




































    

 Academic Journal of Science, Engineering and Technology 

Vol. 9, Issue 3; May-June 2024; 

ISSN: 2837-2964 

Impact Factor: 6.67 

1252 Columbia Rd NW, Washington DC, United States 

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58 | A c a d e m i c  J o u r n a l  o f  S c i e n c e ,  E n g i n e e r i n g  a n d  T e c h n o l o g y  

|  https://topjournals.org/index.php/AJSET 

PLANT MAINTENANCE STRATEGY FOR IMPROVED PRODUCTION IN 

THE FOOD AND BEVERAGE INDUSTRIES 
 

Onyejaka, Chidi Maurice 

Department of Engineering Management, Faculty of Engineering, Enugu State University of Science and 

Technology, Enugu. 

DOI: https://doi.org/ 10.5281/zenodo.12547983 

 

Abstract: The evaluation of plant maintenance methods for improved performance in the food and beverage 

industries was carried out using Nigerian Bottling Company Benin and Owerri Plants and BONS Industries 

Limited Enugu, Nigeria. The study investigated to determine the maintenance approaches used in the food and 

beverage manufacturing industries and to evaluate the availability rate, performance rate, and quality rate of the 

manufacturing industry due to maintenance. Records on maintenance activities on Filler machines, Packers, Blow 

mold, Monobloc (Filler/Capper/Rinser) machines, and Palletizers were collected using record forms from the 

logbook for a period of five years (2017 – 2021) and this serves as the primary data for the research. The world-

class Overall Equipment Effectiveness (OEE) mathematical model was used to evaluate the maintenance 

performance of each plant. In Nigerian Bottling Company (NBC), the Availability rate of the Filler machine 

ranged from 93.0% - 96.9%, the Performance rate ranged from 66.2% - 129.3% and the Quality rate was 99.9% 

for all the years. For BONES Industries Ltd, water production line, the Availability rate of the Monobloc machine 

ranged from 86.8% - 95.8%, the Performance rate ranged from 47.2% - 96.1% while the Quality rate ranged from 

91.8% - 93.7%. The maintenance methods/approaches used in NBC Plants were preventive and usage while the 

maintenance methods/approaches used in BONS Industries equipment were Preventive and Condition-based 

maintenance. The Availability rate, Performance rate, and Quality rate which are the parameters to evaluate 

equipment maintenance performance were better in NBC than in BONS Industries. The Overall maintenance cost 

and cost per case are also better in NBC than that of BONS about volume produced. This recommended that 

companies should carry out routine preventive maintenance and usage-based maintenance such as periodic 

machine overhauls since the better result was obtained when compared to preventive and condition-based. 

Keywords: Food and Beverage Industries, Plant Maintenance, Production, Strategy, Food and Beverage 

Industries.  

 

1.1 Introduction 

Maintenance is defined according to the European standard (Alsyouf, 2004) as “the combination of all technical, 

administrative and managerial actions during the life cycle of an item intended to retain it in, or restore it to a 

state in which it can perform the required function”. It leads to high-quality and low-defect products, a safe and 

secure work environment, increased production speed, and the overall improvement of the performance of the 

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 Academic Journal of Science, Engineering and Technology 

Vol. 9, Issue 3; May-June 2024; 

ISSN: 2837-2964 

Impact Factor: 6.67 

1252 Columbia Rd NW, Washington DC, United States 

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59 | A c a d e m i c  J o u r n a l  o f  S c i e n c e ,  E n g i n e e r i n g  a n d  T e c h n o l o g y  

|  https://topjournals.org/index.php/AJSET 

plant. To perform maximally, the machines have to be maintained. However, some view maintenance as a waste 

of resources whereas maintenance should be viewed as a profit center and not an avoidable expense (Al-Najjar et 

al., 2001; Al-Najjar and Alsyouf, 2004).  Effective maintenance results in long-term profit and it has an impact 

on production and its operational aspects such as capacity, quality, costs, environment, and safety. In recent times, 

the machines used in manufacturing companies are automated compared to simple machines used before World 

War II (Alsyouf, 2007).  Reliability, availability, maintainability (RAM), safety, quality, environment, and multi-

skilling are considered very important in current machines in use. 

