Improving the Maintainability and Reliability in Nigerian Industry 4.0: Its Challenges and the Way Forward from the Manufacturing Sector

The importance of experimental and computational approaches for comprehending various components of technology and machinery utilised in production systems has been heavily researched. The relationships between the different system configuration-derived components, such as series, series-parallel, K out of N, and so on, are referred to as structural dependency [12]. For this kind of system setup, condition-based maintenance has been thoroughly examined. Because resources are typically scarce in an industrial operation, resource reliance results. For example, three machines may share the same specified bearing as a replacement component, and there may be a need for more maintenance personnel. Other factors that may be constrained include staffing, labour, storage space, finances, suppliers, and logistics. As a result, these factors may need to be shared. This dependency should be considered at the planning stage since it might reduce system availability. Different units' deterioration and failure processes may be correlated; this correlation is known as stochastic dependency. For instance, failure of one component might result in damage to or potential loss of other members in a failure-induced damage scenario. Combined condition-based and age-based maintenance strategies may be used in this situation. However, implementing a systematic maintenance detection method can significantly improve the maintainability and reliability of engineering operations in the manufacturing industries [13-15]. These three major enabling technologies—the Internet of Things, wireless sensor networks (WSN), and ubiquitous computing—allow high-performance computing to operate efficiently and cost-effectively in the manufacturing sector to enable sustainable operations regarding maintainability and reliability.

These techniques are employed in manufacturing process performance, material design and development, structural mechanics, and automation systems' bespoke design and engineering that consider cost, performance, and the viability of industry-scale implementation [16]. The manufacturing industry has significantly developed due to societal and economic changes during the past 100 years. Manufacturing technologies and new paradigms have been established to handle financial issues and satisfy social demands because of distinct requirements in various eras [17]. Henry Ford created the moving assembly line in 1913 in response to the need for cost-effectiveness, which launched the mass production paradigm. Consistent product quality has been a primary focus since the Japanese industrial sector began developing lean manufacturing methods in the 1970s [18, 19]. The advent of flexible manufacturing systems (FMS), which allowed the production of a range of goods on the same manufacturing system, was helped by the development of computer numerical control (CNC) equipment in the late 1970s [20-24]. This analysis is to assist sustainability in improving the availability of the machines via maintainability and reliability operations, as presented in Figure 2. The synchronisation of standardisation, interchangeability, fault isolation, diagnostics, and repair with the accessibility of modularisation significantly affects the tooling, test equipment, human actors, and lifecycle of the facilities in the manufacturing industries.

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Figure 2. A structural system for improving availability via maintainability and reliability for manufacturing industries

2.1 Maintainability scheduling in the production system with the analysis of Industry 4.0 Technologies

Maintainability is the chance at which a malfunctioning machine, component, or entire manufacturing system will be brought back into operational efficiency during the restoration period when done by the prescribed protocols. A specific time frame [25-28]. To put it another way, maintainability is an assessment of how easily product maintenance and repair are possible. Consequently, a product's good maintainability will Increase the capacity to be repaired and serviced, lower the maintenance cost, and provide assurance that the item would be suitable for the intended use. This should maintain the components so they may continue to fulfil their purpose. However, the equipment's continued operation depends on its creators, as well as its builders and operators, i.e., not only the maintainers [29-31].

A maintenance strategy is created and implemented in three steps: (1) Create a plan outlining the tasks for each component. (Ex., work identification); (2) Obtain the resources (skilled workers, spare parts, and equipment) required to manage the suggested method successfully (3) Put the plan into action by acquiring and deploying the systems needed to manage the using resources wisely). The goal is to enhance equipment uptime while minimising expenses [32]. Tsarouhas [33] calculated the reliability, availability, and maintainability (RAM) study based on historical information obtained over a year. The data were subjected to a Pareto analysis, descriptive statistics, trend, and serial correlation test. Each machine's failure and repair data parameters and the ice cream-producing system were calculated. The RAM analysis evaluates the present operations management and enhances the line's quality, productivity, and efficiency performance. Preventive maintenance times for each machine and finished system for various dependability periods were discovered. The packing machine and freezer tunnel are the two machines with the lowest reliability rates. This equipment is essential; careful maintenance is required to prevent quality and productivity losses. The exogenous machine, the ice cream machine, and the entire production system have the poorest maintainability and productivity. Furthermore, because the RAM indicators were developed to measure and improve machine performance, production managers and engineers can quickly assess the choices made in the system's operation.

