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Asian Journal of Engineering, Social and Health
Volume 4, No. 1 January 2025
Volume 4, No. 1 January 2025 - (1-20)
p-ISSN 2980-4868 | e-ISSN 2980-4841
https://ajesh.ph/index.php/gp
Lean Six Sigma in Digital Transformation Geotechnical Operational Integration
using the G-Rocks Platform to Manage Geotechnical Hazards
Seno Maris Utomo1*, Gatot Yudoko2, Ridho Kresna Wattimena3,
Dradjad Irianto4, Edy Wicaksono5
Institut Teknologi Bandung, Indonesia
Emails: senomarisutomo@gmail.com1, gatot@sbm-itb.ac.id2, rkwattimena@itb.ac.id3,
dradjadirianto@office.itb.ac.id4, edy.wicaksono@sinarmasmining.com5
ABSTRACT
Delays in the collection, analysis, and dissemination of geotechnical data are critical barriers that threaten
operational safety and efficiency at PT Borneo Indobara. This research aims to design and validate the G-
ROCKS (Geotechnical Real-Time Observation and Control for Key Stability) platform using the DMADV
framework to address these issues. This research method uses quantitative methods including the
development of the G-ROCKS platform consisting of real-time monitoring tools, geofencing systems, and
control centers that can be accessed via dashboards and mobile applications. The implementation of this
platform resulted in significant improvements, including reducing the average response time from 17
minutes to less than 5 minutes, exceeding the emergency team's SOP target of a maximum of 7 minutes,
and achieving a Six Sigma performance level of 4.5 with a design target of 6.0. These findings highlight the
importance of integrated geotechnical systems in reducing risks, accelerating decision-making, and
preventing landslides through actions aligned with Industry 4.0 standards. This research provides
implications in the form of applicative insights for adopting digital solutions to improve safety and
efficiency in the mining industry.
Keywords: Lean Six Sigma, DMADV Framework, G-ROCKS Platform, Geotechnical Hazard Management,
Real-Time Monitoring, Digital Transformation.
INTRODUCTION
PT Borneo Indobara (PT. BIB), a major coal mining company in Indonesia, is embarking on
a strategic expansion to increase its production capacity from 46.8 million tons to 54 million tons
annually. While this ambitious growth underscores the company’s commitment to meeting
global energy demands, it also introduces significant operational and geotechnical challenges. In
particular, managing slope stability in the context of expanding mining activities has emerged as
a critical concern (Daffa, 2024).
Globally, geotechnical hazards, particularly landslides, have been a pressing issue in the
mining industry. These hazards not only jeopardize operational safety but also have severe
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economic implications (Smith, 2013). According to data from the International Council on Mining
and Metals (ICMM), geotechnical failures account for approximately 30% of all incidents in large-
scale mining operations worldwide. This issue is further exacerbated by the increasing scale of
mining projects and the complexities introduced by digital transformation and Industry 4.0
(Oesterreich & Teuteberg, 2016). The integration of advanced geotechnical risk management
tools has become a necessity to address these challenges effectively.
For PT. BIB, these global concerns resonate at a localized level. The company’s mining
concession spans 24,100 hectares in South Kalimantan, an area characterized by weak soil
material properties that significantly increase the potential for landslides as production scales
up. Historical data from 2018 to 2023 reveals an alarming upward trend in landslide occurrences,
as illustrated in Figure 1. The correlation between increased production and geotechnical
instability underscores the urgent need for comprehensive risk management solutions.
Projections for 2024 to 2027 indicate a continuation of this trend, with landslides expected to
peak during the maximum production stage.
Figure 1. Historical Landslides from 2018-2023 and Forecast Landslides from 2024-2027)
The consequences of these geotechnical challenges are multifaceted (Martinez et al.,
2022). Direct impacts include physical damage to infrastructure and equipment, while indirect
impacts extend to production delays and compromised worker safety. Financially, these issues
translate into significant losses for PT. BIB. Furthermore, the current geotechnical processes at
PT. BIB are fragmented and lack integration, resulting in inefficiencies in data collection, analysis,
and decision-making. These shortcomings not only compromise operational safety but also
hinder the company’s ability to respond swiftly to emergencies. Additionally, limited awareness
and competence among mine workers regarding geotechnical conditions further exacerbate the
situation.