Nigeria is a populous developing country with a lot of economic challenges. It has undergone more than two 

economic recessions since 2016. This has led to the folding up of some companies. Some that are still functional 

do not have maximum performance because of myriad factors. However, the demand for products by the teeming 

population of Nigeria and competition among companies demands that the remaining companies perform 

maximally (Mifdal et al., 2013). Industrialization in Nigeria seems to be at a crossroads given that these pursuits 

of the strategy would lead to more inefficient resource usage, intensified foreign exchange constraints, high cost, 

and balance of payment difficulties. This is paradoxical given that the industrial sector is theoretically at least 

expected to have the capacity to innovate and thus exude the dynamism that affects the other sectors of the 

economy. Businesses in the Nigerian manufacturing sector have tottered over the years due to a lack of adequate 

management commitment to timely funding of materials procurement coupled with unethical practices of some 

executives (Oba, 2008). According to a survey carried out in 2010 by the Manufacturers Association of Nigeria 

(MAN), 834 manufacturing companies shut down their operations in 2009 across the country due to high 

manufacturing costs created by exorbitant prices of raw materials and spare parts for machine maintenance among 

other reasons (Adeloye, 2010). The few surviving manufacturing firms are faced with stiff competition in the 

current markets. This has led to the need for coming up with a better method of managing and measuring how 

material resources are utilized by various jobs or products and therefore be able to eliminate any wastage in the 

value chain. With the process of liberalization, there has been a drastic change in the market which has forced 

manufacturing companies to devise strategies to minimize production and equipment maintenance costs to remain 

competitive.  

Today, there are dramatic evolutions in the market environment and every organization must strive to keep itself 

in business. Major competition has shifted from the market to the production floor where manufacturing costs 

(including equipment maintenance costs) can be reduced and profitability boosted for firms to compete favorably. 

Backed by advanced technology, firms are closely monitoring their manufacturing costs and embarking on 

efficient management of materials (Ondiek, 2009). Unfortunately, few studies exist yet on the productivity 

analysis of manufacturing firms for a developing economy such as Nigeria. This study intends to fill this gap on 

mainly the equipment maintenance performance side which is huge, with the right maintenance strategy in place 

all these can be properly achieved.  

1.2 Statement of the Problem  

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 Academic Journal of Science, Engineering and Technology 

Vol. 9, Issue 3; May-June 2024; 

ISSN: 2837-2964 

Impact Factor: 6.67 

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60 | A c a d e m i c  J o u r n a l  o f  S c i e n c e ,  E n g i n e e r i n g  a n d  T e c h n o l o g y  

|  https://topjournals.org/index.php/AJSET 

Poor maintenance of machines and equipment is known to result in low productivity, low profit, and reduced 

efficiency/reliability of the machines. While these organizations are busy working out means of increasing 

productivity and enhancing their equipment performance, the problems continue to increase. It can be pointed out 

here that the results or implications of these are damaging. Low productivity and poor equipment maintenance 

lead to unnecessary loss of huge amounts of money. These losses of money by these organizations cripple the 

economy of the nation. Given the above-mentioned problems, it becomes obvious that there is a need to evaluate 

the plant maintenance strategy for improved production in the manufacturing firm in Nigeria and also determine 

the equipment maintenance performances. Hence, there is a need to evaluate the maintenance culture/strategy of 

the industries in developing countries like Nigeria where resources are scarce. 

1.3 Aims and Objective 

To evaluate the equipment maintenance strategy for improved performance in the food and beverage industries.  

Research Objectives  

1. To determine the maintenance approaches used in the food and beverage manufacturing industries. 

2. To evaluate the availability rate, performance rate, and quality rate of the manufacturing industry due to 

maintenance. 

1.4 Hypothesis of the Study 

The following Alternative hypotheses guided the study. 

 There are no maintenance approaches used in the food and beverage industries. 

 Evaluation of the availability rate, performance rate, and quality rate of the manufacturing industry will not be 

improved due to equipment maintenance.  

2.0 Review of Related Literature 

2.1 Conceptual Review 

Maintenance 

Maintenance is defined according to the European standard as “the combination of all technical, administrative 

and managerial actions during the life cycle of an item intended to retain it in, or restore it to a state in which it 

can perform the required function”. It leads to high-quality and low-defect products, a safe and secure work 

environment, increased production speed, and the overall improvement of the performance of the plant. 

Equipment maintenance is any process used to keep a business's equipment in reliable working order. It may 

include routine upkeep as well as corrective repair work or procedures used by Technicians to keep the machine 

in top shape. Equipment may include mechanical assets, tools, heavy off-road vehicles, and computer systems. 

