using MATLAB and Maple V.
Keywords: heavy electrical working machines, availability, maintenance costs, operating costs

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Topics: Asset and maintenance complexity: predictive maintenance solutions used by airports around theworld and some suggestions for the Vietnamese Airports
The day-to-day airside and landside operations are complex with more than thou- sands individual assets,
multiple siloed maintenance and inventory systems, work- flows dating back sometime up to 1980, and dozens
of contractors working onsite. As such, the airport’s manual processes lead to costly and frustrating
communica- tions challenges—and issues often left unresolved. Asset management solutions tai- lored for
airports that include analytics can provide an integrated approach to man- aging all discrete or complex assets

17th World Congress on Engineering Asset Management (WCEAM)
Ho Chi Minh City, Vietnam 18 –20 October 2023
Sustainable Management of Engineered Assets in a Post Covid-19 World: Industry 4.0, Digital Transformation, Society 5.0 and Beyond

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067

Abstractin the airport inventory. They can help overcome challenges rooted in aging infrastructures or insufficienthuman assets and bring unity to the typical airport’s siloed or disconnected systems.
Predicting the impacts on civil infrastructure over decades is challenging — and 45% of all maintenance efforts
are ineffective. Assets are constantly moving and exposed to nonstop usage as well as ever-changing
conditions. Because materials react differently to different stimulus over time, the condition of an asset today
will not reflect the condition in a month, a year, or ten years from now.
Framework for mapping activities in desalination plant for sustainable maintenance
Seawater desalination plants are complex facilities that require careful management and maintenance toensure that they operate efficiently and reliably over their lifespan. Desalination equipment can suffer fromvarious failures that can impact
the efficiency and productivity of the plant. Some of the most common failures include: corrosion, mechanicalfailures, electrical failures and biological growth. The latter is very specific for this type of system. Biological
growth, such as algae orbacteria, can occur in the intake system, pipes, and other equipment. This can reduce flow rates, increaseenergy consumption, and cause fouling and corrosion. From a sustainability perspective, there are several
concerns associated with the operations and maintenance of desalination plants, including: energy
consumption, water consumption (While desalination provides a reliable source of drinking water,
it also requires a significant amount of seawater for the process and this can have negative impacts on marine
ecosystems), chemical use (Desalination may require the use of chemicals such as chlorine to maintain thequality and efficiency of theprocess. These chemicals can have negative environmental impacts if not properly managed, including impacts
on aquatic life and ecosystems). From a methodological point of view, the paper will apply methodologies toimprove the maintenance management to obtain better performances in terms of operations efficiency and17th World Congress on Engineering Asset Management (WCEAM)
Ho Chi Minh City, Vietnam 18 –20 October 2023
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075

Abstractsustainability. Maintenance models theory is accordingly applied in order to identify the main issues relatedwith this specific business and type of technical systems.
Simulating and optimizing the standard tending station with ABB robots

076

Machine tending station is a recent trend in manufacturing, especially in the era of Industry 4.0. The adoptionof an automatic feeding station is crucial for advancement and innovation in the industry and making asignificant progress in manufacturing and automation industry. In this paper, we aim to simulate and optimize
a machine tending station for milling mechanical parts that will be implemented into main systems. This
station will improve the workflow efficiency and accuracy to prevent errors and hazardous injuries. The
communication between stations will be manipulated by the Omicron controller through a control cabinet. The
workflow will be controlled by RAPID code through RobotStudio. Furthermore, sensors will be utilized for
detecting different shapes of parts for the robot to have appropriate
grabbing extensions motion for pick and place tasks.
Supply Chain Quality Management 4.0 Frameworks: A Case Study in the Health Care Industry

33

Research focusing on the integration of three concepts, which are Industries 4.0, Quality Management, andSupply Chain Management – SCQM4.0 (Supply Chain Quality Management 4.0) to evaluate the impact ofIndustries 4.0 on the supply chain quality management, has been an emerging area among
academics and industry practitioners. The literature identified various benefits of the integration including cost
reduction, increased supply chain performance, and improved customer satisfaction. However, it is still unclear
for firms to assess their maturity level in implementing SCQM4.0. Managing SCQM4.0 competences enablefirms to gain competitive advantages in supply chain operations and performance. This paper provides an
overview of SCQM4.0 concept and proposes a maturity framework for SCQM4.0 based on four constructs
including supply chain performance, supply chain operations, disruptive technologies, and infrastructure
practices. The proposed SCQM4.0 framework identifies four maturity stages of Incidental, Intentional,
Integrated, and Optimized. Our SCQM4.0 framework is then evaluated in a a medical device manufacturer in
Vietnam. Key findings and discussion are provided.