In response to these challenges, PT. BIB recognizes the need to align its operations with
government regulations on good mining practices. The KEPMEN 1827 K/30/MEM/2018
guidelines and the “Road to Mining Industry 4.0” program provide a framework for implementing
these practices (Akbar et al., 2024). These regulations emphasize hazard identification, risk
assessment, and the implementation of control measures to mitigate risks. For PT. BIB, this
includes adopting slope monitoring technology, designing safer slopes, and integrating mine
planning with geotechnical considerations (Simangunsong et al., 2024). However, the lack of fully
Lean Six Sigma In Digital Transformation Geotechnical Operational Integration Using The G-Rocks
Platform To Manage Geotechnical Hazards
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integrated geotechnical monitoring equipment has been a persistent challenge. As noted by
(Kenett & Shmueli, 2016), incomplete and delayed data collection undermines the ability to make
informed decisions, often leaving critical information inaccessible to those who need it most.
The broader context of geotechnical risk management highlights the role of digital
transformation in addressing these challenges. Previous reserach emphasizes that one of the
primary challenges faced by geotechnical engineers in the 21st century is the collection, storage,
and analysis of large volumes of data (Becerik-Gerber et al., 2014). The ability to manage this
data effectively is critical for enhancing decision-making processes and improving operational
safety. Digital platforms that integrate geotechnical data collection and analysis offer a promising
solution to these challenges.
A review of previous studies underscores the potential of digital transformation in
geotechnical risk management. For instance, (Huang et al., 2017) highlight the importance of
integrated monitoring systems in reducing geotechnical risks in mining operations. Their research
demonstrates that digital platforms can significantly enhance data accuracy and decision-making
efficiency. Similarly, a research by (Phoon, 2020) explores the challenges and opportunities
associated with managing large geotechnical datasets. The findings suggest that digital solutions
can address many of the inefficiencies currently plaguing traditional geotechnical processes.
The novelty of this research lies in its focus on integrating the G-Rocks platform with the
Six Sigma DMADV methodology. While previous studies have explored the benefits of digital
transformation and geotechnical risk management separately, this research bridges the gap by
combining these approaches. By doing so, it provides a comprehensive framework for addressing
geotechnical challenges in the context of PT. BIB’s operational expansion.
The urgency of this research is underscored by the increasing frequency and severity of
landslides at PT. BIB’s mining sites. Addressing these challenges is not only critical for achieving
production targets but also for ensuring the safety and well-being of the company’s workforce.
Furthermore, the integration of digital solutions aligns with the broader objectives of the “Road
to Mining Industry 4.0” program, positioning PT. BIB as a leader in adopting innovative
approaches to mining operations.
The objectives of this research are threefold. First, it aims to identify the key geotechnical
challenges faced by PT. BIB in the context of its operational expansion. Second, it seeks to
evaluate the effectiveness of the G-Rocks platform in addressing these challenges. Finally, it
intends to develop a comprehensive framework for integrating digital solutions with geotechnical
risk management processes. The benefits of this research extend beyond PT. BIB. By
demonstrating the effectiveness of the G-Rocks platform and the Six Sigma DMADV
methodology, this research provides a model that can be adapted and applied by other mining
companies facing similar challenges. Additionally, the findings contribute to the broader field of
geotechnical risk management, offering insights into the role of digital transformation in
enhancing operational safety and efficiency.
Seno Maris Utomo, Gatot Yudoko, Ridho Kresna Wattimena, Dradjad Irianto, Edy Wicaksono
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RESEARCH METHOD
This research explored the risk management of geotech improvement through
digitalization using an integration platform to address future problems. It uses a quantitative
method to produce a good evaluation of Six Sigma between the current geotech operational
conditions and geotech operational conditions using an integration platform.
Figure 2. Research Design Diagram
This DMADV (Define, Measure, Analyze, Design, Validate) framework diagram shows the
integration of systems to accelerate geotechnical data collection to reduce the number of
landslide incidents due to increased production targets. The Define stage focuses on identifying
business and customer needs. In contrast, the Measure stage emphasizes measuring the process
and the ability to meet the planned solution through parameters, data collection, and process
behavior analysis. The Analyze stage identifies the root causes of poor performance and
determines success factors. In the Design stage, the proposed design solution is tested and
implemented based on confirmed data, followed by the validation stage to control and ensure
the design function is by the business strategy. This system integration aims to synchronize
geoscientific and monitoring data to improve operational safety, efficiency, and cost
management.