Systems for autonomous manufacturing that can run smoothly, effectively, and qualitatively are required due to global competitiveness. Unexpected production machine failures in an automated system with multi-stage, fast manufacturing processes can be costly. Failure of equipment to perform as required is a common reason for manufacturing machine breakdowns. This immediately adds to production waste, such as preparing for unanticipated downtime or product returns [34]. Therefore, significant dependability information is essential to forecast the cost of unplanned downtime, identify spare parts, and suggest the ideal maintenance intervals. A good reliability program will ensure the gathering of crucial data about the system's reliability performance throughout the operating stage. It will direct the use of this data in analytical and management techniques. Valid data collection and analysis are necessary for good, effective reliability programs and maintenance development and the creation of reliability models to support decision-making processes [35]. Most industrial systems are highly complex, although they are frequently repairable. In those conditions, strong reliability, availability, and maintainability (RAM) research might play a crucial role in the design phase and in any necessary modifications to attain the optimal performance of these systems. However, assessing the RAM characteristics of such systems with the desired level of precision takes work, using both accessible and unreliable data.

The need for high-quality produced goods is rising today [36]. Companies must ensure their interests work well, which entails high availability, safety, and minimal maintenance costs, to remain competitive in the global market. A product's inherent capacity to be maintained significantly impacts the user experience throughout the service phase. Maintainability is a property of goods essentially decided during the design phase. A product's ability to be maintained depends on several factors: visibility, reachability, available space, maintenance safety, and customer demands. The ultimate objective of these components is to expedite maintenance and guarantee that it proceeds safely.

Product Lifecycle Management (PLM) software like Digital Enterprise Lean Industrial Interactive Application, Dassault Structures and JACK allows designers to design maintainability in the early design stages digitally (Siemens Tecnomatix Jack). However, this design approach has several significant areas for improvement, contributing to the maintainability design's low efficiency and accuracy. First, the designer needs to be an expert in creating maintainable designs. A real engineering difficulty is having a designer with such expert maintainability expertise, however. Second, while some PLM Software has tools for maintainability models and analysis, engineers must spend much time creating simulation animations using a key-frame controller, which does not match the demands of rapid turnaround times. Maintainability design is the process of the closed loop and iteration, which is last but certainly not least. Design, verification, assessment, and feedback are all components of the complete maintainability layout process. However, the current approach to creating maintainability is open-ended and only relies on the PLM software’s features. The visual cone and the envelope ball are two examples of functionalities too basic to fulfil the design requirements.

Model of a serial-parallel multistage manufacturing system's production, quality control, and preventive maintenance [37]. Each stage has many machines to achieve productivity and line balance requirements. The devices become less effective with us, affecting the final output’s quality. To safeguard stock against unpredictability, a make-to-stock manufacturing approach is implemented. Each level of processing involves quality inspections on every item. Non-conforming goods are discarded while conforming things are transported to the following step for additional processing. Preventive maintenance is carried out during production runs to increase the machines' dependability and, as a result, the quality of the final output. Machines are examined and, if required, serviced after manufacturing runs. The suggested maintenance plan is unusual because productivity and the machine’s important structural measure are considered when choosing which machines to maintain. To reduce the average cost rate, it seeks to identify the production run duration, quality control threshold, and maintenance threshold concurrently. A simulation-based optimisation strategy combining Monte Carlo Simulation and evolutionary algorithms solves a stochastic mathematical problem.