17th World Congress on Engineering Asset Management (WCEAM)
Ho Chi Minh City, Vietnam 18 –20 October 2023
Sustainable Management of Engineered Assets in a Post Covid-19 World: Industry 4.0, Digital Transformation, Society 5.0 and Beyond

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077

Analysis of interrelated distress types using Naïve Bayes method for provincial highway network in Pakistan

080

Highways play a vital role in regional development. However, due to the focus of road authorities in thesecountries on the construction of new highways, the existing highways are left unattended. Small distresses thatdevelop on these roads after short periods and can be remedied relatively cheaper are left to convert into
more complex types that cost more to repair. An understanding of how these distresses evolve would be
useful for scheduling maintenance activities and reducing maintenance costs. In this research, the probabilityof occurrence of a particular distress type due to the other distress types with time was studied by using aprobabilistic algorithm known as Bayes classifier. The study was conducted by analyzing data from theprovincial highway network of Khyber Pakhtunkhwa province of Pakistan. Data on 12 types of distresses that
occurred in pavement aged up to 7 years were utilized in the study. The results of the study showed theprobability of occurrence of severe distress types like block cracks increased due to delay in treatment of lesssevere distress types like edge cutting, alligator cracks, potholes and transverse cracks highlighting the needfor preventive maintenance.
Evaluation of Project Performance and Sustainability in the Nepal Road Infrastructure Sector

35

Abstract

Infrastructure construction considering environmental and social aspects supports sustainable development.
However, the implementation of mitigation measures is often neglected. This may affect the performance of a
project, as well as the sustainability of the infrastructure. This research examines the environmental and social
aspects considered in road infrastructure projects in Nepal and their effect on project performance. The dataof road and bridge construction contracts are analyzed to evaluate the time and cost performance of projects
in relation to environmental and social considerations. The comparative study of projects financed by theGovernment of Nepal (GoN) and foreign financing institutions was performed using descriptive statistics andthe Mann-Whitney U test considering the non-normal distribution of data. The results showed thatinternational financing institution-supported projects have more robust institutional, governance, andresource management with proper environmental and social consideration. Finally, this research suggests the17th World Congress on Engineering Asset Management (WCEAM)
Ho Chi Minh City, Vietnam 18 –20 October 2023
Sustainable Management of Engineered Assets in a Post Covid-19 World: Industry 4.0, Digital Transformation, Society 5.0 and Beyond

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use of proper institutions, governance mechanisms, and resource management to improve performanceachieving sustainability.

36

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Assessing the transferability of the Highway Safety Manual crash prediction model in the context of themountainous rural two-lane highway of Nepal
Road safety management focuses on mitigating the occurrence of crashes by building safer roads, and crashprediction is one effective technique for achieving this goal. The crash prediction methodology developed by
AASHTO and explained in the Highway Safety Manual (HSM) is the most common model among roadmanagement authorities and researchers. The manual provides calibration techniques to make the model
flexible and applicable for roads that differ from the base conditions. However, the transferability of the HSM
crash prediction model needs to be assessed before using it for real-life crash estimations. The objective of thisstudy is to assess the transferability of the HSM crash model in the case of a mountainous two-lane rural
highway in Nepal. Through this study, two major issues were identified in the HSM model: 1) the homogenous
segmentation approach would lead to the formation of numerous short road segments with zero crashes andthus would be unpragmatic to consider, and 2) the function for crash modification factor for horizontal curves
contributes to overpredicting road crashes because of curves with a smaller radius and shorter lengths. Thisshows that special considerations are required for applying the HSM to mountainous roads.

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082

FUNDAMENTAL STUDY ON THE OVER TORQUE TEST METHOD TO ASSESS THE CONCRETE STRENGTH
In this study, we developed the over torque test method with a small drill. The method is independent of theworn condition of the drill edge and the drilling pressure. In the method, at first, a small guide hole is drilled.
Secondary, a small concrete screw is driven while measuring the torque. Finally, the concrete strength isassessed compared with the concrete strength and the torque property relationship.
A lot of the over torque test were performed while measuring the torque and the test results were examined.
The torque was sharply increased at the start screw-in Next, the torque is kept while driving drill to some

17th World Congress on Engineering Asset Management (WCEAM)
Ho Chi Minh City, Vietnam 18 –20 October 2023
Sustainable Management of Engineered Assets in a Post Covid-19 World: Industry 4.0, Digital Transformation, Society 5.0 and Beyond

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extent. Finally, the torque was sharply dropped down with the over torque. Just a drilled small hole was left asdamage.
The relationship between the concrete strength and torque property was shown and we confirmed that theover torque test method could be highly valuable to assess the concrete strength.

38

084

SMART SYSTEM OF OBSERVATION AND MONITORING IN SHRIMP AQUACULTURE MANAGEMENT USING THE
INTERNET OF THINGS (IOT)This paper investigates to analyze, design, and fabricate a smart monitoring and observing system inaquaculture management via using LoRa and IoT technology. In the paper, recent developments of theautomatic monitoring and observing technology in aquaculture in Vietnam is presented and analyzed. Firstly, asolution is proposed to improve life span of measurement devices of water quality. Conceptual design of asmart system of monitoring and observing system is generated via an integration of smart DO measurement
system, feeding machine, waterwheel and other related components via Lora, internet of things (IoT), andautomation technology. In addition, machine learning algorithm is used in the integrated control system, inwhich water parameters are automatically monitoring basing on environmental conditions. fabricated systemand experimental testing are deployed to validate the proposed solution.

