Information System Design for Water Pump Production Monitoring

Muhammad Dachyar and Ivonny Aqiila Filza Adinda

Department of Industrial Engineering, Universitas Indonesia, Depok, West Java, Indonesia

Keywords:

Information System, Water Pump Production, Monitoring.

Abstract:

This study aims expedite the process of water pump production report by implementing an information system

monitoring the production process in recording production output so that it can meet the accuracy, integration,

and real time factors. The data was taken from an electronics company in Indonesia by means of observation

and interviews. Apart from interviews, the authors also collect literature from books, journals, and research

related to information system. The output of the discussion show that information system can help to reduce

reporting time from 102 minutes to 49.85 minutes or efﬁciency 47.83% and can achieve three stages of tech-

nology development in the digital transformation of the production reporting process, namely digitization, data

integration, and process automation.

1 INTRODUCTION

Provision of water of adequate quality for the commu-

nity has an important role in environmental or com-

munity health which has a role in reducing the num-

ber of sufferers of water-related diseases and plays a

role in increasing the standard or quality of life of

the community. As a developing country, Indonesia

is one of the countries that contributes 70-85% of op-

portunities for water, land, energy and iron produc-

tivity (Ahlberg, 2012). However, Indonesia has only

produced 222.59 billion m³ per year of water that has

been utilized. While the rest, namely as much as

468.72 billion m³ has not been fully utilized (Ober-

man et al., 2012). An electronics company in In-

donesia is a business actor that assists the govern-

ment in helping people have access to clean water

sources by producing water pump products. The elec-

tronics company has problems in the documentation

and recording of its production output. Documenta-

tion and recording of production output have not been

integrated between departments. Currently, the de-

livery of information related to problems in the line

is conveyed orally that make decision making from

management is slow. In this case the company needs

to integrate production output documents to facili-

tate the controlling function. Information systems can

help company operations such as integrating docu-

ments, avoiding input errors, speeding up document

search, and reducing document duplication (Mcleod

and Schell, 2007). The expectation is the research will

recommend information systems design as a form of

digital transformation to integrate all documentation

and recording of among departments production out-

put.

2 LITERATURE REVIEW

2.1 Water Pump Production

The production system is an arrangement of activities

or elements that are all interconnected to achieve the

ﬁnal goal (Gupta et al., 2009). In the water pump pro-

duction process, there are ﬁve processes, namely the

casting process, the forming process, the machining

process, the joining process, and the assembly (Swift

and Booker, 2003). To inﬂuence the innovation pro-

cess strategy in the production process, production

technology is needed to produce high quality, ﬂexi-

ble and efﬁcient products (Lianto et al., 2 02).

2.2 Information System

Information System is a system that has several com-

ponents that collaborate to collect, process, and save

data and information to help coordination, control,

decision making, problem analysis and visualization

in organization. Information system is divided into

four activities, namely Input for data collection, pro-

cess for managing data input results, output of the

information transfer process, and feedback to return

Dachyar, M. and Adinda, I.

Information System Design for Water Pump Production Monitoring.

DOI: 10.5220/0012447200003848

Paper published under CC license (CC BY-NC-ND 4.0)

In Proceedings of the 3rd International Conference on Advanced Information Scientiﬁc Development (ICAISD 2023), pages 227-232

ISBN: 978-989-758-678-1

227

data to users to help evaluate and correct the input

data (Laudon and P, 2014). There are three phases on

the implementation of information system; pre imple-

mentation, implementation, and post implementation

(Dachyar and Dewi, 5 05).

2.3 Digital Manufacturing Supply

Chain

Digital Manufacturing Supply Chain can be deﬁned

as real-time acquisition of data about the management

and decision-making of all supply chain business ac-

tivities, using digital information technology, and try-

ing to reduce supply chain risks and improve supply

chain performance through intelligent management

(Liu, 2 01). Most of the beneﬁts in manufacturing

from digital transformation can be summarized in ﬁve

groups; to increased productivity where development

and design processes, quality with high-resolution

measurements, the costs involved in data capture and

analysis of the manufacturing process, product cus-

tomization, and safety in the workplace where dan-

gerous tasks can be performed by robots (Albukhitan,

2020). Digital transformation implies technological

advances that support existing processes (Liu, 2 01).

Technology architecture contributes to the essential

requirements of IoT applications: Security, Adapt-

ability, Intelligence, Real Time, and Regulation Com-

pliant (Saragih et al., 2018).

