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DIGITAL TRANSFORMATION MODEL FOCUSED ON
PERUVIAN INDUSTRIAL FISHING
Pedro Martín Lezama Gonzales
National University Federico Villarreal, Lima, (Perú).
E-mail: plezama@unfv.edu.pe
ORCID: https://orcid.org/0000-0001-9693-0138
Ciro Rodriguez Rodriguez
National University Federico Villarreal, Lima, (Perú).
E-mail: crodriguez@unfv.edu.pe
ORCID: https://orcid.org/0000-0003-2112-1349
Francisco Manuel Hilario Falcón
National University Federico Villarreal, Lima, (Perú).
E-mail: fhilario@unfv.edu.pe
ORCID: https://orcid.org/0000-0003-3153-9343
Jorge Víctor Mayhuasca Guerra
National University Federico Villarreal, Lima, (Perú).
E-mail: jmayhuasca@unfv.edu.pe
ORCID: https://orcid.org/0000-0002-6465-4738
Recepción: 21/09/2021 Aceptación: 22/11/2021 Publicación: 14/02/2022
Citación sugerida:
Lezama, P. M., Rodriguez, C. R., Hilario, F. M., y Mayhuasca, J. V. (2022). Digital transformation
model focused on Peruvian industrial shing. 3C Tecnología. Glosas de innovación aplicadas a la pyme, Edición
Especial, (febrero 2022), 237-255. https://doi.org/10.17993/3ctecno.2022.specialissue9.237-255
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ABSTRACT
The objectives of this research work were to determine the degree of improvement in
the eciency of the digital transformation, the eciency in the extraction of shing and
the performance and the reference in the implementation of the digital transformation in
the processes of extraction of shing. A proposal for a model of digital transformation of
processes was shown that helps in the improvement of the shing production management
process based on time, resources, prots and the collection of information on the entry
and exit of the sheries. Now they must be responsible for taking conditions at the time of
carrying out the strategic method that will improve the production processes and be able
to control the objectives based on bar charts. The development of technological change
will allow monitoring alerts and obtaining control through devices within the reach of any
responsible user. In summary, the results were the product of the comparative analysis of
the last 4 years of shing, due to the changes between shing seasons
KEYWORDS
M-Learning, Digital Transformation Model, Operational Eciency, Eciency and yield
of crops and references.
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1. INTRODUCTION
1.1. DESCRIPTION OF PROBLEM
The FAO in its latest report stresses that “society is faced with the enormous task of providing
food and livelihoods for a population that will exceed 9 billion people by the middle of the
21st century, while at the same time solving the problem of the disproportionate eects of
climate change and deterioration in the state of the environment as a resource base” (FAO,
2018).
Fish is the largest segment of the food market. “sh consumption accounts for 16% of the
total amount of animal protein consumed in the world.”, (FAO, 2018). This assessment of
the global sh market is provided by Jürgen Vogele, director of the World Bank’s Agriculture
and Ecological Services Department.
Industrial shing despite COVID 19, contributed 1.5% of GDP in 2020, Fishing industries
manage their processes using SAP as the main ERP, however, the extraction process is
controlled through customized developments (web and mobile applications), having a delay
in data integration, and therefore in decision making.
These industries also do not have an end-to-end management of the extraction process,
they only focus on complying with the quotas granted by PRODUCE (Peruvian shing
regulator), sometimes causing overshing and threatening sh stocks, especially anchoveta.
1.2. ADAPTING TO TECHNOLOGICAL CHANGE
Emerging technologies, leveraging the ubiquity of cell phones and tablets, cloud computing,
blockchain, have the potential to contribute to data collection. Automating and empowering
data processing and analysis, employing business intelligence and analytics tools facilitate
the communication of results to relevant stakeholders (Mnatsakanyan & Kharin, 2021).
Technology can also be used to expand the distribution and accessibility of data to decision
makers, enabling them to optimize shing based on the best available information and
transforming unidirectional ows of information (eet to manager) into a collaborative and
mutually benecial cycle of data collection, synthesis and sharing.
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Adapting organizations from siloed organizational approaches to process-oriented,
indicator-based management, agile and value-oriented approaches are objectives that have
not yet been fully implemented in shing companies.
The digital transformation allows a gradual change in shing companies, allowing an
eective use of new technologies and their progressive adaptation in the organization.
1.3. OBJECTIVES
• Determine the degree of improvement in operational eciency (vessel use, fuel
use, cycle time) by implementing digital transformation in harvesting processes.
• Determine the degree of improvement in harvesting eciency (quota advancement,
sh quality, quota compliance per shing trip and per season) by implementing
digital transformation in harvesting processes
• Determine the degree of improvement in performance and benchmark (top 6
industrial shing companies) by implementing digital transformation in harvesting
processes.
2. MATERIALS AND METHODS
In the research “Opportunities to improve sheries management through innovative
technology and advanced data systems” provides an overview of the current status and
challenges of technologically advanced data systems in the sheries extraction process, and
proposes a solution to guide greater use of technology, with the aim of improving sheries
performance (Bradley et al., 2019).
