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Effective Preventive Maintenance Scheduling: A Case Study

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Maintenance is an important system in operation. In an era where industries are focusing on 24 hours operation to maximize production, machines are pushed to its absolute limits to cope with this demand. As utilization increases, the rate at which the machine parts get worn out increases thus the frequency of failure increases rapidly. To combat this problem and ensure that machines continue to operate at its optimum, maintenance work is carried out. One of the branches of maintenance technique which is carried out to prevent occurrences of failure before it happen is known as Preventive Maintenance (PM). However, performing PM may not be as easy as it requires great co-operation from the maintenance, production and management departments. This paper is written to study the aspects of effective PM and to analyze the causes of inefficient PM activity in a case study company and its implications. Another important approach taken is to investigate the causes of machine downtime by performing a root cause analysis. Affinity diagram was formed to highlight several issues with implementation of PM and a further analysis using Tree Diagram enabled to generate possible solutions. The findings of this provides prove that separating the machines into critical and non-critical categories, each having a different priority level is a crucial step towards solving the issue at hand and ensuring the reduction in downtime occurrence in addition to reducing the workload of the technicians.
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Effective Preventive Maintenance Scheduling: A Case Study
Hasnida Ab-Samat, Livendran Nair Jeikumar, Ernnie Illyani Basri, Nurul Aida Harun
and Shahrul Kamaruddin
School of Mechanical Engineering
Universiti Sains Malaysia
Engineering Campus, 14300 Nibong Tebal, Penang, Malaysia
Abstract
Maintenance is an important system in operation. In an era where industries are focusing on 24 hours operation to
maximize production, machines are pushed to its absolute limits to cope with this demand. As utilization increases,
the rate at which the machine parts get worn out increases thus the frequency of failure increases rapidly. To combat
this problem and ensure that machines continue to operate at its optimum, maintenance work is carried out. One of
the branches of maintenance technique which is carried out to prevent occurrences of failure before it happen is
known as Preventive Maintenance (PM). However, performing PM may not be as easy as it requires great co-
operation from the maintenance, production and management departments. This paper is written to study the aspects
of effective PM and to analyze the causes of inefficient PM activity in a case study company and its implications.
Another important approach taken is to investigate the causes of machine downtime by performing a root cause
analysis. Affinity diagram was formed to highlight several issues with implementation of PM and a further analysis
using Tree Diagram enabled to generate possible solutions. The findings of this provides prove that separating the
machines into critical and non-critical categories, each having a different priority level is a crucial step towards
solving the issue at hand and ensuring the reduction in downtime occurrence in addition to reducing the workload of
the technicians.
Keywords
Preventive Maintenance, Machine Downtime, Scheduling, Root Cause Analysis, Affinity Diagram, Tree Diagram
1. Introduction
To cope with the tough competition in manufacturing industries, companies have invested in highly automated
production system with excellent equipment. In order for the companies to sustain their hold in the global market,
full utilization of equipments are vital in order to maintain the production operation thus leading to the economical
sustainability as well as maximization of company profit [1]. When an unplanned downtime occurs due to machines
or equipment failure, this will disrupt the production operation. It would be very expensive to revise the production
plan in an emergency situation, and also causes lower product quality and variability in service level. Therefore,
maintenance system plays a crucial role in order to ensure the whole system runs efficiently and effectively [2].
Maintenance is one of the main functions in the manufacturing environment as it more likely to sustain the
performance of equipment and improve the operations efficiency in manufacturing plant. Even though maintenance
is a non-value added process in industry, it is undeniable that maintenance plays a major role in asset management
process. Maintenance has been mostly practiced in industries as it gives benefits in term of profit to the company
with customer satisfaction. Maintenance which is also known as a profit generator activity, a method to relate with
other operation functions as well as to ensure the availability, reliability and safety of all equipment in the plant [3].
The company will gain higher profits through the safety of the equipment and undisrupted production system which
optimizes cost, quality and throughput.
The performance of maintenance operations becomes the crucial issue in company or operation plant. Maintenance
operation does not only focus on repairs and spare part replacement activities, is also plays a big role as it influenced
the performance of maintenance work. Thus, the scope of maintenance management should cover every stage in the
life cycle of technical system including plant, machinery, equipment and facilities such as specification, acquisition,
planning, operation, performance evaluation, improvement, replacement and disposal [4]. The main problem faced
in this case study is the downtime still occurs even though after maintenance activities are carried out. Therefore, the
available schedule of preventive maintenance (PM) needs to be simplified.
