Production Process Improvement Model Using TPM, Standardized

Work and 5S Tools to Reduce Waste in the Metallurgical Sector

Javier Pui Lung Wu Gamarra

, José Enrique Sandoval Tirado

†b

and Alberto Flores-Perez

Facultad de Ingeniería y Arquitectura, Universidad de Lima, Av. Javier Prado Este 4600, Lima, Peru

Keywords: Metallurgy Sector, Improvement Model, Standard Work, 5S, Total Productive Maintenance.

Abstract: The metallurgical industry has had a positive influence on Peru's economic development in recent years. On

the other hand, problems are observed within the sector under study, such as the high percentage of waste in

production processes, which leads to the generation of high costs for the various companies. Due to this, the

present research article seeks to propose engineering solutions focused on the reduction of wastes by means

of Lean Manufacturing tools within which TPM (Total Productive Maintenance), Standard Work and 5S were

integrated. Through the simulation in Arena software, the results of the research were extracted obtaining

indicators that represented an improvement in the analyzed system. The OEE (Total Equipment Effectiveness)

increased from 72% to 84%, the casting waste decreased from 3% to 2.6%, the percentage of waste in cuts

from 3% to 1.8%. Finally, the high scrap rate in the production process was reduced from 7.64% to 6.20%.

1 INTRODUCTION

The metallurgical sector has a very important impact

on the economic development of countries worldwide.

One of the most attractive non-ferrous metals is

copper, due to its applications in different types of

drawing, tubes, sheets, bars and sections (C. Ayala et

al., 2018). According to Euromonitor (2021), despite

the fact that in Latin America the export of copper as

raw and processed material has significantly

decreased, it is still a source of high-yielding income,

as it remains at around US$140 million. With respect

to countries outside Latin America, the metallurgical

sector stands out to a large extent in Spain, looking at

it from an economic point of view. This is due to the

fact that the country's industrial production is close to

40% and its gross value added is approximately 9.5%

of Spain's GDP (Gross Domestic Product) (Carbajo et

al., 2011, p.15).

According to the literature, for the problem

identified, regarding pyrometallurgical processes in

copper extraction, an approximate value of 2.2 tons of

slag per 1 ton of metal produced is estimated. Most of

the world's copper production (80-90%) comes from

sulfide ores that require high temperatures for

https://orcid.org/0000-0002-2918-4822

https://orcid.org/0000-0003-1374-6509

https://orcid.org/0000-0003-0813-0662

oxidation. However, the performance of these

metallurgical processes generates a large amount of

waste (Echeverry et al., 2016, p.60). Another literary

research, according to Kuznetsov (2017), refers to the

cutting processes and the precision of the machine

when performing such cutting, being able to cause

errors and waste due to dimensional accuracy,

configuration of the machined parts, poor roughness

and even vibrations during the cutting process

(Kuznetsov, 2017). Other factors that directly affect

the excessive production of shrinkage are failures in

visual quality control or quick measurements, which

occur in the various metal manufacturing processes.

Considering the technological advances and the high

precision machinery to which it gives access, human

error has been one of the most critical factors in terms

of quality control. According to Carrillo-Gutiérrez, T.,

Reyes-Martínez, R. M., Arredondo-Soto, K., & Solis-

Quinteros, M. (2021) 70% to 90% of the quality

defects in production systems are of this nature, which

causes the generation of waste due to rejected products

(Carrillo et al., 2021).

Due to the problems observed above, it is essential

to emphasize that companies in the metallurgical

sector in Peru should achieve greater efficiency in

812

Gamarra, J., Sandoval Tirado, J. and Flores-Perez, A.

Production Process Improvement Model Using TPM, Standardized Work and 5S Tools to Reduce Waste in the Metallurgical Sector.

DOI: 10.5220/0012056100003612

In Proceedings of the 3rd International Symposium on Automation, Information and Computing (ISAIC 2022), pages 812-817

ISBN: 978-989-758-622-4; ISSN: 2975-9463

 2023 by SCITEPRESS – Science and Technology Publications, Lda. Under CC license (CC BY-NC-ND 4.0)

terms of waste generation in the processes. One of the

problems identified is the slag losses produced in the

smelting process that cause a decrease in the yield of

the raw material and, on the other hand, the wastes

generated by the cutting and profiling processes are

recognized. These cause a percentage of monetary

losses of 8.53% of the company's profit in the case

study. Therefore, to solve the problem, an

improvement strategy was developed based on the use

of two Lean Manufacturing tools: TPM, Standard

Work and 5S.