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Platform To Manage Geotechnical Hazards
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RESULT AND DISCUSSION
Define
The “Define” section of this project focuses on establishing boundaries and a clear
understanding of the scope and objectives of the Geotechnical Management Information System
at PT Borneo Indobara. A clear definition of the problems faced and the establishment of relevant
performance indicators are crucial initial steps to ensure that the proposed solution is targeted
and effective. In the Define stage in the DMADV framework using the SIPOC (Suppliers, Inputs,
Process, Outputs, Customers) concept, the main focus is to identify business and customer needs
in the context of accelerating geotechnical data information for geotechnical risk management
to reduce landslide incidents, especially in dynamic mining operations with high production
targets (Lima, 2023).
Figure 3. SIPOC Diagram G-ROCKS
Measurement
One of the most crucial stages in the DMADV method is the Measure stage, which aims to
collect relevant data and establish a strong basis for the next steps. The measurement process at
this stage includes identifying and gathering relevant information about variables that affect the
quality or performance of the product or process to be designed. This section aims to measure
each stage's duration in delivering geotechnical hazard information at PT Borneo Indobara using
the Six Sigma method. Time measurement data has been collected to evaluate the efficiency of
the current process and establish a baseline for proposed improvements.
Actual Conditions and Sigma Value Calculation
Measurement of actual conditions is done by taking 10 samples per activity, which is a
compromise between time and cost constraints. A small sample size (8-10) is representative
enough if the data approaches a normal distribution and does not have more than one mode,
according to the Central Limit Theorem, which states that the distribution of sample means will
approach a normal distribution, even though the population distribution is not normal, as long
as the sample size is large enough. To ensure that the data approaches a normal distribution, a
normality test is carried out using the Jarque-Bera Test, which tests the kurtosis and skewness of
the data against a normal distribution. The hypotheses tested are:
1) H0: The data follows a normal distribution.
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2) H1: The data does not follow a normal distribution.
Suppose the Jarque-Bera test results show a probability (p-value) more significant than the
significance level (for example, α = 0.05). In that case, the null hypothesis (H0) cannot be rejected,
which means the data follows a normal distribution. Conversely, if the probability is smaller than
the significance level, the null hypothesis is rejected, which means the data does not follow a
normal distribution.
Defects Per Million Opportunities (DPMO) calculation measures process performance by
calculating the number of defects per million opportunities (Setijono, n.d.). DPMO is calculated
based on the number of defects, the number of units tested, and the number of defect
opportunities per unit. After DPMO is calculated, the sigma value is determined using the DPMO
to sigma value conversion table, which indicates the level of process quality. In the graphic figure
5 the results of measurements and data processing from actual conditions according to the
process stages
Figure 4. Measurement Results And Data Processing From Actual Conditions
Based on the calculation of actual conditions, such as the table 1 below, the Geotechnical
Management Information System at PT Borneo Indobara is currently as follows:
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Table 1. DPMO and Lean Six Sigma Calculation Results Actual Conditions
Data
Sample
Measure
ment
Collecting
from
Monitoring
Tools
Data
Analysis
Risk
Matrix
Calculatio
n
Marking
Hazard
Location
Informat
ion
Viewed
Understandi
ng
Information
Field
Verificat
ion
Follow-up
Informati
on
Duration
(minutes)
Duratio
n
(minute
s)
Duration
(minutes)
Duration
(minutes)
Duration
(minutes
)
Duration
(minutes)
Duratio
n
(minute
s)
Duration
(minutes)
Sample
1
1,9
4,9
3,4
5,3
1,6
2,2
1,7
3,8
Sample
2
2,2
5,4
3,7
1
2,6
2
3,6
1,5
Sample
3
1,8
4,3
3
4,4
2,8
1
1
3
Sample
4
1,8
4,9
3,4
6,7
2
2
2
3
Sample
5
2,4
5,2
3,6
5,6
1,4
1
1
5
Sample
6
2,3
5
3,5
5,4
1,2
2
3
4
Sample
7
2,3
5
3,5
4,5
2,4
3
1
2
Sample
8
2,3
5,2
3,6
5
3,4
1
2
1
Sample
9
2,4
5,2
3,6
3,4
2,5
3
2
3
Sample
10
2
4,9
3,4
-
2,1
1
.