The main aim for this paper is to reduce the planned downtime for PM by analyzing and improving the available
schedule that is employed in the case study company. Therefore, after identifying the maintenance activities applied
Proceedings of the 2012 International Conference on Industrial Engineering and Operations Management
Istanbul, Turkey, July 3 6, 2012
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in the company and analyzing the failure rates occurring in the production operation, the analysis is performed in
terms of management tools and techniques to relate the entire criterion that had been identified before. Thus, the
main objective to simplify the PM schedule is achievable. Based on data gathered, the pattern of the failures based
on the previous month’s downtime can be studied. Hence, more attention is given to the critical downtime machines
in the cluster and analysis is done using maintenance management tools and technique. This should help to reduce
downtime from recurring in the company’s plant.
This paper is written to study the effectiveness of PM and how it functions in manufacturing system. In particular,
this paper is structured in few sections and subsections. In the introduction’ section, overviews of problems faced in
maintenance are firstly elaborated before the maintenance technique is introduced. The implementation of PM is
elaborated in the following section. Next section organized and elaborated the PM Planning and Scheduling
Framework. The following subsection including data analysis, PM Planning Model and PM Scheduling Model are
discussed according to the case study in the company. Maintenance Schedule analysis is discussed in Section 4. To
show practical side of PM, suggested improvement are put forward in final section before conclusion.
2. Implementation of Preventive Maintenance (PM)
According to [5], corrective maintenance and (CM) preventive maintenance (PM) at time intervals are the most
common maintenance techniques. CM is defined as a fire fighting approach where equipment is allowed to run
without interruptions and maintenance activities are conducted only when equipment fails. It requires minimum
number of manpower and money spends to monitor the condition of equipments [6]. However, the downside is high
maintenance cost will be required when any catastrophic failure happen. On the other hand, PM is a basic
maintenance technique which is usually applied in manufacturing environment in order to facilitate the production
flow as well as enhancing the equipment efficiency. PM usually relates to schedule with fixed time interval that is
done daily, weekly, monthly or some other predetermined intervals. The use of performances interval is to
implement preventive task when needed. Usually when applying PM, maintenance activities are planned and
scheduled based on equipment’s requirement and historical data of failures. The planned activities involves the
documented maintenances task, labor resources requirements, parts and material requirements, duration to perform
task and also other technical references related to equipment. The activities are organized according to work’s
priority, the work order, labor resource availability, duration to perform task as well as planning of parts and
materials [7].
PM plays a crucial role in planning an effective maintenance schedule which can be incorporated with production
scheduling, so that this will lead to the efficiency and effectiveness in manufacturing system. Therefore, it is
essential that production planning and PM activities can be carried out in an integrated way in order to avoid the
failures which causes the need to do re-planning. Nevertheless, there are a lots of problems occur during
implementation of PM. For instance, the overlapping between PM planning and production scheduling. The issue of
integrating both areas is highlighted due to its importance in the current highly competitive environment. Thus, this
will lead to the other problems that influence in operating system such as production flow, set up times, cause
downtime, increase the waste and the deterioration of equipment [8].
“Prevention is better than cure” should be applied in solving maintenance problems in manufacturing environment
as PM activities should be done properly to avoid consequences of inefficient production scheduling and PM
planning. In particular, the manufacturing data should be employed in implementing PM, thus will help to facilitate
the production flow. As PM been carried out with good decision making in manufacturing facilities, this will lead to
restore the production line to an ‘as-good-as-new’ status [9]. A proper PM schedule should be conducted wisely
according to the planning, so that, the flow of production and PM activities can be carried out well. Thus, this will
enhance the efficiency of production output without having any difficulties regarding equipment failures or
downtime.
Based on the facts on PM discussed earlier, a case study was conducted in a semiconductor company situated in
Penang, Malaysia. The company which has been established since 1994 is equipped with highly automated state-of-
art facilities and leading technologies in manufacturing flexible printed circuit (FPC). The company comprises a full
range support and services from circuit design, prototype fabrication and mass production up to flex assembly. Most
of the product produce in this company is basically in form of panel or roll. Some of panel and roll produced in
either single sided or double sided. The processes of manufacturing of FPC consist of several operations. The
production operation of manufacturing high quality of FPC can be divided into four clusters. Those clusters are
Circuit Formation (Cluster 1), Circuit Protection (Cluster 2), Finishing (Cluster 3) and Back End (Cluster 4). Each
cluster has its own sections according to the associated processes.
For this case study, the improvement of PM was conducted, focusing on the Circuit Formation Cluster which is
cluster 1. This cluster comprises three sections known as wet process, imaging and post treatment as shown in
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Figure 1. From this figure, it can be comprehended that the processes in this cluster starts with the Imaging process
followed by the Wet-Process and ends at Post Treatment.
NODE: NO.: 1A0 TITLE: CLUSTER - CIRCUIT FORMATION
A1
IMAGING
A2
WET PROCESS
A3
POST
TREATMENT
Panel
Dry
film
Roll
Temperature
Pressure
UV
light
counter
Roller
speed
Machine
specs. &
stds.