39

088

PAPER: “SOLVING THE EXAMINATION TIMETABLING PROBLEM USING A HYBRID EVOLUTIONARY
ALGORITHM”
Designing a feasible examination timetable for universities is a complex task that involves numerous practicalconstraints. This problem is particularly challenging in universities in Vietnam, where there is often a shortageof facilities such as classrooms and laboratory sessions. The efficient use of resources is crucial whenscheduling examinations. In this study, a novel approach to solve the examination timetabling problem using ameta-heuristic that combines Particle Swarm Optimization (PSO) and Grey Wolf Optimizer (GWO) is proposed.
This method has not been previously applied to this problem and is evaluated using a small case study and17th World Congress on Engineering Asset Management (WCEAM)
Ho Chi Minh City, Vietnam 18 –20 October 2023
Sustainable Management of Engineered Assets in a Post Covid-19 World: Industry 4.0, Digital Transformation, Society 5.0 and Beyond

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compared to IBM-CPLEX solutions. Additionally, a multi-search method is incorporated to improve theapproach's search capability. The proposed approach delivers reasonable results even for large-scale studies,such as in the case of the International University, where it solved a problem with over 400 exams, while IBMCPLEX could not find an appropriate solution.
ICT for sustainable development: Designing a Smart IoT platform for online water quality monitoring

092

Water quality monitoring is crucial in protecting the environment. However, most of water quality monitoring
systems in Vietnam are manual, time-consuming, and require well-trained personnel. Some systems utilize
specialized components imported from abroad, which drives up the cost and make them expensive tomaintain. In this paper, we present a design and implementationof an online water quality monitoring system that is cost-effective and easy to maintain using readily available
components in Vietnam. The system consists of one or more sensor units collecting water parameters like pH,
temperature…
etc. Those data are then transmitted wirelessly to a central unit for monitoring and data analysis when needed
later. The result of the study shows that the designed system performs adequately in measuring water quality.
Furthermore, to evaluate its accuracy and reliability, the system is submitted to inspection
authority and subsequently certified.
Digital Transformation in Transportation Management System: Challenges for Vietnam Businesses

41

Abstract.
Digital transformation is a journey with multiple connected interme-diary ends, in the long run, striving
towards constant improvement across opera-tions, divisions, and systems in the hyper-connected era bybuilding the right bridges between the front end and back end for all stakeholders within organizations toparticipate in. In this present era of the Fourth Industrial Revolution, digital trans-formation has emerged as asignificant phenomenon in economic development. Pri-vate and public organizations around the world striketo adopt technology applica-tions and their impact on managing and developing activities to drive better17th World Congress on Engineering Asset Management (WCEAM)
Ho Chi Minh City, Vietnam 18 –20 October 2023
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performance efficiency. The adoption of digital transformation plays an important role in firms having
competitive advantages in the market by increasing productiv-ity and providing a better customer experience,
which leads to growth opportunities.
In Vietnam, a developing country in Asia, the adoption of digital transformation in transportation management
systems has gained significant attention. This re-search examines the challenges faced by Vietnam businesses
in their pursuit of dig-ital transformation in the transportation management system. The study draws uponreliable data and statistics to provide an in-depth analysis of the current landscape. In the logistics sector,
while each step in the traditional supply chain is responsible for a specific function, the End to End (E2E) supply
chain introduces a more inter-connected process. This approach encompasses a comprehensive workflow thatstarts with product design and the procurement of raw materials, extends through scheduling, production, andconcludes with the final delivery of the finished product to the customer. By adopting the E2E supply chain
model, organizations aim to achieve greater efficiency and integration throughout the entire logistical journey,
ensuring a more cohesive and streamlined process from start to finish.
By addressing the challenges, stakeholders in Vietnam's transportation industry can navigate the complexities
of digital transformation and develop effective strategies for successful implementation as well as takeadvantage of potential opportunities.

42

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Vietbank – A successful digital transformation case in Engineering Asset Management
This paper investigates the successful transformation of Viet Nam Thuong Tin Commercial Joint Stock Bank
(Vietbank) from intensive labour management procedure of investment, operation, maintenance and retirement
for engineering assets to highly automation via digital transformation. The research was conducted with thesupport from Vietbank’s internal documentations, procedures and interviews with team of senior information
technology (IT) infrastructure personnel. Vietbank had successfully achieved great saving in term of operation
efficiency, human resources and financial after applying digital transformation. Their successful case can be used

17th World Congress on Engineering Asset Management (WCEAM)
Ho Chi Minh City, Vietnam 18 –20 October 2023
Sustainable Management of Engineered Assets in a Post Covid-19 World: Industry 4.0, Digital Transformation, Society 5.0 and Beyond

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097

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as a framework for other similar size of operation banks to base on in their digital transformation process inengineering assets management.
Risk-based inspection plan: a case study in a loading tanker truck system of chemical company

101

The proposed work is carried out in a chemical company of Chile, which processes and distributes chemical
products as raw materials industries throughout the country. A new loading system was built to improve the
distribution processes of the company, which consists of piping networks divided into 19 circuits. To optimize
the maintenance strategies for the piping networks, a risk-based inspection plan was proposed. The API
580/581(standard of American Petroleum Institute) methodology was chosen to quantify the probability andconsequences of an event occurring, as it is a quantitative methodology created for the petrochemical industry
context. The operational context and technical information of the system were identified, and the baseline risk
was evaluated. Therefore, an inspection plan was carried out according to standard, which includes the minimum
requirements for maintaining the mechanical integrity of the system. Finally, a proposal was developed for aninspection plan based on thickness measurement using UT. It identifies the points to be measured in each of thecircuits and their position, according to the consolidation of information in field and management spreadsheets,
taking into account the company's considerations. The proposed inspection plan aims to reduce the occurrenceof any events and ensure that the distribution processes are carried out safely and efficiently.
A novel method for gearbox fault diagnosis based on shift-invariant and shared dictionary learning