This article will address seven parts, which are the

State of the Art, in which the concepts of Standard

Work, 5S and TPM obtained through the literature

review will be developed. In addition, the contribution

will be presented in which the proposed model, the

components and its indicators will be observed. Next,

a validation of the presented model will be presented,

with detailed findings. Finally, the results and

discussion will be presented.

2 STATE OF THE ART

For the present research, three typologies developed

from the preliminary literature review were

considered. These will be presented in the following

paragraphs.

2.1 Lean Manufacturing in the

Metallurgic Sector (Standardized

Work)

Standardized work is a very effective Lean

Manufacturing methodology when dealing with

processes that involve manual labor in sequential

processes. This is why we chose to analyze a study

conducted by Fin, J. C., Vidor, G., Cecconello, I., &

Machado, V. D. C. (2017) in which standardized work

is implemented in a medium-sized chassis assembly

line belonging to a company located in southern

Brazil. What stands out in this case study is the

thorough analysis of the production mechanism

separating the study of materials and tools from labor

and machinery. With this information, the minimum

and optimum speeds for the production of the product

were calculated, as well as the characteristics of the

machinery.

On the other hand, the different types of waste that

exist in the processes were determined. Through the

preparation of a production capacity sheet,

standardized routines for the operations were

determined and consolidated in a document that was

used in personnel training. As a result of the

implementation, after one month, assembly time was

reduced by 36 minutes, movements were reduced by

200 meters on average and by 5 stops to search for

spare parts and tools. In conclusion, cycle time was

reduced by 15%, operator movements by 34% and

downtime by 9.6%. One of the aspects to be rescued

from this case study is the continuous verification of

compliance with the objectives, as well as the focus on

waste reduction, since this can be focused on reducing

waste in production (Fin et al., 2017).

2.2 Lean Manufacturing in the

Metallurgic Sector (5S)

In this case, the 5S methodology was applied, dividing

the steps into their respective points to be dealt with in

their execution (M. Mau et al., 2019).

- Select: The "RED TAG SYSTEM" is used,

which consists in the use of 2 types of cards.

The red card for objects to be removed and the

yellow card for objects to be repaired or

changed.

- Order: Each tool must be in its respective

assigned place. In this case, 5 labels are used

that correspond to different categories (raw

materials, quality control materials, production

materials, Personal Protective Equipment and

stationery).

- Cleaning: The visualization technique is used

to have a better perception of the results. In

addition, a cleaning plan and a cleaning kit per

operator are proposed.

- Standardize: Procedures are established based

on the three previous stages, defining a cleaning

manual and production planning.

- Maintain: Staff is trained and audit plans are

carried out. Monitoring of the 5S system is

checked.

2.3 Total Productive Maintenance in

the Metallurgic Sector

(Mantenimiento Preventivo)

Considering another research conducted by Joshi, A.

G., & Bagi, J. S. (2015) a gray iron smelting plant

located in India. Through said study, important

analysis techniques are applied such as overall

equipment effectiveness (OEE), which is denoted

under the formula "OEE = Availability * Performance

* Quality"; maintenance and performance history

charts; statistical graphs, Pareto and the cause-effect

diagram. Such applied tools form a specific

methodology that can be used as a model.

Production Process Improvement Model Using TPM, Standardized Work and 5S Tools to Reduce Waste in the Metallurgical Sector

813

From this investigation, recommendations were

obtained for the smelting plant, which included a

change in the design of the pattern to provide adequate

ventilation, verification of the permeability and

moisture content of the sand and maintaining it at the

required values, among others. As a result of the

application of the methods, several studies were

conducted over a period of three months. These yielded

formidable results in which the quality indicator

increased from 0.96 to 0.98, the performance indicator

increased from 0.72 to 0.82, the quality indicator

increased from 0.92 to 0.97 and, finally, the OEE

indicator increased from 0.65 to 0.79 (Joshi, A. G. et

al., 2015).

3 CONTRIBUTION

3.1 Basis

Nowadays, the metallurgical industry has become

very competitive, both for medium and large

companies. This is why it is of utmost importance to

remain relevant in today's market, so it is necessary to

have control over the waste produced in the processes,

especially when working with large volumes.

Due to this, several methodologies and tools have

been investigated with the purpose of solving the

excessive production of wastes. Therefore, we have

chosen to use the TPM (Total Productive

Maintenance), Standardized Work and 5S

methodologies, which will allow us to comply with the

identified standards, benefiting both the customer and

the company.