Chemical
(H2O2, HCl,
CuCl2,
NaOH, soft
water)
UV light
Temperature
Operators
Machines
(Ovac,
Riston
Manual,
Jiann Haur,
Baking
Oven,
Shinkey
Solder
Mask)
Tools
(UV
light,
roller) pH
level
Machine
specs. &
stds.
Conveyor
speed
rpm
Operators
Tools
(pump,
generato
r,motor,
roller)
Machines
(Anti-
Tarnish
Machine
(OSP
No.1),
HMS,
Fujikiko)
Imaged panels & rolls
Developed &
etched panels/rolls
Temperature
pH
level
Machine
specs. &
stds.
Conveyor
speed
rpm
Chemical
(AD 488,
MEDRITE
808) Tools
(pump,
generato
r,motor,
roller)
Machines
(Sunlux
Post-
Treatment)
Cleaned
panels
Operators
A0
Material Issue
A4
Cluster 2 - Tool
Circuit
Protection
Figure 1: Processes in Circuit Formation Cluster
Basically, PM can be optimized as the machines have been clustered into the group of machines. This will lead to
the ease of maintenance activities, and reduce the workload carried by maintenance staff. In the case study company,
the production floor of manufacturing FPC board consists of 109 machines with only 8 technicians for maintenance
work. The technicians who are responsible according to four clusters are also responsible for the maintenance of
company’s equipment like air-conditioners and lamps. The working hour for the personnel in the company is 12
hours/day. But, the few number of maintenance staffs that are responsible for each cluster usually lead to inefficient
PM planning. Furthermore, the company always faces major and minor problem of breakdown. For major
breakdown, most of the machines need to undergo maintenance for more than 2 hours whereas the minor ones take
less than 2 hours. This major problem can be the main attention to the PM in order to reduce the breakdown in
manufacturing facilities. Thus, this contributes to the improper conducted PM scheduling even though it has been
done in predetermined time. Therefore, proper scheduling should be proposed based on the machine’s requirement
and history data of failures.
3. PM Planning and Scheduling
Preventive maintenance (PM) scheduling is a very challenging task in printed-circuit manufacturing due to the
complexity of flexible printed circuit fabrication and systems, the interdependence between PM tasks, and the
balancing of work-in-process (WIP) with demand/throughput requirements. In this section, after a discussion of the
problem background, PM planning and scheduling in flexible printed-circuit fabrication is proposed.
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3.1 Data Analysis
For this research, the PM planning and scheduling are based on major machine downtime where the machine does
not operate due to breakdown more than 2 hours. Recently, the PM schedule is separated into four clusters. A total
of 109 machines need to be rescheduled in proper way as only 8 technicians are responsible to look after all these
machines (six technicians on day-shift and two for night-shift). Data for major machine downtime was collected
starting from January 2011 until September 2011. The PM schedule for clusters is very complicated and thick. No
proper specification on critical machines is taken into consideration. From January to September 2011, data for total
downtime major have been extracted and shown in Figure 2.
Figure 2: Total downtime from January till September 2011
Figure 2 show how the downtime varies with month. Machine downtime in April seems to be worst among other
months with total downtime up to 449.25 hours. Data for April are narrowed down to see causes of machine
downtime and are listed in Table 1.
Table 1: Data on machine downtime major in April 2011
Date
Machine
Description Of Problem
Total down time
Root Cause
01.04.11 1 Annual service 146Hrs 10Min Annual service
04.04.11 2 Motor spoil and bracket broken 7Hrs Oscillation not running
04.04.11 3 Entrance cover run time over 2Hrs 55Min Open close shuttle bracket broken
07.04.11 4 Annual service Until now Annual service
07.04.11 5 Screen function "hang" 93Hrs 55Min
memory data
11.04.11 6 Roller not function 4Hrs 15Min Chain fall down and encoder broken
11.04.11 7 Can't punch 34Hrs Safety sensor problem
12.04.11 8 Main Chiller pipe leaking 4Hrs 30Min Chiller pipe broken
18.04.11 9 Pressure up until 120bar 26Hrs 30Min 2nd Pressure valve not function
18.04.11 10 Water rinsing pump not function 4Hrs 30Min Pump produces an abnormal sound
21.04.11 3 No power supply 93Hrs 30Min Transformer burnt
25.04.11 11 Hal dryer not running 10Hrs
25.06.11 12 Cannot punch 18Hrs
motor jammed
27.04.11 13 Roll scratches 4Hrs Roller scratches
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From Table 1, Machine 5 shows the longest downtime among other machines (93hours 55minutes). The cause for
this breakdown is the touch screen spoilt no data memory in PLC (Programmable Logic Controller). Actions taken
to undergo this problem are by changing the touch screen and download the program. But, these actions cannot be
classified as PM actions as technicians done the maintenance after this machine breakdown, not before these
problem occurred. Second longest downtime is from Machine 3 (93hours 30minutes). Cause of breakdown is
transformer of this machine burnt, thus lead to no power supply. Action taken to overcome this problem is by
changing to a new transformer. Not only focusing on these two machines, other machines that lies into major
downtime must also be taken into consideration. Data collected from all these ten months is analyzed. Machines
which are having longest downtime are classified as critical machines. On the other hand, further causes of
ineffective are being analyzed. Various causes can affect the full implementation of effective PM. Figure 3 shows
the issues involved to the ineffectiveness on PM that occur in the company.