A proactive, profit-driven strategy is needed to close the gap between actual expenditures and desired expenses. The ability of Nigerian industries to create goods could be improved by downtime, which lowers average output rates, increases operating costs, and degrades customer service [38]. Lean total-quality management (TQM) and misused just-in-time (JIT) strategies can significantly increase downtime. Implementing total productive maintenance (TPM) and reliability-centred maintenance (RCM) as organisational improvement initiatives is therefore highly desired. TPM calls for a collaborative effort between operators and maintainers to save waste, lessen downtime, improve product quality, and increase equipment efficiency. RCM entails figuring out what must be done to keep any physical component functioning as its user wants it to. Determining the maintenance requirements and ensuring they are satisfied as inexpensively as feasible are the two goals that must be accomplished. RCM focuses on a small, multidisciplinary team employing the appropriate abilities to operate and maintain equipment. Such teams have been used to resolve and eliminate sporadic, catastrophic, and recurring failures thanks to several root-cause analysis (RCA) methodologies. The key to success is ensuring everyone involved once employees have received the necessary training in these strategies. The company should build the organisational disciplines and processes to guarantee usage whenever the circumstance calls for them. It is crucial that everyone concerned accepts responsibility for the issue.

Bush [39] pointed out that managing people entails more than simply regulating their behaviour. Effective management calls for competent leadership with a distinct vision and goal and the provision of the money required to carry out the program that all parties have agreed to. TPM was created due to TQM, lean management, and JIT developments. Unfortunately, in Nigeria, these ideas have not yet gained much ground. A quality maintenance program's fundamental tenet must permeate the whole company if it is to be successful. What is required is a factual, enumerated approach to decision creating, respect for other organisations, promotion of creativity, and emphasis on constant development rather than placing fault when errors happen. These are the required things, i.e., signs that a company is evolving.

Machine wear and tear increase over time during production cycles, significantly influencing product quality and system dependability. The use of the machine degradation status, the structure importance measure, and the quality information feedback for helping maintenance decision-making describe a novel integrated maintenance method that is introduced [40].

More particularly, due to technological limitations, the machines can only be examined to assess their states after manufacturing runs, after which any necessary maintenance is carried out. An opportunistic maintenance technique is used using quality information feedback during production runs. The goal of concurrently improving production, quality control, and maintenance procedures is to reduce the anticipated total cost rate. A stochastic mathematical model is constructed and solved using a simulink optimisation technique. (1) A serial-parallel multistage production system is evaluated for jointly optimising manufacturing, quality assurance, and maintenance strategy; (2) Condition tracking and effective data feedback are both integrated into the maintenance choice procedure; and (3) Because there is a limited amount of maintenance time between two sequential production runs, the structure importance is also evaluated, furthermore to the forecasting reliability. For the flexible multistage manufacturing system in multi-specification and small-batch production, a maintenance scheduling approach has been developed [41].

The key factors are the unpredictable nature of future production demands and the bidirectional linkages between production and station decay. The dynamic production schedule causes each station's workload to fluctuate, significantly affecting how well each station holds up over time. The choice of the station to carry out the production activities will, in turn, be influenced by the station's degradation condition. A cost-effective maintenance schedule model is then suggested for the system based on the load-integrated degradation model created due to this interaction. Because future production demands are unclear, the system's best preventive maintenance plan is achieved by reducing the anticipated total maintenance cost per unit of time within the next unknown production period. A greedy constraint method is created with the time of preventive maintenance as the constraint to streamline the solution procedure. According to numerical comparisons, the projected total maintenance cost under the suggested maintenance schedule model is consistently less than that under the full and average load models.

Equipment maintenance is crucial for increasing production efficiency, and how to incorporate maintenance into production to deal with ambiguous situations has drawn much interest [42]. The topic of this study is the preventive maintenance (PM) integration into production planning of a complex manufacturing system based on availability and cost. The suggested strategy is divided into two parts. First, this study uses an extreme learning machine algorithm to forecast the needed capacity of each machine. Based on an analysis of historical data, the optimal times for executing PM tasks are determined to minimise their negative effects on productivity and determine the PM interval and length. Second, this study uses an enhanced ant colony optimisation method to determine the schedule planning and the least amount of maintenance workers. Finally, this strategy's viability and advantages are examined. Based on empirical research using actual manufacturing execution system and equipment maintenance system historical data. Experimental findings show the viability of the suggested strategy, which reduces human requirements while maintaining maintenance responsibilities. Consequently, the suggested strategy helps to increase the business's production efficiency. Small quantities of goods may be produced in the manufacturing sector to save inventory costs, albeit this may unintentionally raise setup costs [43].