The need for maintenance is predicated on actual or impending failure – ideally, maintenance is performed to 

keep equipment and systems running efficiently for at least the design life of the component(s). 

Maintenance strategy gives room for strategic maintenance decision making which involves selecting the right 

care and repair methodologies that maximize equipment life and performance for the least cost to the user.  But 

to be able to make successful maintenance management strategy choices you must understand how equipment 

fails.  When you know the equipment’s weaknesses and strengths you can care for it properly and get maximum 

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 Academic Journal of Science, Engineering and Technology 

Vol. 9, Issue 3; May-June 2024; 

ISSN: 2837-2964 

Impact Factor: 6.67 

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61 | A c a d e m i c  J o u r n a l  o f  S c i e n c e ,  E n g i n e e r i n g  a n d  T e c h n o l o g y  

|  https://topjournals.org/index.php/AJSET 

service from it at the least cost. We have different types of maintenance approaches/strategies which include 

Preventive, Corrective, Predictive, Condition-based, Usage-based maintenance, etc. Maintenance has had a 

tremendous impact on the company’s proficiency to optimize its production system to meet its long-term 

objectives. Generally, a production system in which maintenance is not given attention may easily lead to the 

system producing defective products as a result of machine defects, (Alsyouf, 2004). 

Types of maintenance approaches 

The need for maintenance is predicated on actual or impending failure – ideally, maintenance is performed to 

keep equipment and systems running efficiently for at least the design life of the component (s). As such, the 

practical operation of a component is a time-based function. Anytime we fail to perform maintenance activities 

intended by the equipment’s designer, we shorten the operating life of the equipment. But what options do we 

have? Over the last 30 years, different approaches to how maintenance can be performed to ensure equipment 

reaches or exceeds its design life have been developed in the United States. In addition to waiting for a piece of 

equipment to fail (reactive maintenance), we can utilize preventive maintenance, predictive maintenance, or 

reliability-centered maintenance, (Piotrowski, 2001). 

The Strategies/approaches: 

• Reactive Maintenance: The moment the machine breaks down, it will be immediately fixed. 

• Preventive Maintenance: There will be a parts replacement schedule ahead of time before parts breakdown, 

usually at a regular interval. 

• Usage-Based Maintenance: The parts are replaced when the machine has been used for a certain period before 

they break down. 

• Condition-Based Maintenance: The parts are replaced when they seem to getting too worn out to continue 

functioning appropriately. 

• Predictive Maintenance: The historical data are utilized to make predictions about when a part will break and 

replace the parts based on these predictions before they break. This usually, but not always, utilizes artificial 

intelligence and machine learning. 

• Prescriptive Maintenance: This involves using advanced data analysis methods to do more than predict failure 

points, but instead provides hypothetical outcomes to choose the best action that can be taken before failure, safety 

hazards, and quality issues arise as well as the timing of implementation. 

Using the right maintenance approach for manufacturing equipment gives room for better machine performance. 

However, we will go further to elaborate on the strategies/types of maintenance that are mostly used in 

manufacturing industries, (Al-Najjar, 1997; Kelly, 1997; Pintelon and Gelders, 1992). 

Availability rate: Equipment availability is a metric used to measure the percentage of time a machine can be 

used. It is the amount of time in which a machine runs and is available for production. Availability can also be 

called 'uptime', and it is one of the key metrics that give us insight into our production efficiency. Machine 

availability, or uptime, is the total amount of time a machine runs versus the time it was scheduled to run. 

Availability is the percentage of time a machine is in operation. The scheduled time is based on understanding 

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 Academic Journal of Science, Engineering and Technology 

Vol. 9, Issue 3; May-June 2024; 

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62 | A c a d e m i c  J o u r n a l  o f  S c i e n c e ,  E n g i n e e r i n g  a n d  T e c h n o l o g y  

|  https://topjournals.org/index.php/AJSET 

available capacity, having the raw materials on hand in appropriate quantities, and having the staff and sales 

orders required to run. Downtime can slow or stop the machine during this scheduled time. Total downtime 

includes preventive maintenance, changeovers, and other controlled, known variables. Unplanned downtime 

means breakage, quality fallout, jams, or other unpredicted stoppages. For example, a machine could be scheduled 

to run for eight hours and only be active for six hours. In this case, the availability score for the machine is 75%. 