Figure 3: Causes of Ineffective Maintenance
Another method that is used to study the ineffectiveness maintenance consequences on the machines is by using root
cause analysis. The aim of performing this root cause analysis is based on a maintenance perspective where
emphasis is placed on how proper maintenance can avoid the common problems that cause machine downtime. Root
cause analysis is a problem solving process designed for use in investigating and categorizing the root cause of
events. It’s a useful tool to identify what and how an event occurred and why it happened. Through this, suggestions
and prevention steps can be generated to solve the issue. Only through this where the probability of occurrence of
the same problem can be minimized.
The case study company currently has 107 machines operating and a clutch of machines crucial to the flow of the
production processes are prone to failure. Even after countless repairs done, they are still susceptible to failure. It is
notable that many of these machines are involved in processes that involve strong chemicals thus leaves many parts
of the machines exposed to excess wear and tear. Based on the data gathering and analysis done, the root causes of
the machines were identified and its contributions in terms of downtime are recorded based on Table 3.
ISSUES INVOLVED IN THE UNEFFECTIVE PREVENTIVE MAINTENANCE
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Table 3: Machine downtime and their Root Cause
These machines are critical machines that control the overall production flow. Of all the problems that occur, they
can all be generally classified as problems that occur mainly due to wear and tear and other electrical or technical
problems. Wear and tear is a common problem faced by machines in this factory as they are constantly exposed to
strong chemicals such as Hydrochloric Acid (HCL). The developing and etching machines constantly have major
problems that cause lengthy downtimes. Due to the nature of this process, these machines have to be constantly
inspected to detect any possible signs of wear and tear at the earliest stage possible. This is so that the technicians
and operators can be prepared to replace worn out parts at a suitable stage before major problems occur. If this is
carried out, major problems with these machines can be minimized thus keeping downtime at a minimum. However
it is currently not carried properly due to time constraints.
Month Date Machine Description
Of Problem
Total
down
time(hr &
mins)
Root
Cause Action
Taken Preventive Plan
July 04.07.11 A Dryer roller
not function 2 hrs 5
mins Gear
broken Change new
gear
Check all the gear
every month, if
spoil
August
01.08.11 B Chemical
Pressure tank
#2 not function
4 hrs 10
mins Ampler
spoil Change new
pump
Check the motor
during PM time
will
04.08.11 C Top roller dent 5hrs Roller
dent
Change new
roller top and
bottom
Change roller
every 3 month
08.08.11 D Glass broken 9 hrs 30
mins Glass
broken
Change new
glass, do
rubber
surround the
glass
Glass broken at the
joining material.
Ask vendor(LSP)
to fix the sensor
09.08.11 B Aqua control
error 3 hrs 30
mins
Main
MCB
trip
Change new
MCB & wire Monthly check on
all the MCB
09.08.11 E Filter dry film
tearing 3 hrs 55
mins Shelf-
life Change new
filter mesh
will monitor the
shelf-life and get
the standard
Septemb
er
23.09.11 E Chemical temp
low. Heater
problem 2 hrs Heater
spoil
ready
Change new
heater, heater
only run 1
unit
Keep spare two
unit heater
26.09.11 F Power can't on 2 hours 55
mins
Limit
switch
shutter
spoil
Change new
limit switch NONE
29.09.11 G Roller not
running 8 hrs Chain
broken
Change new
chain and do
alignment
NONE
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3.2 PM Planning Model
Based on the collected data, several ideas have been derived in achieving effective PM in this company as illustrated
in Figure 4.
Figure 4: Analysis of effective PM using Tree diagram
Figure 4 shows strategies and tactics evaluated from the proposed ideas in implementing effective PM. Main ideas
generated for this PM are to have simple maintenance schedule, do training for technicians and operators in
maintaining machines to be in good conditions, do routine inspections and also integrations with production. In
terms of integrating with productions, maintenance department must integrate with productions in doing PM
periodically. Communicate with productions plans to stop operations for awhile to do PM and joint shutdown
schedule. By doing this, machine can be maintained without or less breakdown. Operators also will know how to
repair their machines, not only depending on operators.
