Process Improvement Proposal for the Distribution Management to

Reduce Lead Time Using 5S, SMED and Autonomous Maintenance

in a Plastic Company

Maria Alejandra Alamo Matos

, Ximena Fernanda Espiritu Gonzales

and Alberto Flores-Perez

Keywords: SMED, 5S, Autonomous Maintenance, Plastic Indutry, Lead Time.

Abstract: The plastic industry in Peru has grown by 4.5% in recent years, causing great competition among the different

companies that exist. In this regard, the most common problem in the industry is low productivity, which

causes companies to be unable to meet the lead time agreed with customers. Faced with these difficulties, this

study proposes the implementation of Lean Manufacturing tools, specifically Autonomous Maintenance,

SMED and 5S, seeking to eliminate waste and mainly reduce lead time. The results demonstrate the feasibility

of using these methodologies. An improvement of 88% was obtained in comparison with the current situation

that represents 70% of order fulfillment. This happens due to the increase in productivity to 86.83%, waste

reduction to 6.74% and increased equipment efficiency to 86.33%.

1 INTRODUCTION

In Peru, the plastic industry is considered to belong to

the non-primary manufacturing industry by “Banco

Central de Reserva del Perú.” In this country, the

industry has significantly grown by 4.5% in recent

years (Instituto de Estudios Económicos y Sociales,

2019), generating more than 650 thousand jobs

(Población Ocupada, Según Ramas de Actividad,

Tamaño de Empresa y Categoría de Ocupación,

2007-2020, n.d.). The article emphasizes the need to

accelerate production systems and the proper use of

resources in emphasized, since these produce

negative economic impacts (Fernández Marca et al.,

2020). Therefore, the results show that it is necessary

to increase productivity to guarantee order fulfillment

(Ames et al., 2019).

The problem, according to the literature, can

occur due to several factors such as low productivity,

high amount of waste, equipment downtime, among

others (Flores Barbarán et al., 2020), which leads to

the need to improve processes in companies in the

industry due to increased customer requirements

(Ribeiro et al., 2019). This problem has been noticed

https://orcid.org/0000-0002-6629-3331

https://orcid.org/0000-0002-2953-1783

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

in different studies worldwide. For example, a

company in the same industry in Portugal presented a

high number of complaints from customers due to

low performance, availability of equipment, low

productivity and employee autonomy (Ribeiro et al.,

2019). Another article from India found that orders

were not being met on time due to misuse of

resources, poor staff involvement, and inadequate

maintenance (Shukla, 2018). Therefore, it is shown

that companies that produce plastic products need

solutions for the different exposed problems.

On this basis, it is essential that these companies

seek to be more efficient in order to achieve the

planned results. For this purpose, a case was chosen

to demonstrate the problems of the plastic industry

regarding the delay in lead time orders due to low

productivity, poor equipment maintenance and high

percentage of waste, waste that generates monetary

losses of 7% of the utility from the study company.

Therefore, in order to provide a solution to the above,

an improvement model was proposed using Lean

Manufacturing tools specifically Autonomous

Maintenance, SMED and 5S. This improvement was

carried out with the support of projects that have been

Alamo Alamo, M., Espiritu Gonzales, X. and Flores-Perez, A.

Process Improvement Proposal for the Distribution Management to Reduce Lead Time Using 5S, SMED and Autonomous Maintenance in a Plastic Company.

DOI: 10.5220/0012055700003612

In Proceedings of the 3rd International Symposium on Automation, Information and Computing (ISAIC 2022), pages 807-811

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)

807

successful with similar difficulties as the case study

of Diana Fernandez and Karla Mostacero (2021),

which seeks to increase the capacity in their

production process, using 5S to standardize the order

and cleanliness, SMED to reduce their times, and

TPM to gradually obtain a system with zero

breakdowns (Fernández Marca et al., 2020). Finally,

there are very few scientific articles with relevant

information about the mentioned problem in the

industry, being the main motivation to carry out the

corresponding study.

This scientific article is divided into five parts,

which are Introduction, State of the Art, Contribution,

Validation and Conclusions.

2 STATE OF THE ART

2.1 Autonomous Maintenance

Autonomous Maintenance is one of the six pillars of

Total Productive Maintenance (TPM), which aims to

teach workers to keep equipment safe through

activities established in a schedule (Ames et al.,

2019). Likewise, this tool seeks that production does

not stop even when the machine faces serious

problems (Acharya et al., n.d.). On the other hand,

with the application of this pillar, the operators will

have the possibility of being in charge of the

maintenance so the maintenance technicians will be

able to use their time in more serious activities

(Fernández Marca et al., 2020).