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Figure 1. Conceptual diagram of shery-dependent data collection systems using traditional systems (top) and
the use of high technology (bottom).
Source: own elaboration.
2.1. PROPOSAL DEVELOPMENT
Next, we will show the conceptual diagram of the proposed digital transformation model
based on the improvement of the management process by indicators.
a. Digital transformation model proposal
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Figure 2. Proposal of the digital transformation model.
Source: own elaboration.
b. Description of the digital transformation model
The following table shows the respective summary of the digital transformation model:
Table 1. Responsibilities dened in the digital transformation model.
RE
EXTERNAL RESPONSIBLE.
It is the maximum responsible for dening the terms of the
shing season. Includes authority and veto right.
RI
INTERNAL RESPONSIBLE.
Responsible for dening the daily strategy that the organization
will employ in the extraction of anchovy. (R)
MAC
MONITORING ALERT AND CONTROL.
Is the maximum responsible in the control of the fulllment of
the goals and alerts the casuistry found every day in the
different mobile devices, tablets, web applications and
blockchain. (A)
Source: own elaboration.
Asks of the persons in charge
• RE is responsible for:
• Evaluating whether the sea state is conducive for shing.
Ministerio de la
producción
Denir Hoja de ruta
de la temporada
Planes
Denir planes de la
temporada (3 escenarios)
(Tn por Día, Num Viajes,
Combustible, escenarios,
planes, tiempo ciclo)
Evaluar Faena Descarga
Evaluar
Embarcaciones
Operativas
Zarpar al mar, calar
e iniciar la captura
Llevar la pesca
al puerto
Monitoreo y control
Monitorear y
Controlar la Faena
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• Dening the date on which the two shing seasons begin.
• Dening the number of days of operation.
• Dening shing quotas.
• Dene the size of the shery.
• RI is responsible for:
• Directing the evolutionary strategy of the daily shing.
• Carrying out shing plans.
• Carrying out fuel plans.
• Making the shing chronogram.
• Dene the sea route.
• MAC is responsible for:
• Monitoring fuel consumption.
• Monitoring the capacity of the vessel.
• Monitoring the quality of the catch.
• Alerting long unloading times.
• Alerting long waiting times to set sail. o Alerting long waiting times to set sail
o Alertinglong waiting times to set sail.
Detail of the tasks
Assessing the state of the sea
The Peruvian Ministry of Production carries out an evaluation of the state of the
Peruvian sea and denes the areas reserved for artisanal and industrial shing.
Dene season start date
The Ministry of Production denes the start date of the season after the exploration
of the Peruvian sea where it is veried that it is in conditions of exploitation. This
procedure is carried out twice a year, in the Peruvian sea there are two extraction
seasons.
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Dene Quota and magnitude of shing
The Ministry of Production denes the shing magnitude after the evaluation of the
Peruvian sea. This magnitude allows the rational exploitation of these hydrobiological
resources.
Dene days of operation
The ministry of production denes the days of the season allowing the rational
exploitation of these hydrobiological resources.
Dene evolutionary strategy
The organization denes a exible evolutionary strategy for each shing day because
shing is volatile. It takes into consideration the three shing plans, fuel plans, vessel
conditions, trip schedules, waiting times for unloading the catch, the time it takes to
unload the catch, and the time it takes to wait before setting sail.
Dene Fishing Plans
The organization denes three shing plans, which allows you to visualize each day
the status as the vessels report (favorable plan, intermediate plan, unfavorable plan).
Dene Fuel Plans
The organization denes the fuel plans allowing you to make the plans exible
among the vessels according to their daily consumption and how much they have
shed during the season.
Make the trip schedule
The organization denes the trips that the boats will make according to the weather,
sea temperature and the shing season they are in. To make the schedule more
exible due to navigation setbacks, GPS data is taken from the boats.
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Dening the maritime route
The organization denes the shing route in the areas where the Ministry of
Production allows it, taking into account historical data and experience of the eet
when dening the route where the anchoveta shoals are found.
Monitoring fuel consumption
The organization monitors the daily consumption of each vessel and the capacity
of the vessel’s hold. It analyzes fuel consumption per ton shed and distributes the
information on the maritime route taken by the vessel so that the evolutionary shing
strategy can be redened.
Monitor the vessel’s hold capacity.
The organization monitors the free space of the vessel’s hold, if the quantity shed is
appropriate the RSW (refrigeration) is used due to the higher fuel consumption, but
also ensures the quality of the anchoveta. Likewise, the sensors in the hold calculate
the tons caught.
Monitoring the quality of the catch
The organization monitors the quality in which the anchoveta arrives at the port,
dividing it into standard, prime and super prime. When a vessel arrives and lls more
than 60% of its hold, it is decided to use the cold system (RSW) to maintain the
highest quality.
Monitoring of shing zones
The vessels have sensors, GPS and satellite communication, allowing to know the
areas with schools of anchoveta, this allows to alert better shing areas than those
drawn at the beginning of the season in the schedule of trips, to comply with the
shing plan.