All manufacturing operations should measure availability and downtime, taking into account the duration and 

reason for downtime. However, if this is tracked by hand, it is likely to be highly inaccurate, severely delayed, 

and far less actionable. Machine availability also referred to as uptime, is the total amount of time a machine runs 

versus the time it was scheduled to run. Availability is a key figure to monitor when it comes to production 

planning. Production capacity, delivery dates, expected breakdowns, and costing are determined from availability 

data, (Waeyenbergh and Pintelon, 2002; Kumar, 1996). 

Machine availability is calculated in the following way: 

Availability =    Production Run Time   

                         Planned Production Time 

2.1.4 Performance rate: Performance, also known as process rate, measures the speed at which the workstation 

or machine processes units. It is also represented as a percentage of the ideal, with performance losses being 

caused by logistical problems, searching for tools, small stops, operator inefficiency, decreased speed of the 

machine, etc. 

Performance =    (Total Units x Ideal Cycle Time)   

                                             Real Run Time 

Quality rate: The quality rate is defined as the ratio between the yield produced and the total production 

quantity. For the calculation of the quality rate, the scrap quantity incurred must be recorded. This can be done, 

e.g., by manual input which is made directly at the machine terminal, or by comparing the total production volume 

recorded with the possibly existing weighing of the actual yield. Quality is calculated by dividing the number of 

usable units produced by the total units stated. If an asset produces 12,000 units in a 12-hour production time 

frame, but 300 of them have defects that make them unusable, then the number of usable units is 11,700. 

Therefore, the quality score would be 0.975 or 97.5%. Quality takes into account manufactured parts that do not 

meet quality standards, including parts that need rework. Remember, OEE Quality is similar to First Pass Yield, 

in that it defines Good Parts as parts that successfully pass through the manufacturing process the first time 

without needing any rework. 

Quality is calculated as: 

               Quality =      Good Count 

                                    Total Count   

Hence Quality Rate =    Good Count    x 100 

                                        Total Count           

Improved Performance 

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Vol. 9, Issue 3; May-June 2024; 

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63 | A c a d e m i c  J o u r n a l  o f  S c i e n c e ,  E n g i n e e r i n g  a n d  T e c h n o l o g y  

|  https://topjournals.org/index.php/AJSET 

Performance is the result of work and work behavior that has been achieved in completing the tasks and 

responsibilities given in a certain period. Didier (2002) considers that performance is to "achieve the goals that 

you have given in convergence with the company guidelines” and that performance is not simply finding a product 

but rather is the result of a comparison result and objective. Performance improvement is measuring the output of 

a particular business process or procedure, then modifying the process or procedure to increase the output, 

increase efficiency, or increase the effectiveness of the process or procedure. The primary goals of organizational 

improvement are to increase organizational effectiveness and efficiency to improve the ability of the organization 

to deliver goods and or services. A third area sometimes targeted for improvement is organizational efficacy, 

which involves the process of setting organizational goals and objectives. Improving performance can pertain to 

various domains such as personal productivity, physical fitness, or even organizational efficiency. There are two 

main ways to improve performance: improving the measured attribute by using the performance platform more 

effectively, or by improving the measured attribute by modifying the performance platform, which in turn allows 

a given level of use to be more effective in producing the desired output. All companies strive for better 

performance since high performance means high competitiveness, which in turn generates more money. However, 

there are different ways to increase performance, depending on which viewpoint you choose to take, efforts to 

improve performance in manufacturing operations have been important since the start of the industrialization era, 

(Kirkpatrick, 2006). 

Food and Beverage Industries 

The Food and Beverage Industry includes all the companies involved in transforming raw agricultural goods into 

consumer food products as well as processing, packaging, distribution, and retail, which are all included in the 

large, diverse food and beverage industry. Due to their provision of necessary goods and services that support life 

and promote social and economic advancement, these industries are vital to both the global economy and human 

welfare. It does not cover raw food production, which falls into the closely related agriculture industry. This 

industry includes fresh food, packaged food, and beverages (both alcoholic and non-alcoholic). From food sold 

at the grocery store to cooked meals served at restaurants, institutions, and events, this industry serves a huge 

variety of retail outlets. 

The food and beverage industry is divided into two major segments, which are the production and the distribution 

of edible goods. As the world’s population grows, so does the demand for food and drink. But that’s not all. It’s 

one of the oldest industries on the planet, but still full of innovation. From new products to higher-volume, lower-

cost production techniques, this industry is always looking for new ways to produce the food consumers want at 

the best possible price. And vital equipment is there every step of the way. Consumers want more than just food 

and drink for sustenance; their demands are now more health, ethically, and environmentally driven, (FAO, 2018). 