44

Gearbox fault diagnosis is a very crucial part in the field of mechanical diagnosis, and many methods areproposed to solve this problem. Either way, the core idea of fault diagnosis is to extract the class-specific featuresfrom the signals collected by different sensors. Although different types of faults own different class-specificfeatures, they also generally possess common features, and it’s essential to eliminate them for highlighting theclass-specific features. Especially for gearboxes, there are many complex components in the vibration signals,
where many features may belong to more than one fault class, so analyzing and removing these common
features before feature extraction is a quite significant process for a more efficient diagnosis. However, atpresent, few articles are proposed to solve the problem of common features. Inspired by a shared idea, we17th World Congress on Engineering Asset Management (WCEAM)
Ho Chi Minh City, Vietnam 18 –20 October 2023
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Abstract
proposed a novel fault diagnosis method named shift-invariant and shared dictionary learning (SISDL), which
consists of shared dictionary and diagnostic dictionary with shift-invariant. The shared dictionary is responsible
for learning the common features from different fault classes. Meanwhile, the diagnostic dictionary is
responsible for learning the class-specific features. Besides, a feature extraction scheme based on energy
distribution (FEED) with hidden Markov model (HMM) is proposed to extract the sparse features and diagnose
faults. Our proposed method with other five state-of-the-art dictionary learning methods is applied in two
experimental gearbox cases, and the results verify the advantage of SISDL over the others.
Autonomous drone-based imaging system for detection of potholes in rural roadAs a country with a high percentage of motorbikes, the appearance of potholes has a serious impact on people.
Today, detecting and repairing potholes takes a long time. Therefore, this research paper aims to provide
solutions for inspectors to save time in detecting potholes. In this study, the authors used drones to collect data
combined with the common computer vision model YOLOv5 to produce pothole detection models for images
taken from drones. From the identification results, we calculate the size and location of the potholes so that theinspectors can identify the danger range and come up with a reasonable repair plan. The current model reached
the precision, recall, and F1 score at 0.946, 0.961, and 0.95, respectively

46

105

Application of Unmanned Aerial Vehicle and YOLOv5 Model to Identify Water for Risk Assessment of Dengue
Fever
Abstract:
Dengue is a viral disease that is emerging rapidly as a pandemic in tropical and subtropical countries, primarilytransmitted via mosquitoes. Mosquito surveillance and control are challenging due to dynamic interaction
between humans and landscapes. The use of drones could be beneficial in mosquito surveillance and control
programs in the future. The authors aim to identify potential mosquito breeding sites using drones for largescale data acquisition and try to extract the water areas from the raw imagery datasets with 2 different
approaches. A Photogrammetry based approach can build high-resolution 2D maps of these areas, but the17th World Congress on Engineering Asset Management (WCEAM)
Ho Chi Minh City, Vietnam 18 –20 October 2023
Sustainable Management of Engineered Assets in a Post Covid-19 World: Industry 4.0, Digital Transformation, Society 5.0 and Beyond

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rendering of their exploitation by filters may not be very precise and will be dependent on the quality of theimages. Another approach is to train deep learning algorithms to detect stagnant water using the YOLOv5
instance segmentation model. A well-trained deep learning model combined with good data acquisition via
drones can effectively detect water areas and can be used for further assessing the risk of disease outbreaks.

47

110

Issues and Challenges in fault detection for commercial solar panels with Smart AI image processing
techniques – A case study in an Australian utility company

48

111

In recent years, renewable energy has become a high-priority choice in utility companies to reduce their carbon
emission footprint and cut overall energy costs. As a result, worldwide utility companies are building solar farms
to supply electricity for operation usage. Since solar PV panels are relatively new assets for the organization to
manage, organizations are continuously seeking insightful understandings to develop and optimize their solar
panel maintenance programs. For example, some organizations utilize Unmanned Aerial Vehicle (UAV)
technologies combined with an AI-driven image processing technique for condition monitoring to improve theefficiency and safety of the solar maintenance program. While the emerging AI technologies sound promising,
this research found that the existing solar panel maintenance programs could still be time-consuming, unsafe,
and costly as they might require personnel to visually inspect these assets due to various issues associated with
the AI technologies. Therefore, based on a case study, this research investigated the challenges and issues in theexisting solar panel maintenance process from technology, organization, and people perspectives. These findings
can contribute to a more effective and efficient commercial solar panel maintenance approach.
Cyber Security for Critical Information Infrastructure Assets under Nontraditional Security Lens in Vietnam
As Industry Revolution 4.0 (IR4) is exerting its influence across continents and countries, it is becoming
increasingly pressing for engineering asset managers worldwide to adopt this new mantra and adapt accordingly.
With surging cyber physical systems being invested in an ever-popular trend, it is necessary for (engineering)asset managers, especially those in charge of critical information infrastructures to look beyond for a new andperhaps more comprehensive threats and risks management framework, in order to ensure safety, resilience17th World Congress on Engineering Asset Management (WCEAM)
Ho Chi Minh City, Vietnam 18 –20 October 2023
Sustainable Management of Engineered Assets in a Post Covid-19 World: Industry 4.0, Digital Transformation, Society 5.0 and Beyond