Table 1: Comparison matrix of the proposed components vs.

State of the art.

Authors Planning

Waste

management

Maintenance

management

Dinis, C. J., et al.

(2019)

VSM x x

Assis & Carmona

(2021)

x x TPM

Mau, M., et al.

(

2019

)

x 5S x

Lu, J., C., &

Yan

, T.

(

2015

)

Standard

Wor

Madanhire, I., &

Mbohwa, C.

(2015)

x x TPM

Proposal VSM

Standard

Work & 5S

TPM

3.2 Proposed Model

The proposed model is based on three models:

Standard Work Model, 5S and TPM methodology.

These three methods will work in synergy focusing on

meeting the expectations defined above.

Figure 1: Proposed waste reduction model.

3.3 Model Components

3.3.1 Component 1: Problem Analysis

This was done with the help of a VSM (Value Stream

Mapping) matrix in which the percentage of waste

produced in the case study company was compared

with the standard obtained from the literature review.

From this analysis, a review was made of the most

critical processes and the following tools were

applied: FMEA (Failure Mode and Effect Analysis),

SIT (Systematic Interrogation Technique), 5 WHY's

and the Pareto Diagram, which allowed us to better

diagnose and validate the causes.

3.3.2 Component 2: Proposed Application

This component focuses on the application of the

proposed models in order to achieve or maintain a

continuous improvement in the processes.

The first model is the TPM, which will focus on

the efficiency and availability of the equipment to be

used, ensuring reliability and reducing the problem of

losses or waste (Hardt et al., 2021).

The second model is the standardized work model,

which will allow the generation of homogeneous

processes for the operators and their ability to generate

value in the required production times (Antoniolli et

al., 2017).

These models will work together with the 5S,

which will ensure an incremental improvement

focused on order and cleanliness, eliminating what

does not generate value to the company, minimizing

wasted time. For this, the management of personnel

ISAIC 2022 - International Symposium on Automation, Information and Computing

814

and work tools will be taken as key points for a

reduction of defective products (Rodríguez & Cárcel,

2019).

3.3.3 Component 3: Implementation

In this implementation phase, for a broader and more

convincing vision of what is to be achieved, a

simulation of the proposal will be carried out, where

the results obtained through the proposed indicators

will be analyzed, taking the company's current

situation as a point of reference.

3.4 Indicators

In order to evaluate the effectiveness of the integrated

model implemented and to manage a quantifiable

value of the results obtained, the following indicators

are proposed.

3.4.1 Availability

Expresses the capacity of the machines to be available

or in an active state to be able to carry out their

activities normally in the manner assigned to them.

(  )

 

∗ 100 (1)

3.4.2 Percentage of Waste

Identifies the amount of shrinkage generated

throughout the various production processes of any

type of copper finish.

(      )

   

∗ 100 (2)

3.4.3 Overall Equipment Effectiveness

Also known as OEE, it is an indicator used to measure

the productivity and efficiency of industrial

machinery in production.

𝐴𝑣𝑎𝑖𝑙𝑎𝑏𝑖𝑙𝑖𝑡𝑦 ∗ 𝑃𝑒𝑟𝑓𝑜𝑟𝑚𝑎𝑛𝑐𝑒 ∗ 𝑄𝑢𝑎𝑙𝑖𝑡𝑦 (3)

4 VALIDATION

A modeling was carried out using Arena software,

taking as inputs current data from the company Metico

S.A., from which probabilistic distributions were

obtained in order to generate simulations (initial

model and improved model) that allowed obtaining

indicators that show an improvement under an ideal

context. As a result, the loss rate indicator in the

production process was reduced.

4.1 Initial Diagnosis

The main problem present in the entire production

process is the high generation of waste, mostly due to

the poor performance of the operators when carrying

out their activities and the operation of certain tools

and machines in the process. These activities include

casting, extrusion, drawing and cutting processes.

Likewise, a poor organization of the working tools

was also observed, which makes manual tasks

difficult and generates downtime.

4.2 Validation Design and Comparison

with the Initial Diagnosis

The model was designed based on the production

process of the company under study. The model starts

with the reception of the batch, which will go through

a series of transformation processes, as mentioned

above, each process generates a certain amount of

waste that accumulates approximately 7.64%.