3.3 PM Scheduling Model
One of main objective in implementing PM in this company is to have simple yet effective PM schedule. In
achieving this goal, PM schedule will be classified into clusters and its respective technicians. Critical machines are
taken into highest priority where all spare parts must be ready before machine breakdown together with necessary
actions to overcome these machines from breakdown. Other than that, the schedule must state clear timeline
especially on periodic maintenance (some machines part must be changed or maintained within certain period).
Moreover, the PM schedule must be sorted into technicians. Every one of them will focus on their specified
IDEAS
STRATEGIES
TACTICS
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machines. Thus, maintenance activity can be done effectively by fully utilizing all technicians. Ensuring this
schedule will ease technicians is the upmost characteristics in implementing effective PM.
4. Maintenance Schedule Analysis
Analyzing the preventive maintenance schedule thoroughly, it can be noted that for every machine, there are a few
steps of maintenance work to be carried out. A standard machine requires approximately 10 to 15 minutes of
maintenance work to be done. Since the maintenance department currently does its weekly maintenance on Monday,
there are only three to four technicians who have to be responsible on performing maintenance work on 109
machines. This is a tough task to perform considering time limitations and constraints due to unexpected machine
failures to be resolved on the day and other maintenance duties to be done.
From the perspective of production, the machines can be divided into critical and non-critical machines. The critical
machines are the major machines that control the flow of the production and may be the bottleneck machine. When
these machines fail, the production may have to be stopped, such is the importance of these machines. These
machines too are highly susceptible to wear and tear thus constant inspection and weekly preventive maintenance
work has to be carried out. The non-critical machines on the other hand are machines that have very low frequency
of failure. This can be attributed to the working nature of these machines where they are not susceptible to wear.
Based on downtime analysis taken from a period of July to September 2011, the machines having a regular
downtime of over 2 hours can be classified as the critical machines. The rest of the machines are classified as non-
critical machines due to their low failure rate. The critical machines are Machine 10 (predictive maintenance already
being conducted), B, C, D, E, F and G.
Based on the observation from the technician in charge of the cluster, two things are evident where high downtime
machines are given particularly high priority and weekly maintenance is mandatory in addition to the predictive
maintenance being carried out and that weekly maintenance is also carried out for low downtime machines but these
machines are not critical ones and that the weekly maintenance does not affect its performance or influences the
causes of downtime.
5. Suggested Improvement
Based on these observation and analysis, a few solutions can be implemented and its effects examined on the
maintenance work:
1. Critical machines has to be given full attention and predictive maintenance work has to be continuously
carried out no matter what because these machines influence the overall process flow strongly and
downtimes can’t be afforded.
2. Machines that are not critical ones have to be scrapped out from the weekly maintenance schedule. This is
because the technicians have to balance between maintenance and facility work where a chunk of time is
spent on facility work and since first priority is given on the critical machine to allow predictive and
weekly maintenance to be carried, it is only sensible that the weekly maintenance of non-critical machines
be scrapped to allow more time for the technicians to carry out more important duties.
Based on a simple calculation for Cluster 1, where out of 23 machines currently in operation, 6 machines are
deemed as critical ones so if the non-critical machines are scrapped from the weekly maintenance schedule, it is
evident that per week, the technicians gain 5.67 hours of time to carry out the weekly and predictive maintenance of
critical machines, the monthly maintenance of critical and noncritical machines, corrective maintenance work and
also for facility work. From this it is proven that the weekly maintenance of noncritical machines can be eliminated
from the master schedule and this enable lesser work load on the technicians.
Conclusion
The implementation of preventive maintenance (PM) has proven that machine failure rates can be greatly reduced;
ensuring uninterrupted production. In most companies, PM is not always carried out on schedule due to the
circumstances involved and this affects the sole purpose of carrying out PM which requires precise planning on
maintenance dates for each machine. However, based on the situation in the company, it was evident why the
preventive maintenance work could not be carried out efficiently. A lack of manpower coupled with a hefty
maintenance schedule to accomplish is a daunting task. The analysis done on the machine downtime causes turned
up technical problems that are generally caused by improper maintenance work further proving how crucial it is to
carry out PM on time.
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In the case study company, the downtime data and analysis has shown the list of critical machines and the
ineffectiveness of the current maintenance schedule that does not distinguish between the critical and non-critical
machines. A further root cause analysis has shown that the machines suffer critical breakdowns when maintenance
work is not done properly. Thus to prove this, the root cause analysis was done to show how each problem correlates
with issues such as wear and tear and the delay to replace worn out components that lead to breakdowns. From the
maintenance schedule analysis based on Cluster 1(Circuit Formation), the machines can be grouped into critical and
non-critical ones and if the focus is to be given on the weekly maintenance of critical machines whilst sacrificing the
maintenance of non-critical machines, the technician gains approximately 5.67 hours of extra time and this time can
be used to focus on a wholesome maintenance work and inspection on the critical machines. If this is managed to be
done, the downtime of critical machines can be greatly reduced thus ensuring smooth production.
