Lean Implementation on Production Process and Maintenance

Practice for Productivity Improvement

Nani Kurniati, Dewanti Anggrahini, Dwi Kusumaningrum, and Pantoki Ilham

Department of Industrial Engineering, Institut Teknologi Sepuluh Nopember, ITS, Surabaya, Indonesia

Keywords: Lean manufacturing, lean maintenance, manufacturing lead time, operation process chart

Abstract: Lean concept has been discussed extensively across many industries. As its approach to ensure overall

performance by a focus on delivering customer's expected value. Any activities within industries that don't

contribute to value the end product will consider as waste and need to be eliminated. The lean idea for the

Bogie production process useful to identify the potential improvement in production performance in terms of

manufacturing lead time (MLT) or cycle time. Carefully analyze the cause of waste may guide to address the

root cause. One of them is a maintenance problem. Therefore, the continuing lean implementation of

maintenance activities may lead to solving another root cause. It successfully showed the potential escalation

on MLT, about 20% reduced by considering the manufacturing waste. Further advantage and benefit may

gain more due to lean maintenance implementation, albeit the exact improve performance still need to be

detailed quantified.

1 INTRODUCTION

Lean concepts firstly proposed by Taichi Ohno in the

late 1940s. Toyota Production System showed

significant achievement in several areas, including

productivity and efficiency, as well as production

cycle time. The lean implementation relies on five

basic principles. Firstly, value identification defined

by the customers' expectations about the end product.

Second, mapping the process workflow within the

company involved in delivering the end product. It

will identify in what process the value has been

generated, include the proportion of processes that do

not cause to value. Third, disperse work into smaller

batches and visualizing the workflow, to ensure

continuous workflow and easily identify the possible

bottleneck and interruption. Fourth, establish a pull

system means optimizing the production capacity and

delivering a product based on actual demand,

ensuring no waste on resources. The last, encourage

all components of the company actively involved in

creating the continuous improvement program.

Bogie production consists of many processes. The

current situation detected in the shop floor was lack

of documentation both in production/machine

capability, workforce capacity, and many outcome

measurements include cycle time and production rate,

which is very important for providing the baseline

performance and detecting any obstacles. This

condition may cause any difficulty in addressing the

improvement program on production capability.

Bogie product of the company being studied is a

chassis or framework that carries a wheelset, and this

is a modular subassembly of wheels and axis that

attached to a train. At least two bogies need to be

assembled beneath the train. Moreover, the company

instructs to increase the capability of producing the

bogie to reduce the tardiness of product completion

and shipment, as well as to reduce the number of

rework products. Another issue identified in the

company related to maintenance activities that

responsible for restoring any machine failure back

into operation state. It triggered by the high frequency

of machine failure that causes corrective maintenance

instead of a preventive one. Downtime may effect

reducing availability and high inventory work in the

process. In the end, the same problems reveal in

reducing the number of Bogie production.

Therefore, this paper attempts to capture the

current production process to identify potential

improvement by reducing or eliminating the seven

waste on Bogie production. The lean approach has

been chosen to be implemented both in the production

process and maintenance activities, as the benefit of

the promise of lean implementation has reported

144

Kurniati, N., Anggrahini, D., Kusumaningrum, D. and Ilham, P.

Lean Implementation on Production Process and Maintenance Practice for Productivity Improvement.

DOI: 10.5220/0009424301440149

In Proceedings of the 1st International Conference on Industrial Technology (ICONIT 2019), pages 144-149

ISBN: 978-989-758-434-3

(Rohani and Zahraee, 2015; Madaniyah and Singgih,

2017). The combined lean implementation both on

production and maintenance at the same shop floor to

be expected can double the benefit and advantage of

lean. Some tools employed include Value Stream

Mapping (VSM), Operation Process Chart (OPC),

and Cause Analysis (CA).