2.2 Theoretical Framework 

The Systems Theory  

This theory viewed the inputs/output models. The inputs are taken through processes to transform them into 

outputs. The outputs are compared with the objectives and feedback is sent to the inputs to enhance improvement 

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 Academic Journal of Science, Engineering and Technology 

Vol. 9, Issue 3; May-June 2024; 

ISSN: 2837-2964 

Impact Factor: 6.67 

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64 | A c a d e m i c  J o u r n a l  o f  S c i e n c e ,  E n g i n e e r i n g  a n d  T e c h n o l o g y  

|  https://topjournals.org/index.php/AJSET 

of efficiency and productivity of the system (Ludarig, 1968). He noted that maintenance management was the 

system, the inputs were labor, materials, spares, tools, information, and external services. The maintenance system 

processes these inputs into availability, maintainability, safety, and profits as the outputs. Systems theory is a 

concept that originated from biology, economics, and engineering, which explores principles and laws that can 

be generalized across various systems (Alter, 2007; Dubrovsky, 2004). A system is a set of two or more elements 

where: the behavior of each element affects the behavior of the whole; the behavior of the elements and their 

effects on the whole are interdependent; and while subgroups of the elements all affect the behavior of the whole, 

none has an independent effect on it (Skyttner, 1996). In other words, a system comprises subsystems whose 

inter-relationships and interdependence move toward equilibrium within the larger system (Martinelli, 2001; 

Steele, 2003).  

2.3 Empirical Review 

Foon and Terziovski M (2014) conducted a study to evaluate the impact of operations and maintenance practices 

on power plant performance in Australia and Malaysia. The study aimed to examine the impact of Operations and 

Maintenance (O&M) practices, individually and collectively, on power plant performance. A survey research 

design was used for this study. The results revealed that the relationship between O&M practices and plant 

performance is significant and positive in a cross-sectional sense. 

Maletic et al (2014) examined the role of preventive maintenance in improving a company’s competitiveness and 

efficiency in a Slovenian textile company. This study aimed to discuss the potential improvement areas from the 

company's perspective and to examine maintenance impact on the company’s business. An empirical case study 

was utilized for this study. The results revealed that preventive maintenance practices and condition-based 

maintenance (CBM) approach represent the highest opportunity for improvement of organizational performance.  

Oseghale (2014) conducted a study on the impact of maintenance strategies on the performance of industrial 

facilities in selected industrial estates in Lagos state, Nigeria. The study aimed to appraise the facilities and the 

maintenance management strategies employed in selected industrial estates in Lagos State by identifying and 

examining facilities maintenance strategies, and determining their impact on the physical condition of the 

facilities. Both quantitative and qualitative were employed for this research. The results revealed that there was 

no significant relationship between the types of maintenance strategies and the respondents’ level of satisfaction 

with the physical condition of their facilities. 

Uforo et al, (2022) conducted a study to examine the relationship between Maintenance Management and 

organizational performance among selected manufacturing firms in Akwa Ibom State. The study aims to study 

the relationship between corrective maintenance, preventive maintenance, conditions-based maintenance, 

organizational culture, maintenance management, and organizational performance in manufacturing firms. A 

survey research design was adopted for this study. The results revealed that management has to provide the 

maintenance teams with maintenance management software to ensure proper intervention monitoring as well as 

smooth communication between technicians and other professionals to enhance business success. 

3.0 Methodology 

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65 | A c a d e m i c  J o u r n a l  o f  S c i e n c e ,  E n g i n e e r i n g  a n d  T e c h n o l o g y  

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A retrospective study of performance evaluation of maintenance of Nigerian Bottling Company Ltd (Coca-Cola) 

Benin, Owerri Plant, and BONS Industries Limited, Enugu from 2017 – 2021 (5 years) was adopted. Logbooks, 

work orders, operating statistics, and production reports including target volume and actual volumes were 

assessed to obtain primary data. The study was carried out at Nigeria Bottling Company Ltd (NBC), Benin Plant, 

Edo State, and Nigerian Bottling Company Ltd (NBC) Owerri Plant, Imo State, Nigeria. A record form containing 

questions on year of study, type of machine, type of maintenance, machine breakdown records, downtime incurred 

in each equipment,  hours of operation, target amount of product, actual amount of product, quantity of defective 

product, cost of maintenance and major maintenance done on the lines were used. Record analysis of relevant 

data was obtained from the company’s annual maintenance report and journals. 