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Alerting of waiting time for unloading
The organization monitors the waiting times for unloading in the ports and can
divert the unloading in another port if it is not favorable.
Alerting of unloading times
The organization monitors vessel unloading times, sensors in the port unloading area
send an alert to the vessel when unloading is completed and the actual tons unloaded
at the port is declared.
Alerting waiting times for departure
The organization monitors the time it takes for vessels to depart after anchovies have
been unloaded.
Relationships of tasks and responsibilities
Table 2. Process tasks and their relationship to responsibilities.
PROCESS TASKS RI MAC
Dene shing plans in three tonnage scenarios R/A I
Dene fuel consumption plans R/A I
Dene the maritime shing route R/A I
Make the shing trip schedule R/A I
Monitor fuel consumption I R/A
Monitor vessel's hold capacity I R/A
Monitor the quality of the catch I R/A
Monitor shing zones I R/A
Alerting long unloading times I R/A
Alerting long waiting times to set sail I R/A
Alerting long waiting times for unloading I R/A
Source: own elaboration.
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3. RESULTS
a) Fishing extraction results for the last 4 years
The analysis is a comparison of the result of the last 4 years of shing, due to the changes
in the weather between the rst and second shing season, the analysis is divided in two:
Season-I and Season-II of the last 4 years.
Progress of tons shed
Figure 3. Tons shed advances.
Source: own elaboration.
According to Figure 3, the following was observed:
• In the last 4 years, the goal was reached with the exception of 2017, which only
reached 80.9%, narrowly missing the minimum established of 80%. The trac
light for the years 2019, 2018 and 2017 is the comparison with the year 2020 and
the average of the 3 years, which is in compliance with what was established.
• In the year 2020 it is observed how the target of 407,813TN (tons) was met and
exceeded.
• The bar graph shows the amount of tons shed. Each year is dierent due to the
quota assigned by the Peruvian Ministry of Production.
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Fuel consumption
Figure 4. Fuel consumption.
Source: own elaboration.
Fuel consumption GL/TN
Figure 5. Fuel consumption GL/TN.
Source: own elaboration.
According to Figure 4 and Figure 5, the following was observed:
• Fuel consumption in 2020 is 1.845 million gallons, which is below the consumption
of previous years; however, fuel consumption is linked to the quota that the
company must sh, which can be seen in the advance graph of tons shed.
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Advancement of vessel performance
Figure 6. Advancement of vessel performance.
Source: own elaboration.
According to Figure 6, the following was observed:
• Increasing performance in 2020 compared to previous years.
Analysis by vessel size
The last 5 years of the shing season-I are observed.
Figure 7. Report of the last 5 years of the shing season-I.
Source: own elaboration.
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According to Figure 7, the results of the digital transformation are seen in 2020, we visualize
a slight reduction in cycle time.
Tons shed for the season – II
Figure 8. Season progress - II in tons of sh caught, own elaboration.
Advancement of vessel performance
Figure 9. Vessel performance reportown elaboration.
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Fuel consumption
Figure 10. Fuel consumption report.
Source: own elaboration.
Fuel consumption GL/TN
Figure 11. GL/TN Fuel Consumption Report.
Source: own elaboration.
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Analysis by vessel size
The last 5 years of the shing season-II are observed.
Figure 12. Analysis report by vessel size.
Source: own elaboration.
Next, we are going to show the dictionary of key words regarding the shing process:
• Cycle time: It is the average time it takes for a vessel, waiting in port, unloading the
catch and the time it takes to set sail again.
• Number of trips: The number of trips made by the vessels as a whole.
• Hold capacity: The storage capacity of the vessels as a whole, expressed by the
number of trips.
• Fuel consumption Gl/h: It is the fuel consumption per hour of the vessels.
• Fuel consumption Gl/TN: Fuel consumption per tons shed.
4. CONCLUSIONS
An improvement in operational eciency was increased through the digital transformation
in the collection processes, since it reached an increase in the last 4 years with a normal
margin of 80.9%. In the year 2020 the objective was achieved and the margin of 407,813TN
was exceeded. In addition, there is a bar system that shows the amount of catches obtained
during the year, observing the development and progress of Peruvian productions.
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Harvesting eciency was improved through the application of digital transformation in
harvesting processes as there was moderate consumption with the bar platform evaluating
the harvesting margin of sh for 4 to 5 years, achieving the objective as a point of
improvement. within marine production.
A lower consumption of 1,845 million gallons could be obtained in reference to previous
years due to the eectiveness of the platform that was able to evaluate the points in favor
for production from the production analysis to the unloading times and waiting for delivery
of the products. Sea products.
There was a total improvement in performance and reference based on the implementation
of digital transformation in the collection processes with a margin of 70.37% in 2020- I,
46.55% in 2020- II, a higher rate than expected allowing invest in dierent resources that
can help the production processes of the harvest based on dierent exible techniques to be
able to have shing processes based: fuel, ship conditions, unloading time and sailing time,
a lot of criteria must be considered in order to be able to have the highest eectiveness in
the production method.
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