2 RESEARCH METHODOLOGY

The lean implementation on the production process

called lean manufacturing, while implemented on

maintenance practice, becomes lean maintenance.

The steps taken were accommodating the five basic

principles of lean. Initially, the production process

needs to be clearly identified using Operation Process

Chart (OPC).

Value Stream Mapping (VSM) used to visualize

the information and material flow within a process,

followed by identifying the appropriate waste i.e.,

seven waste for lean manufacturing, eight waste for

lean maintenance. The third step is flowed the value

by mapping all the activities into three categories:

value-added activity (VA), non-value added an

activity (NVA), and necessary but non-value added

activity (NNVA).

The pull system brings to evaluate several

performance measurements i.e., manufacturing lead

time (MLT) for production and overall equipment

effectiveness (OEE) for maintenance. The final step

is continuous improvement by eliminating the waste

by audit, standardization, and identify the cause of

waste.

3 LEAN FOR BOGIE

PRODUCTION

There are 25 process routing in order to produce one

unit of bogie (called bogie set), that consists of two

bolsters and four side frame.

3.1 OPC and VSM of Bogie Production

The routing processes and its cycle time is provided

in Table 1.

Table 1: Process routing and its cycle time.

Process Cycle time (mins of

roducin

roduct

)

Core making 420

Mold making 240

Core settin

210

Melting 525

Pouring 80

Shake out 210

Cuttin

300

Swin

rindin

675

Hand grinding 600

MPI 1 150

Welding repair 1 640

Heat treatment

(normalizing)

505

Shot blast 285

Machinin

320

Finishing & gage

inspection

500

MPI 2 150

Weldin

air 2 245

Final inspection

(internal)

Assembly 180

Final inspection

(external)

240

Packaging 210

All the processes above done serially except the

first three processes conducted in parallel at the same

time. By categorize the activities during VSM into O

(operation), T (transportation), S (storage), dan D

(delay), the distribution of their VA, NVA, NNVA

frequencies are provided in Table 2.

Table 2: Process activity mapping.

The calculated MLT for bogie production is total

cycle time + transportation time = 675 mins + 20 mins

= 695 mins, or 208 hours, or 8,6 days.

3.2 Waste Identification in Bogie

Production

There is critical waste includes waiting and inventory.

The waiting data is given in Table 3 as follow:

Table 3: Process activity mapping.

Waitin

Time

(

mins

)

Waiting in mold making

ueue

180

Mold making wait core

making

180

Lean Implementation on Production Process and Maintenance Practice for Productivity Improvement

145

Meltin

wait core settin

315

Waiting for pouring until

acka

645

Total waitin

1320

Total waiting is 22 hours or 0.9167 days. Another

critical waste is transportation, consume 695 mins or

11,58 hours. While excess processing, transportation,

and motion also being identified. The defect product

was recognized into two types i.e., gas hole, crack,

shrinkage, and cold shut, as provided in Table 4.

Table 4: Waste defect.

Defect type Repair Probability

repair

Repair

time

(

mins

)

Gas hole,

cracks,

shrinka

Welding

repair 1

67% 640

Mold making

wait core

making

Welding

repair 2

33% 245

tempering 3% 127.05

Shrinkage

could shut

Re-

meltin

0,23% 31.275

The total repair time would be 646.721 mins or

17.38 hours.

3.3 Root Cause Analysis (RCA) for

Bogie Production

The following steps after waste identification are

finding the cause of waste by applying the RCA

diagram. For defect waiting, the appropriate RCA is

given in Figure 1. The root of the problem shows by

the circle symbol. From Figure 1, it can recognize that

one of the root cause for waiting is machine

breakdown. The historical data shows the proportion

of corrective maintenance is almost 80%, which

means the maintenance activities don't well planned.

This situation triggered to analyze the current

maintenance activities by using a lean maintenance

approach, which slightly different from the lean

manufacturing approach both on the waste category

and the value characteristics.