2
Sample
11
-
.
-
-
2.2
2,7
-
5
Spec
Limit
(minute)
1,9
4,8
3,6
2,6
1,4
1,2
2,2
3,3
Average
2,1
5
3,5
4,6
2,2
1,9
1,9
3
Standar
d
Deviatio
n
0,2
0,3
0,2
1,6
0,6
0,8
0,9
1,3
Jarque-
Bera p-
value
0,5
0,2
0,2
0,3
0,9
0,6
0,7
0,8
Defect
8
9
3
8
10
7
2
4
DPMO
800000
900000
300000
888889
909091
636364
222222
363636
Sigma
Level
0,66
0,22
2,02
0,28
0,16
1,15
2,26
1,85
This table shows the analysis of the time duration of several activities in a process, including
data collection, analysis, risk calculation, and information verification. Each activity is measured
in minutes for 9-11 samples, with a specific time limit set. Statistics such as average, standard
deviation, defect rate (DPMO), and Sigma Level are used to evaluate the performance of each
activity. Activities with low Sigma Level, such as "Information Viewed" (0.16), "Data Analysis”
(0.22) and “Marking Hazard Location” (0.28), "Collecting From monitoring tools" (0.66),
"Collecting From Field Inspection" (0.66), indicate a lot of defects and need significant
improvement. In contrast, activities such as “Field Verification” (2.26) perform better. These
results highlight that most processes still need improvement to achieve more optimal
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performance levels, especially activities with high DPMO and Sigma Level below 1. Improvements
can focus on root cause analysis and corrective measures in processes that show low
performance. This is important to reduce variability and improve overall system efficiency. It was
found that the actual condition process of the data analysis and hazard reporting section took
17.1 minutes to collect monitoring tools data or 19.5 minutes to collect inspection data in the
field. In the Figure 5 is the actual condition workflow:’’
Figure 5. Geotechnical Workflow Actual Condition
Based on PT Borneo Indoboara’s Standard Operating Procedure for the Golden Time
Emergency Response Team, the longest is 7 minutes, while for the follow-up of hazard reports,
it is 8.8 minutes; this causes a misalignment of time between the Golden Time Emergency
Response Team and the follow-up of geotechnical hazards so that improvements are needed,
especially in the follow-up of hazard responses. If we refer to the potential for digitalization, it
tends to have a low sigma value. This shows that most of the processes in this system still have
significant defects and require improvement. However, there is an exception in the information-
sending process with a sigma value of 6. This process has been declared efficient because it is
supported by available technology and well optimized. High efficiency in this information-sending
process shows that the geotechnical management information system can achieve excellent
performance with the right technology.
Analyze
This evaluation aims to detail the areas that need improvement and provide a strong basis
for decision-making. To identify the root cause of the existing problems, we use the Root Cause
Analysis approach with the Fishbone Analysis method & Pareto method.
Root Cause Analysis
Root Cause Analysis (RCA) is a systematic method for identifying the root causes of a
problem or undesirable event (Rodríguez-Álvarez et al., 2024). The primary goal of RCA is to find
the underlying causes of a problem rather than simply fixing the symptoms that are visible on the
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Platform To Manage Geotechnical Hazards
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surface. By understanding the root causes, organizations can implement more effective and
sustainable solutions that not only address the temporary problem but also prevent similar
events from happening again in the future.
Figure 6. Result Fishbone Analysis G-ROCKS
This figure 6 provides an overview of the factors influencing geotechnical risk management
in mining areas. These factors are divided into six categories: work methods, materials, people,
machines, measurements, and the environment. Some factors are uncontrollable, such as
weather conditions, climate change, and soil material characteristics, while others are
controllable, such as measurement methods, use of technology, and time coordination. The main
challenges faced include the weakness of monitoring tools, the mismatch between analysis
models and field conditions, and risks influenced by environmental factors and human activities.