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... Techniques like visual analysis can be employed to pinpoint areas for improvement and optimize code quality during perfective maintenance, ultimately minimizing future costs and simplifying adaptations in complex software systems [11]. 4) Preventative Maintenance: Preventive maintenance adopts a proactive stance, involving targeted software modifications to detect and address potential faults before they escalate into actual errors [13]. This approach aims to mitigate software failure risks, minimize downtime, and ensure the reliability and performance of critical systems [13]. ...
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... Based on these methods, various frameworks are developed as found in Ab-Samat et al. (2012), Chen (2013), Koussaimi et al. (2016), Rukijkanpanich and Mingmongkol (2020) and Inyiama and Oke (2020). ...
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... The Root Cause Analysis is the main instrument used in the EWO data analysis, which permits to understand which cause is responsible for every machine failure and leads to the right countermeasure to undertake, as mentioned in the work of Ab-Samat et al. (2012). ...
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Purpose The purpose of this paper is to provide the description of an original framework for maintenance management plan development. The research aims to use in an integrated way different World Class Manufacturing (WCM)-based tools, in order to obtain a model which can be used for preventive maintenance in different industrial contexts. Design/methodology/approach In this research, a conceptual framework of preventive maintenance was described and then it was evaluated through a qualitative study in an Italian company. The company was chosen based on an initial interview with the operations team and the model area was selected. Then, the location was reorganized in order to obtain a green field which could sustain the implementation of the framework tools. Findings The case study was carried out in a small-medium manufacturing company which produces quick-release couplings and multiconnections, ranging from medium to ultra-high pressure. The defined framework has proved to be easy to implement in a company with a corrective maintenance plan, allowing the maintenance department to embrace the preventive maintenance culture. The maintenance model has been well received from the employees. Practical implications The framework allows a standardization of maintenance plans. Firstly, the standardization design itself allows finding previous wastes and consequent improvement areas. Then, it brings the improvement of a single machine which impacts all other machines in its family. Originality/value The added value of this study is the ability to integrate different WCM-based tools. Since the framework depicts a step-by-step process; it is also a starting point for companies that want to approach preventive maintenance for the first time.
... One of the factors that considerably affect OEE in automated lines is unplanned downtime. Usually, this problem occurs through a machine failure along the manufacturing lines and it leads to a loss in production minutes thereby reducing plant productiveness (Ab-Samat, et al., 2012). An approach on maintenance strategies is aimed at conserving the quality and market share of a product in any manufacturing or production environment. ...
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Equipment breakdown adds to the cost of production and considerably affect the overall equipment efficiency in automated lines due to unplanned downtime. Preventive maintenance with appropriate actions has been considered to enhance products quality, equipment reliability and minimize the probability of system brake down or failure. To this end, this study conducted a reliability status of nine packaging facilities, from the perspective of existing failure data of production system in the Nigerian multinational bottling plant. Failure data of the production system were stratified and analyzed to achieve the failure interval of each of the facilities and the subsystems. Stratification of failure data resulted to an established input format that fitted the Pareto chart analysis, Weibull Distributions and Reliability/Failure Time analysis. The results showed that the facility with minimum value of reliability was filler machine. A standby filler system was therefore recommended in order to prevent unnecessary idleness of the other facilities especially when the production target is high. The study concluded that, analysis of downtime in a production/manufacturing system assisted in predicting the likely failure interval and hence a preventive maintenance scheduled was proposed.
... Source: The breakdown of equipment contributes to cost of production and affects the overall equipment efficiency significantly in production lines that are automated due to downtime unplanned (Oke et al. 2020). This problem takes place through failure in machine along the lines of manufacturing and cause to loss in time of production thus reducing plant productivity (Ab-Samat et al. 2012). Thus equipment in manufacturing lines are always under constant pressure either when being operated or left unattended. ...
Conference Paper
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Most manufacturers are striving to manage and improve their operations at the perspective of manufacturing costs. Equipment failures and breakdowns should be kept at minimal as possible, thus to increase availability of equipment within a production line. A coal fly ash processing plant experienced continuous equipment breakdowns or failures which resulted in loss of production time. Data was collected on a 31 days period to identify types of failures or breakdown and their frequency of occurrences, and time spent by maintenance personnel to rectify the failures. Cause and effect diagrams were used in order to assess the causes that lead to overall effect of failures. It was identified that pipe conveyor belt failure was as a result of torn metallic structures, belt not fitting fully on idlers, deformed idlers and belt was unfolding at any point on the station while running. Furthermore, pipeline leakages were also identified as contributing factors to failures. Pareto chart was used to analyse the failures and it was identified that 80% of the pipe conveyor belt failure are caused by belt not fitting fully on idlers, torn metallic structure and deformed idlers, meanwhile 20% are caused as a result of belt unfolding at any point while running. Meanwhile in the case of pipeline leakages, 80% of pipeline leakages caused by high coal fly ash operating flow rate and coal fly ash being corrosive which resulted with pipeline being torn, while 20% of the leaks were due to improper sealing on divetor valve. It was concluded that incorrect maintenance procedures lead to the overall continuous failures at the plant and recommendations were made which mainly emphasised the implementation of maintenance program.