2.4 Business Process Reengineering

Business Process Reengineering (BPR) is the funda-

mental rethinking and radical redesign of business

processes to achieve dramatic improvements in crit-

ical contemporary performance measures, such as

cost, quality, service and speed (Herzog et al., 9 10).

BPR in Manufacturing Supply Chain is a process of

modeling and documenting information architecture

can be a sufﬁcient starting point to ensure the suc-

cess of BPR (Nabelsi and Gagnon, 5 05). The BPR

approach and the use of RFID create efﬁciencies in

terms of time & cost (Bevilacqua et al., 2011). In

practice, there are many ways to do BPR. However,

there are 10 best practices; task elimination, task com-

position, integral technology empower, order assign-

ment, resequencing, specialist-generalist, integration,

parallelism, and numerical involvement (Mansar and

Reijers, 2007). Make a model using enterprise archi-

tecture (EA) notation is a strategic framework map-

ping of the new business process (Dachyar et al., 0

10).

3 METHODOLOGY

The water pump production process improvement

model uses a Business Process Reengineering ap-

proach to determine scenarios in the design of infor-

mation systems as a solution. The data used in this

research are interview with stakeholders, observation,

and production output documents. Activities will be

created into an As-Is model with enterprise architec-

ture (EA) notation using iGrafx software. This model

will produce output in the form of the total time of the

entire production reporting process. Based on these

results, an analysis of the problem regarding the waste

of activities will be carried out. After knowing the

problem, a new business process model will be de-

signed, namely the To-Be model. BPR best practices

are carried out to obtain alternative solutions in the

form of several scenarios. The next phase is the de-

sign of the information system, which is consist of 4

phases, namely database design, system design, sys-

tem usage ﬂow, and interface design.

4 RESULT

Figure 1 shows the current water pump production

output reporting process. In the last process, namely

receiving reports and recording reports into Excel

manually, it creates a vulnerability for human error,

which are:

• Writing numbers on production report paper can

be wrong due to mistakes in writing back from

targets that are on the computer to paper

• Error reading the number written by the leader re-

garding the number of units produced

• Error in entering data into excel

Figure 1: Production Output Reporting As-Is Model.

In addition, in the middle of the process, if there

is a problem, the leader must walk to the ofﬁce and

report the problem, then the section head will analyze

the problem so that decision making is a process that

has high barriers or a delay process. From the simu-

lation results on iGrafx (Table 1) it is found that the

average waiting time for this process is 0.42 hours.

When divided by the production takt time of 1 water

pump model, which is 33 seconds/unit, an opportu-

nity loss of 45 units/shift is obtained.

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Table 1: As-Is Model Simulation Result, Transaction Statis-

tic (Hours).

Count 1

Avg Cycle 1,75

Avg Work 1,33

Avg Wait 0,42

Avg Res Wait 0,00

Avg Block 0,42

Avg Inact 0,00

Avg Serv 1,75

From the results of the interviews, it was found

that the user requirements. The company wants an

accurate process, integrated data, and information that

can be accessed in real time. From this, three alterna-

tive solutions are obtained by implementing BPR best

practices, namely automating information recording

by implementing RFID so as to increase the accuracy

of recording the number of product outputs, Automat-

ing information recording by implementing a barcode

scanner so as to increase the accuracy of recording the

number of product outputs, and Designing a database

or information system by creating a production moni-

toring dashboard that can be accessed by all actors in

real time.

Based on these alternative solutions, possible

improvement scenarios that can solve problems in

recording water pump production output are as fol-

lows Table 2.

Table 2: Improvement Scenario.

Solution Automate record-

ing by imple-

menting RFID

Automate record-

ing by imple-

menting barcode

scanner

Database or in-

formation system

can be accessed

by all actors in

real time

Scenario

Name

Automated

recording system

with RFID chip

tag

Automated

recording system

with barcode

scanner

Monitoring sys-

tem with Power

Scenario 1 ✓

Scenario 2 ✓

Scenario 3 ✓ ✓

Scenario 4 ✓ ✓

The scenarios are modeled into the To-Be model

in Figure 2 for scenario 1 automated recording system

with RFID chip tag. The Automated Recording Sys-

tem with RFID chip tags is an automation of record-

ing information by implementing RFID to increase

the accuracy of recording the number of product out-

puts. The tools and software needed are RFID Tags in

the form of a microchip that contains a unique product

code, an RFID Reader to decode data on the tag, and

a Software System to process data from RFID Tags

and RFID reader devices.