Pareto analysis is a strategic method for identifying priority elements in a system based on
their impact on overall performance. In geotechnical project integration systems, it highlights key
activities affecting operational efficiency and success rates. Using Pareto diagrams, improvement
efforts can focus on critical factors influencing system performance. Integrated with a Six Sigma
approach, the analysis evaluates fishbone categories like Man, Measurement, Method, and
Machine under controllable condition factors. Notably, activities such as Hazard Location
Marking and Data Analysis (both under Method) have sigma values below 1.0, categorized as
"Poor" (red line), requiring significant improvement. Human Factors (Man) dominate as priority
elements, emphasizing the need for training and competency development to boost efficiency.
Addressing these priorities ensures enhanced system integration, reduced errors, and optimized
project outcomes.
G-ROCKS Platform Design Needs
Based on the results of the previous in-depth analysis, various root problems have been
identified that underlie the need to design solutions that can overcome existing constraints.
These problems include multiple aspects of the system that could be more optimal in terms of
operational efficiency, effectiveness in responding to emergencies, and management of limited
resources. Therefore, it is essential to design a solution that not only fixes existing aspects but
can also optimize the entire system to be more responsive to existing challenges. This solution
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must be holistic and comprehensive, answering every issue that has been identified, with the
ultimate goal of significantly improving system performance and productivity.
The design of the solution to be developed must meet several critical criteria to ensure the
success of its implementation. Each element in the design must consider various factors that
affect system performance, such as data management, process optimization, more efficient use
of technology, and increasing human resources capabilities. This design must also include a
continuous monitoring and evaluation mechanism to ensure that the new system can continue
to develop and adapt to changing needs and conditions. With this approach, the implemented
solution is expected to not only solve the current problems but also provide added value in the
long term, making the system more flexible, responsive, and ready to face future challenges.
Thus, the proposed solution can be a strong foundation for improving overall operational
efficiency, effectiveness, and sustainability. The table 2 following is a design that must be met in
the design to overcome these problems:
Table 2. G-ROCKS Design Needs Results Based On Analysis
Activity
Design Needs
Collecting from Monitoring Tools
Database Integration of all geotechnical monitoring tools
Collecting from Field Inspection
Field inspections are made into digital and interactive forms so
that they can be integrated with the database
Data Analysis
Integration produces automatic analysis reports with Al
capabilities and data input based on the entire database, so that it
can provide slope geometry recommendations
Risk Matrix Calculation
Risk matrix calculations can be integrated based on the database
and calculated automatically to determine the geotech risk/hazard
category
Marking Hazard Location
Integration of data analysis and risk matrices that can be plotted
on a map to be applied to the geofencing method
Information Viewed
Alert/TARP notifications have been delivered and understood by
the user
Understanding Information
User-friendly reports and visualization of potential landslide
positions for the user
Field verification
Get confirmation or feedback from the user based on alert/TARP
notifications
Follow-up Information
Effective communication features that can provide follow-up to
the information provided.
The Design phase in the DMADV (Define, Measure, Analyze, Design, Verify) methodology
for geotechnical system integration platform research aims to design solutions that meet user
needs and expectations and optimize the overall system quality based on previously identified
root causes.
Design
The Design phase in the DMADV (Define, Measure, Analyze, Design, Verify) methodology
for geotechnical system integration platform research aims to design solutions that meet user
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Platform To Manage Geotechnical Hazards
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needs and expectations and optimize the overall system quality based on previously identified
root causes (Jaselskis et al., 2021).
G-ROCKS Platform Master Design
The screen and interface design in the Geotechnical Master Platform is designed to ensure
a responsive, intuitive user experience that supports operational needs. The digital-based
Geotechnical Master Platform is designed with two integrated systems, namely the G-ROCKS
Command Center and the Geotechnical Information Mobile Apps, each of which has a different
focus on use and interface but supports each other in providing a comprehensive solution for
geotechnical risk management. The main difference between the two systems lies in the purpose
of their use and the interface provided, which is tailored to the specific needs of users based on
their responsibilities or job positions. G-ROCKS Command Center is a desktop-based system
designed explicitly for geotechnical engineers. This system presents a comprehensive display
with various geotechnical data analysis and visualization features that allow engineers to monitor
and analyze geotechnical data in great detail. Engineers can interpret data results through this
dashboard, identify potential problems or risks, and conduct simulations to design mitigation
solutions. Another essential feature is the dashboard's ability to create hazard reports
automatically and manually, making it easier to carry out risk assessments and make decisions
faster and more accurately. Thus, this system supports the monitoring and control process of
geotechnical risks more comprehensively and efficiently.