The first component that will help to reduce this

problem is preventive maintenance, which will focus

on the efficiency and availability of the equipment to

be used, ensuring the reliability to improve the OEE

% indicator, making the use of the machines in the

process more efficient. On the other hand, with the

implementation of standardized work, the percentages

of waste generated in the manual processes of the

operators are reduced, based on the generation of

homogeneous processes for the operators and the

measurement of the value generated per process. As a

result, a greater reduction was obtained in the cutting

processes, where more waste was emitted. Likewise,

the last component belonging to the 5S methodology

is the Red Tag System, which also has a positive

influence on the generation of waste by maintaining

the order and optimal location of the work tools, which

in turn reduces downtime. The management of

personnel and work tools for a reduction of defective

products, as well as the operation of the continuous

casting machine to reduce waste in the chemical

process, will be taken as key points.

In conclusion, with the implementation of the

mentioned methodologies, a clear improvement in all

the proposed indicators was observed, therefore, a

reduction in our main problem was also observed,

reaching 6.20% of the 7.64% that we had initially with

respect to the indicator of the amount of shrinkage

produced.

Production Process Improvement Model Using TPM, Standardized Work and 5S Tools to Reduce Waste in the Metallurgical Sector

815

Figure 2: Proposed simulation in Arena.

Table 2: Average values of the indicators

Identifier Average

Half-

width

Minim

Maxi

mum

Waste indicator

(Current in kg)

175.71 6.243 161.17

184.3

Waste indicator

(Improvement

in Kg)

142.58 4.826 133.4 149.5

System time

(Current in

min

)

238.63

0.1363

238

239.5

System time

(Improvement

in min

)

230.14

0.0901

229.59

230.5

Table 3: Measurement of the project implemented

Problem Current Target Improvement

High rate of

wastage

(production

proccess)

7.64% 5.24% 6.20%

Table 4: Measurement of the project implemented by

indicator.

Cause Indicator Current

Targe

Improv

ement

Inefficient

control in

the casting

process and

in manual

processes

such as

cutting

% OEE

72% 89% 84%

% foundry

waste

2.00

2.60%

% cut waste 3%

1.50

1.80%

Timing of

measuremen

ts are not

standardized

System time

(min)

239.58 223 230.57

4.3 Improvement - Proposed

Simulation

A simulation of the system was carried out using

Arena software, considering a confidence level of

95% and an average error range of 10% to calculate

the optimal sample size per activity. For the number

of replications, 30 runs were considered for the initial

model, and 55 runs were obtained for the improved

model.

An increase in OEE of 7% can be seen, this was

due to the TPM techniques implemented, among

which the use of the maintenance cards stands out, in

which a greater emphasis was placed on the cutting,

extrusion and profiling tools. On the other hand, the

time indicator in the system is one of the most

important if we talk about productivity. This aspect

was influenced by the adequate use of the 5s tool and

the standardized work, which allowed the reduction

in dead times, representing a reduction of

approximately 9 minutes per lot produced.

5 DISCUSSION

In order to ensure greater precision of the tools

applied, other production plants of the company were

analyzed, these being in the same metal-mechanic

industry. Using the segmentation technique, the case

was divided into sub-segments related to each other

by the type of manual and automated processes they

handle. Within these sub-segments, similar scenarios

to the main company were observed.

It is emphasized that the results obtained could be

improved through an analysis involving a larger

sample size. In addition, the model does not

accurately cover performance improvements in

automated machines, so this analysis could be

improved with a chemical study of the casting

techniques, with the aim of obtaining a better OEE

indicator.

ISAIC 2022 - International Symposium on Automation, Information and Computing

816

6 CONCLUSION

The TPM methodology was one of the tools that

helped in the optimization of the machines to be used

in the production process through techniques such as

maintenance cards oriented to three main processes,

cutting, extrusion and profiling.

On the other hand, by means of the Standardized

Work tool, the activities of each operator were

optimized, thus avoiding variation and standardizing

the functions to be performed on a daily basis, making

clear the role to be followed, preventing the risk of

error in any part of the process.

Likewise, the 5S tool, which was complemented

with the other tools, was the one that allowed the

reduction of downtime that was witnessed during the

processes to be performed, optimizing the production

time and organizing the work environment.

The integration of these techniques or

methodologies achieved a reduction in our main

problem, which is the high rate of waste in the

production process, representing a decrease of 7.64%

to 6.20%, in addition, improvements are also

observed in other processes such as cutting seeing a

reduction of 3% to 1.80% in waste, in the OEE of

72% improved to reach 84%, in waste in the casting

process from 3% to 2.60% and a reduction in time in

the system from 239 to 230 minutes approximately.

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