Figure 3 for scenario 2 automated recording sys-

tem with barcode scanner. The Automated Record-

Figure 2: To-Be Model Scenario 1.

ing System with Barcode Scanner is an automation

of recording information by implementing a barcode

system so as to increase the accuracy of recording the

amount of product output. The tools and software

needed are the Omni Directional 1D Laser Barcode

Scanner.

Figure 3: To-Be Model Scenario 2.

Figure 4 for scenario 3 combination of automated

recording system with RFID chip tag and monitor-

ing system with Power BI. Automated Recording Sys-

tem with RFID chip tags and Automated Monitoring

System with Power BI is a database or information

system design by creating a production monitoring

dashboard that can be accessed by all actors in real

time. The tools and software used are RFID, SQL,

and Power BI.

Figure 4: To-Be Model Scenario 3.

Figure 5 for scenario 4 combination of automated

recording system with barcode scanner and monitor-

ing system with Power BI. The yellow boxes are pro-

cesses that are reduced time process from the As-Is

model, and the green boxes are additional processes

from the As-Is model.

Figure 5: To-Be Model Scenario 4.

The improvement scenarios built into the infor-

mation system design. Based on the results of in-

Information System Design for Water Pump Production Monitoring

229

terviews with companies and the results of the liter-

ature, several system requirements were obtained for

a stock monitoring system, production target achieve-

ment charts, and daily production monitoring which

functions to create databases and menus on the wa-

ter pump production dashboard. The details are de-

scribed in Table 3 System Requirements in General.

Table 3: Sysrem Requirements in General.

No Functional Require-

ment

Non-Functional

Requirement

1 User can login with

email and password

The system can

accomodate large

amounts of data

2 Certain users can

download certain docu-

ments

This information

system has a secu-

rity system

3 Certain users can view

certain dashboards

4 The system can manage

the access of interested

users

5 Certain users can input,

edit, and delete

6 Certain users can ac-

cess certain menus

7 The system can record

time and related users

whenever there is a

change in data in the

system

4.1 Database Design

First thing to design a database is by make entity re-

lationship diagram (ERD). ERD describes how the

conceptual design of the database model for reporting

the water pump production process (Btoush and Ham-

mad, 2015). The conceptual model of this database

is broadly divided into 8 parts, namely database for

motor casing production, database for core & die cast

motor production, database for pump casing produc-

tion, database for rotor production, database for stator

production, database for ﬁnishing parts, database for

semi-ﬁnished products, and a database for the ﬁnal as-

sembly. ERD of production output database is shown

on Figure 6.

4.1.1 System Design

The next step after determining the system to be built

and the requirements that have been determined is to

design related documentation. For system design, the

diagram used is a Use Case Diagram which shows

cases in the use of information systems. In database

design, Entity Relationship Diagram is used as a con-

Figure 6: ERD of Production Output Database.

ceptual model of the database and Relational Table to

design the logical model of the database and the last

is development planning using Data Flow Diagrams.

Use case diagrams are used to describe the activities

of actors or parties who will use the system against

the system (Kendall and Kendall, 2014). Use case di-

agram of daily production monitoring are shown in

Figure 7. There are 6 entities which are employee,

management, leader, RFID reader, barcode scanner,

and monitoring system.

Figure 7: Use Case Diagram of Daily Production Monitor-

ing (Barcode Version).

DFD shows the ﬂow of data in the system

which are input, process, output, and data store used

(Kendall and Kendall, 2014). Figure 8 displays a con-

text diagram on a water pump production monitor-

ing information system using RFID and barcode scan-

ner. The context diagram describes six external enti-

ties that will be related to the daily production mon-

itoring information system using a RFID reader or

barcode scanner, namely management, leader, scan-

ner, stock monitoring, production target achievement

charts, and daily production monitoring.

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230

Figure 8: Data Flow Diagram of Water Pump Production

Monitoring.

4.1.2 System Usage Flow

After designing the system which is the relationship

between the actors and the system, designing the

database and the relationship between each table in

the database, the last thing to do is designing activ-

ities for a system. In this study, activity diagrams

were used to provide an explanation for users about

how to use the system and for software developers to

make the system according to the user’s wishes. In

this study, activity diagrams were used to provide an

explanation for users about how to use the system and

for software developers to make the system according

to the user’s wishes (Kendall and Kendall, 2014).