This presents a difficulty in optimising the lot size to increase the manufacturer's economic gain, a topic that has been extensively researched for a long time. The best lot sizes are often achieved by minimising the total inventory storage and setup cost. In real life, a production system might malfunction, necessitating maintenance. This presents even another difficulty in determining the best maintenance plan to minimise the likelihood of system failure in the future. For manufacturers, issues include increasing manufacturing costs and stricter efficiency standards. Enhancing maintenance effectiveness is a key strategy for overcoming these obstacles, and several publications are on this subject. Before creating a fresh batch of product items, a multi-product system might need to be reset. To lessen the disruption brought on by the maintenance procedures in this situation, the set-up epoch might be used as a maintenance window.

One of the cornerstones of the fourth industrial revolution is smart manufacturing (Industry 4.0) [44]. It is not only opens up positive prospects for highly reliable, available, maintainable, and safe manufacturing processes, but it also makes the systems more complicated to analyse for health. To address these issues, it is necessary to have a solid strategy for tracking and evaluating the system's health. The manufacturing sector greatly impacts societal and economic progress [45].

Since the term "Industry 4.0" is widely used by universities and research organisations, it has generated much attention from both the commercial and scientific sectors. Although the idea is not novel and has been discussed from various angles in academic circles for many years, the term "Industry 4.0" has only recently been coined and is already gaining some traction outside of the academic community and in the industrial society. Whereas academic research focuses on comprehending and defining the concept and attempting to develop related technologies, business models, and respective techniques on the other, industry, on the other hand, focuses its attention on the evolvement of industrial machine suits and intelligent products as well as potential customers. Businesses first need to understand the features and content of Industry 4.0 to prepare for a future change from manufacturing dominated by machines to digital production. Nigerian industrial industries must carefully assess their situations and individual potentials in relation to the fundamental criteria outlined for the Industry 4.0 standard if they are to transition successfully. They will be able to create a clear road map as a result.

Modern marketplaces are characterised by quick requirements changes and emerging client needs [46]. Therefore, quick changeable production is a key objective of the Industry 4.0 strategy, which intends to increase manufacturing's adaptability and efficiency by integrating different factory components and virtualising the industrial assets in digital twins. The use of scenario-based evaluation to investigate the changeability capabilities of Industry 4.0. We arrive at three possible change scenarios that a plant can experience: Product flow might change depending on product kind, quality, and the launch of a new product. Based on the impact of the resulting transformation, we compare the third industrial revolution (Industry 3) with Industry 4.0 designs using these scenarios.

The Architecture-Level Modifiability Analysis (ALMA) technique is what we use for our evaluation, and Presenting ALMA 4.0, a guideline for Industry 4.0 Maintainability scenario-based evaluation, describes its instantiation to the provided situation. Manufacturing firms must implement more sustainable production and facility control techniques in response to growing worries about climate change and energy deficit [47].

Such methods necessitate operational procedures prioritising sustainability by concurrently considering economic, energy, and environmental factors. To concurrently solve the issues of energy consumption, intelligent maintenance, and throughput enhancement, a novel combined production scheduling model that considers energy control and maintenance implementation is suggested in this work. Several measures are combined and assessed to achieve a single goal: cost minimisation. The cost minimisation issue is solved using particle swarm optimisation with a local optimal avoidable mechanism and a time-varying inertial weight to discover a close-to-optimum solution for production and maintenance schedules. A complicated network that stretches from oil and gas fields to demand nodes is known as the hydrocarbon supply chain (HCSC) [48].

Since the petroleum industry is the most important sector of the global economy and any interruptions or changes in the supply of hydrocarbon products would impact the whole global economy, it is imperative to integrate operation and maintenance operations throughout this intricate network. Therefore, thorough and efficient maintenance increases the reliability of an asset and extends its lifespan. The maintenance tasks are preferably carried out during periods of low demand to minimise significant losses in production and, ultimately, to fulfil client demands. Operating planning and maintenance scheduling decisions are interdependent and should be optimised together [49-55].