On the other hand, G-ROCKS Mobile Apps is a mobile-based application designed to
support field team activities, especially for mine operation teams or all mine workers. This
application has a more straightforward and accessible interface, allowing users in the field to
receive hazard reports in real time. With direct notifications regarding potential hazards or
deteriorating geotechnical conditions, this application enables the field team to immediately take
preventive action or respond quickly to reduce the risk of landslides that may occur. In addition,
this application is also equipped with a hazard report follow-up feature, which allows users to
provide feedback on the report and verify it directly on-site. This makes the process of handling
hazards in the field more efficient, effective, and well-coordinated, accelerating the response to
situations that have the potential to endanger work safety.
With the integration between these two systems, this digital-based geotechnical platform
not only improves the accuracy of analysis and monitoring, but also accelerates the process of
handling potential landslides in the field, connecting data from the analysis center with tangible
actions that can be taken by the field team directly. This integration ensures that the entire
process, from analysis to execution in the field, runs more coordinated and transparently, as
illustrated in the following sketch. Geotechnical engineers can monitor overall geotechnical
conditions and perform in-depth data analysis through a desktop dashboard that provides a
comprehensive and interactive view. The Figure 9 shows the main conceptual design of the G-
ROCKS integration system.
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Figure 7. Main Conceptual Design Of The G-ROCKS Integration System
Geotechnical engineers can monitor overall geotechnical conditions and perform in-depth
data analysis through a desktop dashboard that provides a comprehensive and interactive view.
This dashboard allows engineers to obtain up-to-date information, identify potential problems,
and formulate solutions based on available data to support safe and productive mine operations.
G-ROCKS Command Center
G-ROCKS Command Center is a desktop-based system designed explicitly for use by
geotechnical engineers at PT Borneo Indobara. This system provides an intuitive and
comprehensive user interface, allowing engineers to perform in-depth geotechnical data analysis
quickly and efficiently. This dashboard is built to present information in real-time, enabling direct
monitoring of geotechnical conditions across all mine sites managed by the company, from
exploration to production. Engineers can access and analyze data collected from various
geotechnical sensors and automatic monitoring tools spread across the mine site through this
system. The data obtained includes information related to soil stability, ground movement, rock
conditions, humidity, and other relevant geotechnical parameters. This system facilitates
monitoring of mine conditions and provides tools to process and interpret the data needed to
conduct more accurate geotechnical risk assessments.
Figure 8. G-ROCKS Command Center Dashboard Main Design
In the figure 8 is a display of the dashboard platform designed to present data more
efficiently and effectively. All data collected from monitoring tools is stored centrally and
displayed in an easily accessible interactive map format, allowing users to visualize information
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Platform To Manage Geotechnical Hazards
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more clearly. In addition, this platform is equipped with automation features that speed up the
report generation process. Data that has been integrated and automatically analyzed can be used
directly to generate comprehensive geotechnical hazard reports, saving time and reducing the
potential for human error. The report generation process that was previously time-consuming
and error-prone can now be done faster, more accurately, and more efficiently, which in turn
supports more precise and effective decision-making. With the ability to present data in real-
time and provide in-depth analysis, this platform not only speeds up the creation of geotechnical
hazard reports but also increases the accuracy and precision of the information presented. The
reliability of the information provided is critical in taking appropriate mitigation steps to reduce
potential geotechnical risks and ensure operational safety in the mining area.
G-ROCKS Mobile Apps
This research concludes that the integration of the G-ROCKS system with the DMADV
framework effectively addresses inefficiencies in geotechnical information distribution, focusing
on critical stages with sigma values <2, such as data analysis and hazard location marking. The
solution includes a centralized Command Center for rapid decision-making and Mobile Apps for
real-time notifications and reporting, with implementation progressing toward the February
2025 launch of G-ROCKS 1.0. Future research can enhance this framework by exploring
scalability, AI integration, sustainability, and user-centric innovations to advance geotechnical
hazard management globally.