Data were analyzed using Microsoft Excel.  The availability rate, performance rate, and quality rate were 

calculated using OEE, The availability of the machine was further analyzed with a bar chart or pie chart, and the 

explanation was done to see how it affected equipment performance. Also, the performance rate and the quality 

of the product produced by the machines were further analyzed using the bar chart and pie chart and the result 

was explained. The mathematical expressions below are used to obtain the actual values in percentages of these 

parameters (availability, performance, and quality rates): 

Availability rate of the equipment = Planned runtime-planned downtime x100 

                                                                                         planned run time 

Performance rate of the equipment = Total actual amount of product x100 

                                                                                   Target amount of product  

Quality rate of the equipment = Processed quantity –defective quantity x100 

                                                                                      processed quantity  

The total cost of maintenance and cost per case of each maintenance strategy were also analyzed to obtain the 

best method of maintenance for effective food and beverage production. The mathematical expression/formula 

below was used. 

Preventive Maintenance percentage cost = Preventive maint. Cost x100 

                                                                    Total Maintenance cost 

Cost Per Case =    Preventive Maint.Cost 

                            Total volume of product. 

Usage Based Maintenance percentage cost = Usage Based maint. Cost x100 

                                                                           Total Maintenance cost 

Cost Per Case = Usage Based Maint.Cost 

                             Total volume of product. 

This is done for the condition-based maintenance strategy used in this study. 

4.0 Data Presentation and Analysis 

4.1 Presentation of results 

This study was for a period of five years,s (year one: 2017; year two: 2018; year three: 2019; year four: 2020; 

years five: 2021) 

The Filler Machine – NBC Benin Plant. 

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66 | A c a d e m i c  J o u r n a l  o f  S c i e n c e ,  E n g i n e e r i n g  a n d  T e c h n o l o g y  

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Table 4.1 shows that the Filler machine – Benin Plant was purchased in 2008 and the type of maintenance 

approaches carried out were preventive and usage-based maintenance. The machine has a capacity of 1650CPH 

– (CPH: Cases Per Hour). 

Table 4.1: General information of the filler machine 

Variables Information 

Name of machine  Filler 

Year of purchase 2008 

Type of Maintenance Preventive and 

usage-based 

Capacity of machine 1650CPH 

Table 4.2: Data obtained from the company (Nigerian Bottling Company (NBC) Benin plant South-South) - Filler 

Machine RGB 

Variables  2017 2018 2019 2020 2021 

Total number of 

hours of  breakdown 

per year(hours) 

123.66 107.33 146.33 153.4 108.5 

Planned number of 

hours of operation 

per year(hours) 

2386.67 2462.56 3626.02 2028.80 3481.41 

Number of hours of 

machine overtime 

per year 

242 201 166 143 129 

Target amount of 

product per year 

(cases) 

3,102,244 3,505,644 4,799,560 5,234,767 4,878,455 

Actual amount of 

product per 

year(cases) 

3,230,017 3,794,995 6,207,177 3,467,081 5,543,752 

Quantity of 

defective products 

per year (Cases) 

4213 4983 5310 4643 4891 

Machine capacity 

(CPH) 

1650 1650 1650 1650 1650 

    

      

     

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67 | A c a d e m i c  J o u r n a l  o f  S c i e n c e ,  E n g i n e e r i n g  a n d  T e c h n o l o g y  

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Calculations Using the Oee Model for the Filler Equipment: 

The calculations in Appendix 1 show the workings using the Overall Equipment Effectiveness world-class model 

for evaluation of the Availability rate, Performance rate, and quality rate of the Filler machine. 

The Availability rate: 

Table 4.3 shows that the availability rate of the Filler machine ranges from 92.5% - 97.0%. In 2017, it was 94.8%; 

2018 (95.6%); 2019 (96.0%); 2020 (92.5%); 2021 (96.9%). However, it was highest in year five at 97.0% while 

least in year four at 92.4%. 

Table 4.3: Availability rate of the NBC Filler machine – Benin Plant. 