... A qualitative study about the aspects of effective PM has been conducted in [8], where the root cause analysis of the ineffective PM in a semiconductor company is also presented. The study proposed that the maintenance schedule must be incorporated with the production schedule to achieve an efficient and effective manufacturing system. ...
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Machines are valuable assets that need to be protected from damage and failure through proper maintenance measures. This paper proposes a system that automatically monitors the running time of machines and sends notifications regarding their preventive maintenance (PM) schedules. The system core consists of a programmable logic controller (PLC) and a human machine interface (HMI). The HMI is connected to an online platform via internet connection provided by a router, so that the monitoring result can be accessed via Android smartphone or laptop/PC. This IoT-based running time monitoring system (IRTMS) will be particularly helpful in implementation at an production site that consists of multiple various machines. The PM items of a machine may vary from cleaning, changing single component, to an overhaul, each with different time interval. By using the IRTMS, the user will have an overview of the PM schedules anytime and anywhere. The preparation of material, components, or tools can be known ahead of time. For simulation purpose, a prototype is constructed by using components as used in industrial real-life condition. Four output connections are provided to simulate the simultaneous monitoring of four machines. The IRTMS prototype is tested and completely successful on doing the running time monitoring, the running time reset, the PM notifications, and the remote access for monitoring and control.
... Ahmad et al. [2] investigated the maintenance management decision model for preventive maintenance strategy on production equipment. Hasnida et al. [3] studied the effective preventive maintenance scheduling. Jian Zhang et al. [4] focused on proposing an optimal inspection-based preventive maintenance policy for three-state mechanical components under competing failure modes. ...
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The aims of this study are to introduce the appropriate preventive maintenance to the production line machines at the company to increase their reliability and reduction the shutdown, and to obtain more safety. Mean time between failure, mean down time and availability are investigated as the best indicators to generally evaluate all type of maintenance. Pareto diagram and Effect-Cause techniques both have been used for identifying where and what are the problems in the production lines. The big and serious way that the company staff was using was maintenance of run to failure. Many solutions in this paper are introduced to the company to follow the proper preventive maintenance. After one year monitoring to those production lines, their productivity increases by 15.47% and the reliability becomes high.
Article
Scheduling electrical machines based on consumer demands improves the efficiency of the purpose through flawless allocations. However, due to peak utilization and maximum run-time of the machines, the chances of schedule mismatch and overlapping are common in large production scales. In this paper, an Operation Scheduling process (OSP) using Classification Learning (CL) is proposed. The proposed process classifies operation schedules based on overlapping and mismatching intervals post-output completion. The classification is performed using interval stoppage and re-scheduling performed between successive completion intervals. This is required to improve the output success rate for simultaneous machine operations. Therefore the scheduling is improved regardless of distinct tasks allocated with better outcomes.
Chapter
Research forms part of the beer production and plant trust improvement program. Research is a member of a drinking company. The filler/crowder with a glass bottle was 96.62 h of inactive time and quickly became a critical machine for a few months of machine failure collected. As a result of failures that affected the production and quality of the product, the availability of the critical machine was fully automated. Autonomous maintenance (AM) was introduced as part of total production maintenance on the bottle filler/crowner to minimize the maintenance pressure. The objective is to improve accessibility for machines so that professional service providers can focus their efforts on value-added and technological repairs through training and upgrading of shop floor operators. Averaging 1.15 h, shifts of 87% (12 h) and 76% throughout the day were average 87.42 h before the AM was filled (24 h). The MTTR was 113.27 h after two months of execution and the MTTR was 0.87 h with machine reliability rising by 90.0% and 81.0%. The results have shown that the independent maintenance of operators in their machinery is key in detecting equipment failures, cutbacks, reliability and improving machine performance.
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Presents a model of five linked maintenance management components (strategy, human aspects, support mechanisms, tools/techniques and organization). Analyses the present status of these components in Swedish manufacturing firms through a survey of 284 respondents. Shows that fewer than half have written maintenance strategies or computerized maintenance information systems and several give maintenance low status. The figures are lowest in small firms and in the timber industry. Preventive maintenance at fixed intervals and corrective maintenance are the most common maintenance techniques. However, condition monitoring is common in large paper and chemical firms. Also indicates that Swedish firms have not fully made maintenance a company-wide issue, and that centralized maintenance departments dominate resources in large firms, but outsourcing has become important in small firms. Many of these figures are considered not to be optimal, but the average firm should be able to improve.