2.2 Single Minute Exchange Die

(SMED)

The Single-Minute Exchange Die or better known by

its acronym SMED was developed by Shigeo Shingo,

who sought to reduce changeover times on machines

(San Antonio Ignoto et al., 2018). SMED is effectively

used to improve quality and accelerate lead time to

meet customer needs (Haddad et al., 2021). For its

implementation in an industrial company there are

seven steps, starting with the observation of the

current situation, followed by staff training, creation

of an equipment programming schedule, data review

on mold changeover times, data collection on

improvement times for later comparison, application

of the proposed improvements and finally, in the last

step the collection of information on the implemented

improvements, including the staff training (Cervantes

Esparza & Zorilla Briones, 2018). In addition, the

methodology is defined by four phases. In phase zero

there is no difference between the internal and external

operation of the setup. Phase one separates the internal

and external operation. Phase two convert internal

operations to external. Phase three apply the

improvement of all the setup operations (Antosz &

Pacana, 2018).

2.3 5S

The 5S tool was created by the Japanese engineer

Shigeo Shingo. This methodology combines five

steps which ensure that the environment is kept clean,

safe, and efficient (Ribeiro et al., 2019). The five

phases are called Seiri, Seiton, Seiso, Seiketsu and

Shitsuke, which in English mean Sorting (separate

what is not used), Organizing (assign a place for each

element), Cleaning (leave the environment in optimal

conditions), Standardization (standardize operations)

and Discipline (ability to do things while respecting

established guidelines) (Shahriar et al., 2022). The

application of this Lean Manufacturing tool is crucial

as it helps to achieve productivity improvements in

the work environment with less human effort,

equipment, space and time (Fernández Marca et al.,

2020).

3 CONTRIBUTION

3.1 Basis

For the proposal development to improve the lead

times of orders in the company of the plastic industry,

references of several scientific articles related to Lean

Manufacturing tools, mainly 5S, Single Minute

Exchange of Die (SMED and Autonomous

Maintenance, were considered. Compared to other

studies, this one focuses on the development of the

worker regarding the use and solution of machinery

failures. In addition, waste management proposal was

added. Next, the comparative matrix between the

causes of the proposed model and the state of the art

is shown below.

ISAIC 2022 - International Symposium on Automation, Information and Computing

808

Table 1: Comparative matrix of causes of the proposal vs.

State of the art.

3.2 Proposed Model

The proposed model is based on the implementation

of three tools, 5S, SMED and Autonomous

Maintenance in the production process to improve the

order fulfillment on time. At the same time, the

impact of the application of these will be positive on

productivity, equipment efficiency and the output of

defective products. Likewise, the model was

developed in three phases: diagnosis, proposal, and

implementation.

Figure 1: Proposed model.

3.3 Model Components

3.3.1

Component 1: Diagnosis

The first phase, called Diagnosis, was based on the

collection of the company’s historical data. Limits

were established with the help of the SIPOC tool,

Pareto and Ishikawa diagrams were applied to

determine, the main problem and its root causes, and

more precise causes were obtained with the 5 whys

tool. In addition, with the objectives tree it was

possible to have a broader view and thus, a better

analysis of the information.

3.3.2 Component 2: Proposal

The second phase, called Proposal, was based on the

tools chosen to be implemented. With the literature

review, it was possible to decide which tools were the

most appropriate for the case of study. It was

determined the use of 5S to reduce the number of

defective products, Autonomous Maintenance to

reduce failures in the company’s machines and

SMED to reduce downtime.

3.3.3

Component 3: Implementation

- 5S implementation

For the 5S application, it was divided into the stages

the Seiri (Sorting), Seiton (Organizing), Seiso

(Cleaning), Seiketsu (Standardize) and Shitsuke

(Discipline) to reduce the number of defective

products.

- Autonomous Maintenance implementation

The autonomous maintenance application was used to

reduce failures in the blow molding machine,

establishing schedules and training plans so that

operators act with knowledge in case of problems and

avoid unnecessary downtime.

- SMED implementation

To reduce the downtime due to low productivity,

SMED was applied. By following the seven steps of

this methodology, times could be reduced, as well as

increasing the process efficiency and reducing lead

times.