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Abstract
and asset values under their possessions. This paper presents a slice of the current situation in Vietnam in termsof CII (assets) management, focusing on cybersecurity aspects using nontraditional security analytic framework,
developed by (Hoang et al., 2022) that has been applied in areas such as finance (Nguyen and Hoang Dinh, 2021),
marketing (Hoang, Ta and Bui, 2022), engineering and technological security (Hoang and Nguyen, 2023)* . The
paper also explores how several large enterprises and organizations of Vietnam perceive cyber threats and risks
as well as their opinions on CS importance.
Exploring the Challenges and Opportunities in Operationalising ICTbased Asset Management Maintenance
Practices within Emerging Telecom Industry: – The Case of Nigeria Telecom.
Telecommunication network operators in emerging markets are operating in an increasingly demanding
environment due to deficiencies in basic infrastructure, increased internet penetration, regulatory policies andgrowth in subscribers' connections and usage. In several instances, these demands, and subscriber growth havetranslated into the deployment of physical assets, which leads to enormous tension in the telecom basetransceiver stations (BTS) that house the assets. Under these conditions, network operators need to operate andmanage their infrastructure or assets efficiently to add to the overall performance of their operations andcustomer satisfaction. However, several studies have not provided a clear perspective, as there is no developed
maintenance strategy concerning asset management practices across the emerging telecoms environment.
Therefore, the research aims to explore current asset management and maintenance practices across the Nigeria
telecoms environment and then suggest measures and approaches to addressing the research context. A survey
case study strategy was adopted using a mixed-method approach and a technology acceptance model (TAM2)
to define the most efficient management and maintenance intervention required to maximize the asset lifecycle
and sustainable network service. The study findings intend to show that asset management and maintenancepractices in Nigeria's telecoms environment face critical management and maintenance issues. Because physicalassets must be managed and maintained strategically, weak monitoring and non-application of an ICT-poweredpredictive-based asset management model for asset visibility are critical challenges in the researched domain.
These results could explain how a predictive and human-centric approach's ICT capabilities addresses andenhance asset problems and performance.

17th World Congress on Engineering Asset Management (WCEAM)
Ho Chi Minh City, Vietnam 18 –20 October 2023
Sustainable Management of Engineered Assets in a Post Covid-19 World: Industry 4.0, Digital Transformation, Society 5.0 and Beyond

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114

Development Perspective of Electrostatic Machine
Abstract.
The electromagnetic motors have been dominated the industrial and house-hold market so far. The main costof these machines stems from metallic ma-terials, iron cores and/or permanent magnets. The problems
associated with these machines are the increasing cost and the lower availability of rare earth for producing
permanent magnet. In addition, the production of the metals such as aluminium, copper heavily deteriorates
the environment by the emission of industrial wastes. This paper presents a development perspective of theelectrostatic machine including the general design and analysis of different machine topologies and theirapplications.

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Integrating Blockchain Technology to Manage Telecommunications Infrastructure: A Case Study116

The Covid-19 pandemic had a profound impact on all sectors of society. In the telecommunications sectors, thepandemic led to a massive increase in demand for mobile communication and network services. Among otherthings, the pandemic also created the need for investment to rapidly expand existing infrastructure as well as toestablish new capacity in telecommunications assets systems to keep track of the evolution in, for instance,
subscriber growth and internet usage. The rapid evolution boosted by the pandemic raises questions about how
to manage the systems of assets such as, equipment, machinery and infrastructural facilities that underpin thetelecommunications sector. A particular question is how to deploy 4IR technologies to facilitate the managementof rapidly expanding and evolutionary assets in the telecommunications sector. This paper discusses an
exploratory case study on the application of blockchain technology to facilitate the management oftelecommunications infrastructure.
Assessment design before and after the emergence of generative AI

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Sustainable Management of Engineered Assets in a Post Covid-19 World: Industry 4.0, Digital Transformation, Society 5.0 and Beyond

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Abstract
The birth of generative AI has had a profound impact on assessment design in the field of software programmingcourses. This study investigates the changes in assessment methodologies before and after the emergence ofgenerative AI technology. Traditional assessment approaches in programming courses often involved manualcode reviews, quizzes, and practical assignments. However, with the advent of generative AI, new assessment
methods have emerged, leveraging automated code analysis, intelligent feedback generation, and adaptive
testing. This abstract highlights the paradigm shift in assessment design, emphasizing the potential benefits ofgenerative AI in enhancing assessment accuracy, efficiency, and personalized learning experiences for software
programming students. By examining the evolution of assessment practices in the context of generative AI, thisstudy aims to contribute to the ongoing discussions on the integration of AI technologies in software
programming education.
Remote Identification of Mining Dump Truck Operations Based on Vibration Signal
A mining dump truck is one of the most essential pieces of equipment for transportation in an open-cast mine.
The trucks carry out cyclic material movement operations such as loading at excavation points, hauling material
on mine roads, and unloading at dumping sites. While performing these operations, the body of dump trucks is
impacted by loading and roads of mines which cause damage to them over time. This paper shows the remote
operation monitoring of dump trucks based on vibration sensors mounted on different parts of it. The vibrations
sensors are installed on the left-right frame, cabin floor, and engine of the dump truck. Vibration is recorded
from dump truck when they carry out these mining operations and is transferred to the cloud simultaneously.
These processes are accomplished with the help of a specifically designed system. Data in the cloud is extracted
remotely and analysed to detect loading, dumping, hauling, and idling operations using time features andfrequency domain features of the signal. Kalman filters are used to denoise the measured vibration signals andremove any outliers in the estimated features. Also, it is found that frames and cabin floor vibration help identify
the mining operations more effectively than engine vibration, where loading and hauling operations aredetected in low-frequency regions. The experiments were conducted in real-time in an open-cast coal mine ineastern India

17th World Congress on Engineering Asset Management (WCEAM)
Ho Chi Minh City, Vietnam 18 –20 October 2023
Sustainable Management of Engineered Assets in a Post Covid-19 World: Industry 4.0, Digital Transformation, Society 5.0 and Beyond