Figure 1: Root cause analysis of waste waiting

ICONIT 2019 - International Conference on Industrial Technology

146

4 LEAN MAINTENANCE FOR

BOGIE PRODUCTION

MACHINE

Machine failure characterized by downtime is

provided in Figure 2. Under the standard downtime of

5%, there are three critical machines that need to

address.

Implementation of lean maintenance follows the

framework proposed by Mostafa et al. (2015), as

depicted in Figure 3.

Figure 2: Downtime of machine production

Figure 3: Lean maintenance framework

4.1 Specify the Value, Value Stream,

and Flow of Value in Maintenance

Based on the waste of maintenance as proposed by

Davies and Greenough (2002), waste of maintenance

can be categorized into eight types as follows:

unproductive maintenance, waiting for maintenance

resources, centralized maintenance, poor inventory

management, unnecessary motion, poor maintenance,

ineffective data management, and under-utilized of

resources.

Based on the value stream maintenance mapping

(VSMM), among 51 activity of maintenance can be

grouped into 26 VA, 21 NNVA, and 3 NVA.

4.2 Pulling the Value of Maintenance

The performance of maintenance can be identified by

OEE measures. OEE determined by availability,

performance, and quality. The world-class

maintenance should have 85% OEE.

Availability rate calculated from uptime divided

by total loading time. The uptime is total loading time

subtract by downtime. Historical loading time,

planned unplanned downtime bring the value of

availability rate in 96.7%.

Performance measures how good the machine

produces the product determined by total actual cycle

time divided by total operation time. The historical

8,43%

8,30%

7,17%

3,31%

2,77%

2,48%

2,24%

1,49%

1,34%

1,15%

1,13%

1,07%

0,95%

0,94%

0,77%

0,46%

0,28%

0,27%

0,11%

SAND …

HANGER …

ARC …

TABLE …

HAMMER …

SAND …

HANGER …

CONTINUE…

ARC …

HEAT …

ROLLOVER …

MESIN …

IND F …

CONTINUE…

CONTINOU…

MESIN …

SAND …

% DOWNTIME

MACHINES

Lean Implementation on Production Process and Maintenance Practice for Productivity Improvement

147

data shows only 41.3% (under the standard minimum

of 60%).

The quality rate measures the proportion of good

product among all product produced by

manufacturing. Historical data shows a 100% quality

rate. This means all rework due to imperfect pouring

and casting was successfully resolved by the

machining process conducted after the cooling

process done.

Based on the value of the OEE component, the

demonstrated OEE is around 40.2% with containing

slightly increasing trend during 1,5 years of data. The

summary of losses is provided in Table 5 as follows.

Table 5: Six Big Losses.

Losses type Time (hours)

Equipment Failure 222.75

Setup and Adjustment 0.00

Idlin

and Sto

es Mino

1198.58

Reduced S

eed Losses 537.31

Process Defect 0.00

Reduced yield (start-up) 0.00

Based on Table 4, it can easily be recognized that

the largest portion of losses is idling-stoppage and

speed losses.

4.3 Continuous Improvement of

Maintenance

Instead, all the quantitative performance measures of

lean maintenance that already calculated, carefully

figure it out the existing condition shows some issue

as follows:

a. Availability of maintenance operator.

Responsibility to handle all the maintenance

tasks for all production facilities may expose

over the worked condition, especially when

several machines fail that need to be

maintained at the same time. Therefore, as the

concepts of TPM suggest that the machine

operator could be trained as the maintenance

crew since they can identify easily and rapidly

whenever the failure mechanism happened on

the machine where they operate.

b. Job safety analysis has been produced for

several parts of the machine and production

area. The health issue for the operator is also

important to concern.

c. The administration of maintenance activities

and data need to be carefully stored by the

system — technical maintenance library as a

database of maintenance useful for any

decision taken for maintenance.

d. Part warehouse needs to be managed in order

to easily quantify the available spare as well as

the spare part demand. Rearrange of the spare

part placement on the rack will help the

operator to find the spares need and minimize

the searching time.

e. Fault tree analysis (FTA) for each maintenance

waste will help the company to identify the

correct response to the problem reveals as well

as to prevent the same problem happened in the

future. The FTA for poor maintenance and

reduce speed loos was developed, as provided

in Figure 4.