4.1.3 Interface Design

The ﬁnal design stage is interface design. Interface

design is needed to make it easier for software de-

velopers to make it. Interface design also helps pro-

vide an overview of the results of the system design

to prospective users. In this study, the interface design

created on Microsoft Power BI with a desktop or web

computer display. Figure 9 shows the daily produc-

tion monitoring dashboard. In reporting problems in

the line of stages, the ﬁrst step is for the leader to click

the link or scan the barcode. Then, the leader can ﬁll

out the form. By submitting the form, management

will receive an e-mail notiﬁcation of a problem report

on the line. Then management can ﬁll in the deci-

sion of the problem. The results of these reports and

decisions will be immediately updated automatically

because they have been integrated into the daily pro-

duction monitoring information system.

4.1.4 Analysis

The improvement scenarios are analyzed by compar-

ing the processing time of the simulation results and

ﬁnancial projections for selecting scenarios as de-

scribed in Table 4. Scenario 3 produces the short-

est processing time with a signiﬁcant increase in

Figure 9: Data Flow Diagram of Water Pump Production

Monitoring.

changes, where the Automated Recording System

with RFID chip tags and Automated Monitoring Sys-

tem with Power BI added in scenario 3 provides a

greater change delta than the Automated Recording

System with RFID Chip Tags in scenario 1, Auto-

mated Recording System with Barcode Scanner in

scenario 2, and Automated Recording System with

barcode scanner and Automated Monitoring System

with Power BI in scenario 4. However, scenarios 1

and 2 only implement RFID chip tag solutions or a

barcode scanner that can be developed in combination

with other solutions in scenarios 3 and 4 to improve

ﬁnancial projections over a longer period.

Financially, scenario 3 requires the largest initial

investment cost because it is a combination of an

Automated Recording System with RFID chip tags

and an Automated Monitoring System with Power

BI. However, when compared to scenario 4 which re-

quires lower initial investment costs plus scenario 4,

it provides the largest net present value (NPV) among

the four scenarios over a longer period, in this case

within 12 months. The internal rate of return (IRR)

given is also the largest for scenario 4, which indicates

that by taking risks from large investment costs, com-

panies can obtain higher proﬁts as well. In addition,

scenario 4 is projected to have the shortest payback

period, which is 5.9 months.

Table 4: Comparison of Processing Times and Financial

Projection.

Scenario 1 Scenario 2 Scenario 3 Scenario 4

Process Time Be-

fore (Minutes)

74.85 75.33 54.78 55.15

Process Time Af-

ter (Minutes)

30.15 29.67 50.22 49.85

Change (%) 28.71 28.26 47.83 47.48

Total Investment

($)

T13,965 3,385 23,464 12,877

Net Present Value

($ Million)

C18,644 30,434 49,065 57,611

Interest Rate Re-

turn (%)

15.75 29.62 23.69 35.36

Beneﬁt Cost Ra-

tio

1,463 1.997 1.925 2.265

Payback Period

(Months)

7.7 6.5 6.8 5.9

Information System Design for Water Pump Production Monitoring

231

5 CONCLUSIONS

To speed up time spend on water pump production

output report, the company should implement infor-

mation system as a form of digital manufacturing sup-

ply chain. There are four strategies to speed up water

pump production output report. Scenario 1 is auto-

mated recording system with RFID chip tag. Scenario

1 can reduce cycle time of water pump production

output report by 30.15 minutes or 28.71%. Scenario

2 is automated recording system with barcode scan-

ner. Scenario 2 can reduce cycle time of water pump

production output report by 29.67 minutes or 28.26%.

Scenario 3 is a combination of automated recording

system with RFID chip tag and monitoring system

with Power BI. Scenario 3 can reduce cycle time of

water pump production output report by 50.22 min-

utes or 47.83%. Scenario 4 is a combination of au-

tomated recording system with barcode scanner and

monitoring system with Power BI. Scenario 4 can re-

duce cycle time of water pump production output re-

port by 49.85 minutes or 47.48%. Scenario 3 is the

best scenario in reducing cycle time water pump pro-

duction output report. However, the selection of sce-

narios depends on the company’s ﬁnances and needs.

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