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Exploring Asset Management Performance: A Knowledge Management Perspective

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Asset management is a crucial index for the yearly performance evaluation of state-owned higher education
institutions (HEIs) in China. Although studies have investigated asset management in HEIs from various
perspectives, few have explored the predictive role of knowledge conversion in asset management performance.
To fill this research gap, this study embraces structural equation modelling analysis to identify the relationshipbetween knowledge conversion and asset management at both the institutional and individual levels. It also
explores institutional and personal enablers of implementing knowledge management to contribute to HEIs’
asset management performance. The analysis was based on questionnaires collected from university leadershiporganizations, administrative officers, and academic faculty members from 60 universities across China. The
findings show that a collaborative culture advocates for knowledge contribution through the application ofhuman interactions in HEIs’ asset management mechanisms. Knowledge management facilitates personal
motivation and the promotion of asset management in HEIs’ performance evaluation.
Fault Diagnosis based on Graph Convolutional Network for Industrial Robot Harmonic Reducers

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With the widespread application of industrial robots in automated production, strengthening health monitoringand ensuring reliability and accuracy through fault diagnosis have become crucial. Harmonic reducers, which are
critical transmission components in industrial robots, can experience faults that result in performancedegradation or downtime, making accurate fault diagnosis essential. In this study, we propose a graphconvolution-based approach that constructs a graph structure from the vibration signal data of harmonic
reducers and applies graph convolutional networks (GCNs) for end-to-end fault diagnosis. We validated our
method through experiments using real-world collected data, and conducted comparative experiments on
different graph construction methods, demonstrating the feasibility and effectiveness of our approach.
Furthermore, we discuss the potential future prospects of the proposed method.
Intelligent fault diagnosis method of robot joint—harmonic reducer

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Ho Chi Minh City, Vietnam 18 –20 October 2023
Sustainable Management of Engineered Assets in a Post Covid-19 World: Industry 4.0, Digital Transformation, Society 5.0 and Beyond

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As the core component of a robot, the harmonic reducer is a high precision, high-torque transmission device
that has a wide range of applications in the field of robotics. However, owing to the complex internal structureof the harmonic reducer and the large amount of friction and heat generated during operation, it is more prone
to failure unexpected which has a significant impact on the operation of the robot. Therefore, a fault diagnosis
method based on empirical mode decomposition (EMD) and support vector machine (SVM) was proposed. First,
the fault data are decomposed by EMD, and the eligible IMFs are screened for reconstruction according to thesteepness value of each eigenmode function (IMF) and the number of correlations with the signal before
decomposition. Second, the reconstructed signal is band-pass filtered according to the recommended center
frequency and bandwidth, and the square envelope is demodulated after filtering. Third, the time-domain andfrequency-domain features of the square envelope signal are input into the SVM classifier for training and testingand obtain classification results. Finally, a comparative experiment is conducted, and the comparison results
show that the proposed method has high accuracy for the fault identification of the harmonic reducer, which
can provide theoretical support for ensuring the safe operation of the harmonic reducer and robot.
Integrating Predictive Analytics with RAMS Analysis to Quantify Performance Improvement

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Traditional RAMS analyses such as FMEA and RBD rely on a mix of work history and the assessment ofexperienced personnel to estimate probability of failure of components within systems. In this paper we present
an improved approach to manage delay data from equipment downtime logs into probability density functions
that assist with quantifying potential savings. The analytics include data conditioning to classify types of faults
and support standard Weibull calculations for MTTR and MTBF to classify failure modes to specific blocks
representing components within the system. The approach relies on a data model that handles a wide range ofcodification schemas with plain English interpreters to convert commentary to failure modes which can then be
allocated to the blocks. The outcome of this work is the automated treatment of the many problems impacting
complex systems of equipment, rolling up component-level issues to the system level and advising on reliability
improvements.
Optimisation of Asset Management with Qualitative Risk Profiling58

17th World Congress on Engineering Asset Management (WCEAM)
Ho Chi Minh City, Vietnam 18 –20 October 2023
Sustainable Management of Engineered Assets in a Post Covid-19 World: Industry 4.0, Digital Transformation, Society 5.0 and Beyond

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Assessing the risk in physical assets considers their multi-criteria criticality and the likelihood that they will nolonger function as intended, thereby realising risk. Quantifying this risk provides an important ranking scheme
for prioritising investment and additional work on the assets to manage down the likelihood of the worst-caseoutcome. Criticality ranking determines this outcome for a range of criteria and considers mitigating factors
which are typically investments in control, redundancy of operation and fail-safe measures. The more complex
consideration is the probability that the worst-case risk may be realised. This may be calculated either as
deterministic measures associated with physical degradation of the asset or probabilistic estimates based oncommonly collected maintenance and inspection information. This paper examines practical implementation ofthese considerations in complex facilities which comprise thousands of assets. Consideration is given to how risk
may be better managed once it is quantified.
Evaluation of the effect of different factors on pavement roughness, rutting and cracking; A case study
A well-maintained transportation infrastructure system is an indicator of a wellfunctioning economy. Road
degradation is often considered to be unpredictable due to the effect of various influential factors including
environmental and geographical conditions. Even though, the real trends of the pavement deterioration under
different combinations of environmental and geographic factors have not been much explored and they are not
implemented in the optimum pavement designs. Therefore, this study examines the effect of different factors
when considered individually and collectively on the performance of the flexible roads based on real field dataof IRI, rut depth and crack area measurements. The distribution of values of each distress in two road clusters;
urban and rural is studied to identify the behavioural patterns with various external factors including rainfall,terrain type and drainage condition. The study is based on the monitoring data collected over 15 years acrossAustralia. 60 unique combinations of factors including 5 different rainfall classes, 4 terrain types and 3 drainage
conditions are analysed to identify the trends in the spatial distribution of each distress. The results reveal clear
trends of IRI, rut depth and crack area values with rainfall, terrain type and drainage condition of the road when
considered as individual factors while the combined effects of different factors show contradictory behaviours.