One of the main features of this application is Geofencing, which aims to improve user
safety in the field. Using highly accurate GPS technology, this feature lets the platform track the
user's real-time position. Thus, the system can ensure that users are always in a safe area and
provide warnings when they enter a dangerous zone. The hazard map provided in the application
has clear boundaries for each risk zone, and potentially hazardous areas are marked with striking
colors and symbols, making them easy for users to recognize. If a user enters a risky area, the
platform will automatically send a striking warning notification in the form of an alarm sound and
text message, ensuring that users can immediately take action to avoid the danger zone. The
Figure 9 below shows the design of the G-ROCKS Mobile Apps.
Figure 9. G-ROCKS Mobile Apps
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In addition, this application is also equipped with an interactive form feature, designed to
make it easier for users to conduct inspections and verifications in the field. This feature
automatically records the user’s GPS location, ensuring that every inspection and verification
activity can be recorded accurately and integrated with the system. Thus, this platform not only
helps provide fast and accurate hazard information but also increases efficiency and accuracy in
the field documentation process, which supports better decision-making and more effective risk
mitigation actions.
Design Plan Target
Based on the design plan that has been determined, various targets will be formulated that
are expected to be achieved if the design is successfully implemented. By considering the main
aspects of the design, we set several main targets that include increasing operational efficiency,
information accuracy, team responsiveness, user satisfaction, and data integration. These targets
will be the primary reference for evaluating the success of the design implementation and
ensuring that the new system can meet the needs and expectations set. The details of the design
stages are as follows:
Figure 10. G-ROCKS Design Feature Results For Design Stage
a. Stage 1 is a recapitulation of the initial stage (Stage 1) features of developing a digital-based
geotechnical management information system. Data Analysis and Hazard Reporting:
a) From Monitoring Tools: 7.7 minutes
b) From Field Inspection: 8.9 minutes
c) Hazard Response Actions: 5.7 minutes
b. Stage 2 recapitulates the intermediate stage (Stage 2) features of the development of a digital-
based geotechnical management information system. Data Analysis and Hazard Reporting:
a) From Monitoring Tools: 3.6 minutes
b) From Field Inspection: 5.8 minutes
c) Hazard Response Actions: 5.4 minutes
c. Stage 3 recapitulates the final stage (Stage 3) features of the development of a digital-based
geotechnical management information system. Data Analysis and Hazard Reporting:
a) From Monitoring Tools: 1.9 minutes
b) From Field Inspection: 2.6 minutes
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c) Hazard Response Actions: 5.0 minutes
The figure 13 following compares the sigma values of existing conditions with the design
stages 1, 2, and 3. Note that sigma values other than existing conditions are predictive, direct
verification is needed if they have been successfully implemented.
Figure 11. Lean Six Sixma G-ROCKS Design Feature Results For Design Stage
Verify
The final stage of DMADV is verification or Control (Baptista et al., 2020). At this stage, the
project team tests and evaluates the designed solutions to ensure they meet the project
objectives and customer expectations. The steps taken include:
a. Conducting final testing of prototypes or product/process models.
b. Validating the performance of new products/improvements against established standards and
specifications and ensuring that corrected errors will not reoccur.
c. Developing a plan for implementing and launching new products/improvements into the
production or operational environment.
Feature Control Process
The verification process ensures that the system or process that has been implemented can
meet the standards and requirements that have been determined. Verification aims to confirm
that the implemented solutions or controls are running effectively and consistently in managing
essential variables that affect the final result. In this context, verification is not just an inspection,
but a deeper step to ensure that each element in the control system functions according to the
desired parameters, be it in manufacturing process control, automation control, or broader
operational management. The feature control process is essential to ensure product quality and
increase user satisfaction and trust in the product or system used. Proper control is needed to
ensure functionality, quality, and suitability to user needs so that it can be relied on under various
conditions. The figure 12 and figure 13 following is a table of verification results in the feature
control process for the G-ROCKS Command Center development progress stage:
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Table 12. Feature Control Process for The G-ROCKS Command Center Development
Table 13. Feature Control Process for The G-ROCKS Command Center Development
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The verification process for the dashboard features has made significant progress, with
visual elements like the main dashboard display achieving 75% completion, indicating an almost
finalized interface design. However, complex functional features, such as integrating
geotechnical data into interactive hazard maps (40% verified) and refining the notification system
(50% verified), require more testing and optimization. Challenges remain in real-time data
integration, accuracy of displayed information, and ensuring notifications work effectively in
dynamic hazard situations. While visual displays and some real-time data aspects are performing
well, priority must be given to refining data processing, hazard map integration, and notification
systems to ensure the dashboard is both user-friendly and capable of delivering accurate,
actionable information for effective decision-making in real-world scenarios. The verified main
features involve various aspects of the application, such as the user interface (UI) display,
notifications, and real-time data processing and presentation. The following is a table 13 of
verification results in the feature control process for the G-ROCKS Mobile Apps development
progress stage:
Table 14. Feature Control Process for The G-ROCKS
Essential elements of the mobile application have been verified and are functioning
correctly, with features such as User Activity Log and User & Role Management reaching 100%
and 80% verification, respectively, ensuring effective user activity tracking and role management.