Po or main ten a nce

Wrong repair/

maintenance

Wrong methode Wrong spre parts

Lac of understanding

from maintenance

srew

Lack of training

Lack of standard

cmpetency of

maintenance crew

Reduced speed losses

Inefficient

operator

Product not ready to

be processed

Unbalance operator

speed

Unstable iir pressure in

compressor

Lack of

standard in

work processes

Unrespon sive operator

to monitor macine

operations

Lack of

standard in

work processes

Figure 4: FTA of maintenance waste and looses

4.4 Designing the Overall Measure of

Maintenance Performance based

on the Lean Concept

By considering many factors in maintenance

performance suggested by Smith (2003), the

proposed key performance indicator for the

maintenance department as follows:

a. Monitor the OEE, by providing measurement

on MTBF, MTTR, MTBF of each machine

trough reliable failure data collection

mechanism

b. Monitor the percentage of the PM work order.

c. Develop an effective planning and scheduling

maintenance

d. Monitor store service level (% stock out)

e. Design and evaluate the proper training to

improve the skill of maintenance crew as well

as the standardization of maintenance task by

providing SOP for maintenance

f. Measure the overtime proportion of

maintenance crew for completing the job

ICONIT 2019 - International Conference on Industrial Technology

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g. Calculate the maintenance cost relatively

compare to the production rate.

5 CONCLUSIONS

Lean manufacturing successfully implemented to

manage the improvement of the Bogie production

process. The OPC highly contributes to shows several

processes that consume the largest production time.

Moreover, re-evaluate of NVA may drive to identify

the potential reducing time to escalate the MLT. From

the simulation of the production process, the potential

improved MLT is 6.9 days from the previous 8.63

days.

By carefully find the cause of manufacturing

waste, it brings to another problem of maintenance

activities. Therefore, deep analysis of lean for

maintenance activities brings the proposed idea of

improvement on standardizing the process of

maintenance, managing spare part inventory, and

identifying scheduled maintenance as well as

developing skill improvement programs for the

maintenance crew. All the suggested proposed

programs ensure the leanness of maintenance

activities that further will put more value for leanness

in the production process.

ACKNOWLEDGMENTS

This research partially funded by the Research of

Program Pengembangan Teknologi Industri (PPTI)

under Statement No 1538/PKS/ITS/2019 from the

Ministry of Research, Technology, and Higher

Education (RistekDikti).

REFERENCES

Davies, C. dan Greenough, R. M. (2002) “Measuring the

effectiveness of lean thinking activities within

maintenance,” Maintenance Journal, 3, pp. 8–14.

Madaniyah, R. N., & Singgih, M. L. (2017). Minimasi

Waste dan Lead Time pada Proses Produksi Leaf

Spring dengan Pendekatan Lean Manufacturing.

JURNAL TEKNIK ITS, 6(2), pp. 2337-3539.

Mostafa, S. et al. (2015) “Lean thinking for a maintenance

process,” Production & Manufacturing Research. 3 (1),

pp. 236–272.

doi: 10.1080/21693277.2015.1074124.

Rohani, J. M., & Zahraee, S. M. (2015). Production Line

Analysis via Value Stream Mapping: a Lean

Manufacturing Process of Color Industry. 2nd

International Materials, Industrial, and Manufacturing

Engineering Conference, 2, pp. 6-10.

Smith, R. dan Hawkins, B. (2004) Lean maintenance:

reduce costs, improve quality, and increase market

share, Plant engineering CN - TS155 .S635 2004.

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