Year of Study Availability Rate (%)   

Year One (2017) 94.8   

Year Two (2018) 95.6   

Year Three(2019) 96.0   

Year Four (2020) 92.5   

Year Five (2021) 96.9   

 

Figure 4.1 shows the availability rate of the filler machine. The availability rate was highest in year five 96.9% 

while it was lowest in year four (93.0%) 

 

 
 

Figure 4.1: Availability rate of the filler machine 

From Table 4.3 and also looking at Figure 4.1, the availability rate is higher in year five than in year three despite 

the higher planned hours of operation for year three. This is because the availability rate of equipment is 

95.0%

96.0% 96.0%

93.0%

96.9%

91%

92%

93%

94%

95%

96%

97%

98%

Year one Year two Year three Year four Year five

A
v
a
il

a
b

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ISSN: 2837-2964 

Impact Factor: 6.67 

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68 | A c a d e m i c  J o u r n a l  o f  S c i e n c e ,  E n g i n e e r i n g  a n d  T e c h n o l o g y  

|  https://topjournals.org/index.php/AJSET 

considered about downtime incurred during operation and even the corresponding volume of product produced. 

For example looking (table 4.2) at the planned number of hours of operation in years three and four, that of year 

three is more but that does not make that year the highest in equipment(filler) availability due to downtime it 

incurred. This implies that a year with smaller planned hours of operation might turn out to be the year with the 

best availability of the equipment if the downtime or machine breakdown is reduced due to the maintenance 

strategy that may be applied. 

However, in this case, the actual hours of operation about the planned hour give a higher availability rate in year 

five. Also when the machine breakdown is reduced with the corresponding reduced downtime, there is always a 

positive effect on the volume of product produced and all these are influenced by the type of maintenance 

strategy/method involved as can be seen in Table 4.2 for year three (6,207,177) and year five (5,543,752).  

The Performance rate: 

Table 4.4 shows that the Performance rate of the Filler machine ranges from 66.2% - 129.3%. In 2017, it was 

104.1%; 2018 (108.3%); 2019 (109.3%); 2020 (66.2%); 2021 (113.6%). However, it was highest in year three 

with 129.3% while least in year four 66.2%. 

Table 4.4: Performance rate of the NBC Filler machine – Benin Plant. 

Year of Study Performance Rate (%)   

Year One (2017) 104.11%   

Year Two (2018) 108.25%   

Year Three(2019) 129.32%   

Year Four (2020) 66.23%   

Year Five (2021) 113.63%   

Figure 4.2 shows that the performance rate was lowest in year four 2020 (66.2%) while it was highest in year 

three (129%). 

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69 | A c a d e m i c  J o u r n a l  o f  S c i e n c e ,  E n g i n e e r i n g  a n d  T e c h n o l o g y  

|  https://topjournals.org/index.php/AJSET 

 
Figure 4.2: Performance rate of the filler machine. 

From Figure 4.2, the bar chart, the performance rate was highest in year three (129.3%). This may be attributed 

to the complete year-round refit (quarterly overhaul) done on filler, the preventive maintenance was routinely 

carried out hence the equipment availability for that same year was 96.0% above the OEE world-class standard 

(90% ) and that of the Performance rate 129.3% also above 95% OEE world-class standard (Jain et al., 2013). 

Also looking at Table 4.2, comparing the actual volume of product produced and the target, the margin/difference 

between the actual and target for year three (2019) is 1,407,617 cases and that of year five (2021) is 665,297 cases 

hence the margin was higher positively in year three with over a million cases of the product and hence the year 

with the highest performance for filler Benin plant even though year five recorded highest availability rate. 

However, through the year of the study from year one (2017) to year five(2021), the production targets were met 

and exceeded. This may be attributed to the type of plant maintenance strategy used and in this case, a combination 

of preventive and usage-based was used.  

The Quality rate: 

Table 4.5 shows that the quality rate was 99.9% all through the five years of study.  

Table 4.5: Quality rate of the filler machine 

Year of Study  Quality rate (%) 

Year one (2017) 99.9 

Year two (2018) 99.9 

Year three(2019) 99.9 

Year four (2020) 99.9 

Year five (2021) 99.9 

104.1%
108.3%

129.3%

66.2%

113.6%

0.0%

20.0%

40.0%

60.0%

80.0%

100.0%

120.0%

140.0%

Year one Year two Year three Year four Year five

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70 | A c a d e m i c  J o u r n a l  o f  S c i e n c e ,  E n g i n e e r i n g  a n d  T e c h n o l o g y  

|  https://topjournals.org/index.php/AJSET 

From Table 4.5, it was seen that the quality rate was 99.9% throughout the five years of the study of the filler 

machine RGB Benin plant. This will be attributed to the quarterly refit/overhaul done on the equipment year-

round. This quarterly maintenance program is done on this machine. The refit is carried out four times every year 

on each plant, the filler is refurbished and the result is this excellent quality rate/quality product. 