17th World Congress on Engineering Asset Management (WCEAM)
Ho Chi Minh City, Vietnam 18 –20 October 2023
Sustainable Management of Engineered Assets in a Post Covid-19 World: Industry 4.0, Digital Transformation, Society 5.0 and Beyond

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The results can be used in the pavement maintenance decisions and in the design and construction of the newroad sections.

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Incorporating environmental impacts and end-of-life potentials for sustainable asset management decision
making
Civil infrastructure sector contributes up to 40% of global annual carbon emissions. Different sustainability rating
systems and circular indices are currently being developed to quantify and reduce emissions in the industry.
While a methodology to quantify carbon emissions considering the entire life cycle of the built environment has
yet to be fully developed. A better approach would optimize the management of civil infrastructure assets byfocusing on the life cycle emissions and end-of-life impacts to deliver a circular economy. This paper proposes anovel index for capturing the whole-life-cycle environmental impact and circularity of an infrastructure asset.
The integrated methodology to develop the Digital sustainability index (DSI) from material passports is presented
by conducting a comprehensive literature study. For the demonstration of this index, a methodologicalframework has been constructed. This novel index will enable building owners and managing authorities toadopt strategic initiatives for reducing emissions associated with the life cycle of building assets with a clear
knowledge of quantified benefits in mind.

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Vibration Analysis and Troubleshooting of Large Synchronous Motors and Generators: Common Faults andSolutions
Large synchronous motors and generators can experience high vibration due to various mechanical andelectrical faults. This paper focuses on mechanical faults such as unbalance, misalignment, mechanicallooseness, structural resonance, oil instability (i.e., oil whirl or insufficient oil flow), rubbing, and bearing wear.
Vibration can be measured using accelerometers located on the bearing housing or proximity probes forjournal bearings. These sensors can serve as protection sys-tems, tripping the machine when high vibration isdetected, or provide condition monitoring services and machine diagnostics. Common vibration analysis tools

17th World Congress on Engineering Asset Management (WCEAM)
Ho Chi Minh City, Vietnam 18 –20 October 2023
Sustainable Management of Engineered Assets in a Post Covid-19 World: Industry 4.0, Digital Transformation, Society 5.0 and Beyond

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in-clude FFT spectrum, waterfall plot, orbit plot, shaft centreline plot, polar plot, and bode plot, which can begenerated using computer software. This paper presents a list of the most common causes of high vibration inlarge synchronous motors and generators, including recommendations for checks to diagnose the issue andcorrec-tive actions to solve the problem. Industrial examples will also be provided. The findings of this study
can help asset managers and maintenance professionals trou-bleshoot and resolve high vibration issues inlarge synchronous motors and genera-tors, improving their reliability and extending their lifespan.
A Review of Personalised Gamified Applications.
Human factors play a critical role in asset management, impacting the effectiveness and efficiency of asset
management processes. It encompasses the psychological, social, and organization aspects that influence how
individuals in-teract with assets, systems, and processes in asset management. In the transporta-tion sector,
human error contributes significantly to crashes including the use of alcohol, failure to use a seat belt, and risky
or aggressive driving. Gamification features serve to inform the driver about their driving characteristics(acceleration, braking, cornering, speeding, idling etc.) in an engaging format. To be effective, gamification
features in an eco-driving application must support the driver’s atti-tudes, subjective norms, and perceived
behavioral control toward eco-driving. Al-so not understood is whether the relative importance of thesefactors changes ac-cording to personality type. Accordingly, there is a need to develop gamification tailored tothe driver’s eco-driving behavioral intention. This work presents a re-view of existing research on designingpersonalized gamification interfaces. In the field of asset management, personalized gamification may makeeco-drive pro-grams or even improve training programs to be more effective and engaging.
Digital Transformation in Higher Education with Support from Large Language Models: A Multiple
Perspective Approach to Teaching Engineering Courses

This study evaluates the efficacy of ChatGPT as an AI teaching and learn-ing support tool in an introductory
integrated circuit systems course at a higher ed-ucation institution in an Asian country. Various question types
were completed, and ChatGPT's responses were assessed to gain valuable insights for further investiga-tion.