However, complex features like Real-time Hazard Notification and Geofencing, at 60% and 50%
progress, require further refinement due to the challenges of real-time data processing and user
location tracking. Additionally, the Interactive Forms for Field Inspections, at 70% progress, need
enhancements to ensure accurate field data integration. Prioritizing the testing and optimization
of Geofencing and Real-time Hazard Notification is crucial to achieve timely alerts, accurate
hazard warnings, and optimal functionality in dynamic field conditions, ensuring both user safety
and a seamless user experience.
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G-ROCKS Implementation Plan
The implementation of G-ROCKS was carefully designed to ensure a smooth transition from
the planning stage to full implementation in the field. This phased approach focused not only on
technical development and data integration but also on user training and continuous monitoring
to optimize the platform's functionality. This allowed for early detection of potential problems
and ensured the system could adapt to evolving operational needs. By completing the
implementation within a 12-month, G-ROCKS could provide significant benefits in geotechnical
data management, occupational safety, and operational efficiency while ensuring that users
could operate with a stable and secure system.
Overall, the success of the G-ROCKS implementation will depend heavily on effective
coordination between technical development, user training, and ongoing maintenance. This
phased approach is justified by the need to ensure that the platform functions well throughout
the operational phase, from data collection in the field to data-driven decision-making. Thus, G-
ROCKS will be a very effective tool in supporting safety, risk management, and efficiency
improvement in the geotechnical and mining sectors. The following figure 13 is a roadmap
diagram for the implementation of the G-ROCKS Platform at PT. Borneo Indobara.
Figure 15. G-ROCKS Platform Implementation Roadmap Diagram
This figure 15 shows the development roadmap for a geotechnical integration system
designed to improve risk management in mining areas through key feature development and
phased implementation until 2026. The system includes features such as user management,
automated matrix calculations, interactive dashboards for real-time data reporting, and mobile-
based notifications and alerts. Development is carried out progressively in 9 stages, starting with
user and role management (Stage 1) through real-time sensor integration and AI-based
predictive analytics (Stage 10). Each stage adds new elements, such as geofencing features,
interactive data visualization, and technical repositories, while involving the system's
socialization and stabilization process. This approach allows for a structured and sustainable
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implementation, focusing on improving operational efficiency, risk management, and safety in
the field.
CONCLUSION
The conclusions in this research demonstrate the challenges in geotechnical information
distribution by identifying critical issues in the Man, Measurement, Method, and Machine
dimensions, which hinder efficiency and timely hazard management. Using Fishbone and Pareto
analysis, key stages with sigma values <2 - such as Viewed Information, Data Analysis, and Follow-
up Information - were prioritized for improvement. The proposed G-ROCKS system, which is
integrated with the DMADV framework, offers a comprehensive solution through a centralized
Command Center for systematic data analysis and a Mobile App for real-time notification and
geofencing. The implementation roadmap, divided into three phases, is progressing with the
launch of G-ROCKS 1.0 scheduled for February 2025. This research contributes to the
advancement of geotechnical hazard systems by integrating modern technologies and process
optimization, laying the foundation for future research on scalability, AI integration,
sustainability, and improved user-centered design.
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Copyright holder:
Seno Maris Utomo, Gatot Yudoko, Ridho Kresna Wattimena, Dradjad Irianto, Edy Wicaksono
(2025)
First publication right:
Asian Journal of Engineering, Social and Health (AJESH)
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