Finally with the use of the Arena software the

simulation of the implementation was carried out.

The results were evaluated by indicators.

3.4 Indicators

To measure the impact caused by the improvement

tools, four indicators were used to analyze the results.

They are detailed below.

3.4.1

Order Fulfillment

This is used to measure the number of orders

delivered in relation with the agreed date.

   

  

∗ 100 (1)

Process Improvement Proposal for the Distribution Management to Reduce Lead Time Using 5S, SMED and Autonomous Maintenance in a

Plastic Company

809

3.4.2

Overall Equipment Effectiveness

Provides insight of the machine efficiency

𝐴𝑣𝑎𝑖𝑙𝑎𝑏𝑖𝑙𝑖𝑡𝑦 ∗ 𝑃𝑒𝑟𝑓𝑜𝑟𝑚𝑎𝑛𝑐𝑒 ∗ 𝑄𝑢𝑎𝑙𝑖𝑡𝑦

(2)

3.4.3

Productivity

It allows to measure how productive a process is in

accordance with time.

   

   

∗ 100 (3)

3.4.4

Rework Level

It allows to know the number of reprocessed units

produced.

   

  

∗ 100 (4)

4 VALIDATION

4.1 Initial Diagnosis

It was determined in the initial diagnosis that there is

a technical gap in the order fulfillment. Currently, the

company under study complies with 70% of its

orders, compared to the general index of the industry

that represents 85% compliance. Therefore, in order

to increase productivity and the percentage of order

fulfillment, the main causes of the problem were

addressed: (a) insufficient maintenance, (b) output of

defective products, (c) inefficient employee. The

following are the results of the data obtained from the

current model and what we wanted to achieve with

the application of the proposed model.

Table 2: Average values of the indicators.

Indicators Current Objective

Order Fulfillment 70 % 85%

Overall Equipment

Effectiveness

(

OEE

)

68.24 % 85%

Productivit

69.05% 85%

Rework Level 9.81 % 6%

4.2 Validation Design and Comparison

with the Initial Diagnosis

For the validation design and comparison with the

initial diagnosis, two schemes were made. One of the

current model that represented the output process of

the bottles from the blow molding machine and its

output from the process as packages containing 300

bottles ready to continue to the next process. And

another off the proposed model containing the

implementation of 5S tools to reduce the number of

defective products, SMED to reduce downtime and

Autonomous Maintenance to reduce machine

failures. With the application of these tools, it was

also possible to reduce the number of processes and

resources compared to the current model.

4.3 Simulation of the Proposal

The model simulation was developed in Arena

software to validate the results and corroborate the

performance. The number of replicates was

determined in 330 times with the Input Analyzer

software wand the collected data. The proposed

model simulation is presented in Figure 2 below.

Figure 2: Diagram of the proposed model.

The simulation diagram shows the elimination of

activities that did not add value. At the same time, the

production work is only centered on the operator due

to Autonomous Maintenance and SMED.

Table 3: Actual indicators vs Improved situation.

Indicators Current Improvement

Order Fulfillment 70 % 88%

Overall Equipment

Effectiveness (OEE)

68.24 % 86.33%

Productivity 69.05% 86.83%

Rework Level 9.81 % 6.74%

The results obtained showed an 88% in the order

fulfillment percentage, verifying the effectiveness of

the 5S tools, Autonomous Maintenance and Single

Minute Exchange of Die implementation and

demonstrating the improvement of all the indicators

when applying them.

ISAIC 2022 - International Symposium on Automation, Information and Computing

810

5 CONCLUSION

The implementation of the model that applies the

Lean Manufacturing methodology allowed to

improve the productivity index by 17.78% and thus

an 18% increase in the order fulfillment on time.

Therefore, demonstrating the viability of the

improvement proposal and its possible application in

companies of the same industry.

In turn, it was found that the application of these

tools managed to exclude activities that did not

generate value, eliminate waste, and reduce time.

In the future, it is recommended to carry out a

good diagnosis and data collection to be able to

determine more easily the problem and its main

causes, and thus obtain more accurate results.

Likewise, to validate the improvement of process

optimization with the use of Lean Manufacturing

tools in different scenarios using other equipment

such as the injection molding machine.

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Process Improvement Proposal for the Distribution Management to Reduce Lead Time Using 5S, SMED and Autonomous Maintenance in a

Plastic Company

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