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Purpose The purpose of this study is to identify various issues and challenges associated with development and implementation of a maintenance performance measurement (MPM) system. Design/methodology/approach An analytical approach is adopted to identify the issues and challenges associated with MPM. Findings The study finds that for successful implementation of MPM all employees should be involved and all relevant issues need to be considered. Furthermore, the traditional overall equipment effectiveness (OEE) used by the companies is inadequate, as it only measures the internal effectiveness. For measuring the total maintenance effectiveness both internal and external effectiveness should be considered. Practical implications What cannot be measured cannot be managed effectively. To manage maintenance process operating managers and asset owners need to measure the contribution of maintenance towards their business goals. This paper discusses issues and challenges associated with MPM system, there by helping the managers to take care of the pitfalls of the MPM system and advocates that managers should focus on measuring the total effectiveness of maintenance process. Originality/value The paper presents a concept of total maintenance effectiveness with focus on both internal and external effectiveness, and integration of the hierarchical levels and multi‐criteria maintenance performance indicators of MPM system.
Article
Today, world-class competitiveness is a must for companies. The undeniable global competition, characterised by both a technology push and a market pull, and the rapidly evolving technology and increased customer requirements put forward a lot of challenges for management. One of these challenges concerns the production equipment. High-speed technological innovation combined with severe competition shortens the equipment life cycle and puts equipment under higher stress. In order to deal with this problem, a company's strategic investments in production equipment should not only consider cost and capacity, but also technology trends, flexibility, etc. Another important aspect is maintenance. Proper maintenance helps to keep the life cycle cost down and ensures proper operations and smooth internal logistics. The decision on the required maintenance concept and a thorough and easily accessible technical knowledge are crucial here. More and more companies are searching for a customised maintenance concept. The framework described in this paper offers some guidelines to develop such a concept, and borrows some ideas from maintenance concepts described in literature. An important feature of the framework is that it allows to incorporate all information available in the company, ranging from experience of maintenance workers to data captured by modern Information and Communication Technology (ICT) means.
Article
Purpose The purpose of this paper is to review the literature on maintenance optimization models and associated case studies. For these optimization models critical observations are made. Design/methodology/approach The paper systematically classifies the published literature using different techniques, and also identifies the possible gaps. Findings The paper outlines important techniques used in various maintenance optimization models including the analytical hierarchy process, the Bayesian approach, the Galbraith information processing model and genetic algorithms. There is an emerging trend towards uses of simulation for maintenance optimization which has changed the maintenance view. Practical implications A limited literature is available on the classification of maintenance optimization models and on its associated case studies. The paper classifies the literature on maintenance optimization models on different optimization techniques and based on emerging trends it outlines the directions for future research in the area of maintenance optimization. Originality/value The paper provides many references and case studies on maintenance optimization models and techniques. It gives useful references for maintenance management professionals and researchers working on maintenance optimization.
Article
Despite the inter-dependent relationship between them, production scheduling and preventive maintenance planning decisions are generally analyzed and executed independently in real manufacturing systems. This practice is also found in the majority of the studies found in the relevant literature. In this paper, heuristics based on genetic algorithms are developed to solve an integrated optimization model for production scheduling and preventive maintenance planning. The numerical results on several problem sizes indicate that the proposed genetic algorithms are very efficient for optimizing the integrated problem.
Article
We are given a set of items that must be produced in lots on a capacitated production system throughout a specified finite planning horizon. We assume that the production system is subject to random failures, and that any maintenance action carried out on the system, in a period, reduces the system’s available production capacity during that period. The objective is to find an integrated lot-sizing and preventive maintenance strategy of the system that satisfies the demand for all items over the entire horizon without backlogging, and which minimizes the expected sum of production and maintenance costs. We show how this problem can be formulated and solved as a multi-item capacitated lot-sizing problem on a system that is periodically renewed and minimally repaired at failure. We also provide an illustrative example that shows the steps to obtain an optimal integrated production and maintenance strategy.
Capability assurance: a generic model of maintenance
  • M Murray
  • K Fletcher
  • J Kennedy
  • P Kohler
  • J Chambers
  • T Ledwidge
Murray, M., Fletcher, K., Kennedy, J., Kohler, P., Chambers, J., Ledwidge, T., 1996. "Capability assurance: a generic model of maintenance", Maintenance Engineering Society of Australia.,
Lean Maintenance: Reduce Costs; Improve Quality and Increase Market Share
  • R Smith
  • B Hawkins
Smith, R. and Hawkins, B., 2004. Lean Maintenance: Reduce Costs; Improve Quality and Increase Market Share. Massachusetts: Butterworth-Heineman Publication.