However, this represents the usage-based maintenance recommended by the equipment manufacturer which is 

being followed by the NBC plants. Apart from the routine preventive maintenance strategy, refit (usage-based) 

being combined gives a quality rate that met and exceeded the OEE world-class standard of 99% (Jain et al., 

2013). With the right plant maintenance strategies 99.9% quality rate was obtained. 

5.1 Summary 

This was a retrospective study on the evaluation of maintenance in food and beverage manufacturing industries 

using Nigerian Bottling Company (NBC) Ltd, Benin Plant Owerri Plant, and BONS Industries Limited, Enugu. 

Machines for the study were Filler (Krones), and Packer/Palletizer for NBC while Blow Mould, Monobloc, and 

Packer/Caser for BONS Industries Limited (these are Bottling line equipment). It was found that the maintenance 

approaches used were preventive and usage-based in NBC while BONS Industries Limited used Preventive and 

condition-based based.   Availability rate, performance rate, and quality rates were high in both industries 

although NBC was better for both Benin Plant – South-South and Owerri Plant – South-East. This was because 

of the maintenance strategy used generally by NBC Ltd, there is a quarterly refit on all production line equipment 

yearly. This means that there is a major maintenance/overhaul/refit schedule four times each year and a normal 

routine preventive maintenance is done routinely. 

However, all these maintenance activities are done in NBC with the embedded equipment manufacturer’s 

engineers/technicians team. Also, the manufacturer’s (KRONES Germany) maintenance recommendations were 

Quarterly refit/overhaul and weekly preventive maintenance. 

5.2 Conclusions 

The approaches used for the maintenance of these machines in these manufacturing companies are preventive and 

usage-based in all the NBC plants used in this study and preventive and condition-based in BONS Industries 

Limited. The availability rate, performance rate, and quality rate were high however performance rate was lower 

in the year 2020 in both companies due to the reasons given above (COVID-19 Pandemic).  However, it was 

concluded after going through this study that the combination of preventive maintenance and usage-based 

maintenance strategies is the best and should be adopted/used by the food and beverage industries for optimal 

output and improved equipment performance.  

The cost of maintenance is better in NBC Ltd than in BONS Industries Ltd, The cost per case is also higher in 

BONS Industries than in NBC which is lower and considered favorable and friendly to the company’s profit 

margin. For NBC the CPC value is within two digits which is the standard/target for the company’s CPC. That of 

BONS the value is up to three digits which is higher than the standard value for a manufacturing firm. Hence, the 

combination of Preventive and Usage-based (overhauls) is considered better than the combination of Preventive 

and Condition-based used by BONS Industries Ltd. 

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|  https://topjournals.org/index.php/AJSET 

5.3 Recommendations 

It is recommended that companies should carry out routine preventive maintenance and usage-based maintenance 

such as periodic machine overhauls since better result was obtained when compared to preventive and condition-

based based. For local/ Indigenous companies like BONS Industries Ltd, local manpower should be trained on 

machine maintenance, and in some cases of overhaul or refit, the owners/manufacturers of the machine should be 

involved as routinely done by the NBC plants. 

Also, the equipment manufacturer’s maintenance recommendation should always be followed to achieve a highly 

favorable machine performance like that of NBC Ltd. The equipment manufacturer’s guidelines/recommendation 

for maintenance are Preventive and quarterly refit which is usage-based maintenance. For BONS Industries 

Limited the equipment (China) manufacturer’s recommended routine preventive maintenance only. However, the 

company included condition-based maintenance to manage their equipment. 

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Impact Factor: 6.67 

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72 | A c a d e m i c  J o u r n a l  o f  S c i e n c e ,  E n g i n e e r i n g  a n d  T e c h n o l o g y  

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 Academic Journal of Science, Engineering and Technology 

Vol. 9, Issue 3; May-June 2024; 

ISSN: 2837-2964 

Impact Factor: 6.67 

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73 | A c a d e m i c  J o u r n a l  o f  S c i e n c e ,  E n g i n e e r i n g  a n d  T e c h n o l o g y  

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