17th World Congress on Engineering Asset Management (WCEAM)
Ho Chi Minh City, Vietnam 18 –20 October 2023
Sustainable Management of Engineered Assets in a Post Covid-19 World: Industry 4.0, Digital Transformation, Society 5.0 and Beyond

BOOK of ABSTRACTSNo

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The objective is to assess ChatGPT's ability to provide insights, personalized support, and interactive learning
experiences in engineering education. The study includes the evaluation and reflection of different
stakeholders: students, lecturers, and engineers. The findings of this study shed light on the benefits andlimitations of ChatGPT as an AI tool, paving the way for innovative learning approaches in technical disciplines.
Furthermore, the study contributes to our understanding of how digital transformation is likely to unfold in the
education sector.
Keywords: ChatGPT, Generative AI, Digital transformation, engineering educa-tion, tutorial design, peerassisted learning, AI-assisted learning, integrated circuit education.
Increasing Asset Management Capabilities of Local Authorities in Sri Lanka
Infrastructure planning, management and budgeting, including establishing and managing of infrastructure
inventory has been quite a challenge in local authorities of Sri Lanka and one can see a lot of gaps, duplication,
and wastage of already limited resources in the provision of services to the community. A robust AssetManagement System has been the longstanding need for the Local Authorities to efficiently plan and manage
the local infrastructure. But their capacity in this regard is much wanting and there has been a need for both (i)establishing an efficient and user-friendly system and (ii) building the capacities to operate and manage thesystem. Government of Sri Lanka has been making a concerted effort to improve asset management practices.
One such successful effort was securing the support of RMIT University for digital transformation of the asset
management practice in Sri Lanka enabling capacity building not only in optimized management of
infrastructure assets but also enabling digital transformation of the practice. A pilot project to develop thesystem and build capacities in asset management of local authorities has just been completed. The
Government plans to expand the capabilities of other local authorities based on this experience.
The paper presents the current scenario of Asset Management in Local Authorities of Sri Lanka and efforts of
the Ministry in-charge of Local Government in increasing the capacities of Local Governments in establishing
and working on sustainable inventory and asset management systems, through an Asian Development Bank
funded project. The paper will present the current practice, identification of the best appropriate level of17th World Congress on Engineering Asset Management (WCEAM)
Ho Chi Minh City, Vietnam 18 –20 October 2023
Sustainable Management of Engineered Assets in a Post Covid-19 World: Industry 4.0, Digital Transformation, Society 5.0 and Beyond

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digital capability for the authorities and design and implementation of the software platform in seven local
authorities as a pilot. The training program deployed and the benefits of the project as observed by thegoverning authorities will also be presented.
Explore an optimized trade-off for retrofitting measures in office buildings.
Abstract:
Buildings account for over one-third of global energy consumption and emissions. Reduction in building energy
consumption is feasible by implementing active and passive retrofitting strategies. However, the rise of highperformance buildings poses a unique challenge to understanding retrofit measures and their relative
efficiency adopted in the existing buildings. Conventional analysis of energy audits is insufficient to have an indepth insight into improved efficiency measures. This study addresses this issue with a holistic approach todiagnosing faults by installing an energy monitoring system. An energy savings model has been performed per
AS/NZS 3598:2000 standard to represent building energy use in the operational phase. The critical pathmethod (CPM) is defined based on retrofitting strategies' installation cost and annual savings. Installation of a
new chiller, variable speed drive (VSD) pump and fan coils are identified as the potential energy efficiency
measures for retrofitting. Financial indicators of retrofitting variables facilitate estimating and identifying
energy savings, informing the decision-making process during retrofitting. Furthermore, the study also
addresses the associated risks with the installation process to the development of best practices in retrofitting
the existing building.
Managing Highway Pavement Skid Saves Lives
Skid resistance is a critical pavement surface characteristic associated with road user safety, especially during
wet weather conditions. There is an inverse correlation between roadway friction levels and the number ofwet weather crashes: as skid resistance decreases, the number of wet weather crashes increases. However,skid remains a cumbersome characteristic to measure at a network level due to the inefficiencies of themeasuring equipment. These limitations have created the need for an alternative method capable of predicting
pavement friction continuously using readily available information, such as pavement texture. This study

17th World Congress on Engineering Asset Management (WCEAM)
Ho Chi Minh City, Vietnam 18 –20 October 2023
Sustainable Management of Engineered Assets in a Post Covid-19 World: Industry 4.0, Digital Transformation, Society 5.0 and Beyond

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evaluated thirty highway pavement sections in the state of Texas that cover a vast range of pavement surfaces,
textures, and friction levels. The data were used to create machine learning models that use pavement texture
to accurately predict surface information and friction. The model estimates skid in terms of grip number (GN)on the major types of flexible pavements present in Central Texas with an accuracy in the order of 80%. The
innovative way in which machine learning algorithms are used in this study has the potential to allow highway
agencies to obtain full network coverage of reliable estimates for friction.

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Indus TANTRA: An Indigenous, Modular, Scalable Platform for Industry 4.0 Implementation
Industry 4.0 protocols involve integration of physical systems with cyber technology for enhanced productivity
and quality assurance. They provide the bridge between Operational Technology (OT) and Information
Technology (IT). Operational Technology (OT), concerned with Physical Processes, involves Control Systems like
PLC, DCS, SCADA etc., Hardened PCs and Servers, Industrial Networks, Sensors (temperature, pressure etc.),
Cameras, Scanners, Embedded Systems (robots, analylzers), etc. Information Technology (IT) is concerned with
Computing operations, Business Applications, Data Analysis, Storage Systems, and other hard and soft
elements for managing information. Several hardware and software constraints, limit OT and IT integration. In
this paper we describe implementation of Industry 4.0 protocols for a manufacturing unit. This is achieved
through development of an indigenous platform, christened IndusTANTRA, which is modular and scalable andattempts to provide an end-to-end solution to Monitor, Manage and Control capabilities for CNC/Robotic
Machines; possesses flexibility to incorporate Manual Machines monitoring using indigenously built add-on
hardware, and capabilities for RFID enabled material tracking, Human Machine Interfacing, Indigenous
Scheduling and ERP integration, and AI/ML powered Custom Analytics.