Sustainable manufacturing processes are crucial for production industries, but individuals putting production systems in place need help achieving this reliability objective. In this manner, a production system is modelled using a fundamental economic-production paradigm with a storage restriction and demand-dependent unit production cost under carbon emissions [63]. More reliable manufacturing companies create fewer faulty goods than an unreliable production system. A geometric programming technique is the best to create a quasi-closed form of the ideal solution since the model includes a power function. Geometric programming is a suitable analytical method to tackle this issue in a production system. The production system is considered dependable when waste created during the manufacturing process is controlled or reduced while maintaining product quality and mitigating any unfavourable environmental consequences. The production model is new since it depicts a dependable method for producing goods while minimising carbon emissions and faulty product manufacture. To build a dependable manufacturing system while reducing carbon emissions, waste must be managed while product quality is preserved. A reliable production system model that included reliability as a decision variable under carbon missions was built on the foundation of a basic economic production system. The model aims to save costs and enhance current manufacturing processes by adding dependability as a quantifiable attribute under carbon emissions. The following fundamental premise is applied to construct a trustworthy production system model: Fewer faulty items are produced by more reliable production processes. The main objective is to create a carbon-controlled production system that is 100% dependable, defect-free, and operates with regulated carbon emissions, which is a sign of an ideal environment for green manufacturing.

Demand is what determines the cost of unit production under carbon emissions, and high demand for dependable items corresponds to lower unit output; as a result, if demand rises, production must also rise to avoid shortages. As a result, without considering shortages, an increased production rate results in lower unit production costs. As a result, the unit production rate and the demand rate must be inversely related.

Figure 5 provides a graphic representation of the relationship. The cost per unit of production for carbon emissions is regarded as p = αD−β, where α is the capital investment's yearly fractional cost. And β measures price elasticity (α > 0, β > 1). Modern technology may be used to produce goods more effectively. Although managers may create large quantities when there is considerable demand for a reliable product, small batches have lower storage costs. So, a storage space restriction is taken into account. Another reliability restriction is used since no product can be completely dependable [63].

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Figure 5. Demand and unit production cost relationship

Digitalisation and sustainability affect every step of the production process [64]. Digitalisation and sustainability are crucial issues for the manufacturing sector. Businesses are adopting the fourth industrial revolution's sustainability-related ideas through several different projects and strategies. One of the recurrent themes in smart and sustainable manufacturing is the application of contemporary maintenance techniques, such as Maintenance 4.0. From the standpoint of the difficulties presented by the fourth industrial revolution and the difficulties associated with sustainable growth on the economic, environmental, and social fronts, the most recent developments in maintenance management in Nigeria should consider intelligent and sustainable maintenance from three angles. The first is the historical viewpoint, which highlights how the maintenance method has evolved in line with the advancement of production engineering. The development perspective, which offers historical insights on maintenance data and data-driven maintenance technology, is the following: The third viewpoint discusses maintenance about the elements of sustainable development and potential ways to use data-driven maintenance technology to address the financial, environmental, and social issues associated with sustainable production. Many businesses are looking to rethink their production practices and philosophies in light of the increasingly unstable political, economic, environmental, and societal environments, as well as the pressures of globalisation, rising competition, and manufacturing systems, products, and technologies with very short lifespans. Their goal is to increase the number of product variations while maintaining manufacturing efficiency. Consequently, manufacturing systems must be extremely adaptable and reconfigurable to flourish and meet these demanding objectives. The idea of reconfigurable manufacturing systems (RMS) originated in this setting in the late 1990s to get beyond the constraints of traditional production and to adjust quickly and economically to shifting market and societal situations. Due to its fundamental qualities, including scalability, convertibility, diagnosability, customisation, modularity, and integrability, RMS is seen as a catalyst for Industry 4.0. Moreover, reduced energy use and carbon footprints are essential in the industrial sector due to rising fuel prices, increasing electricity usage fees, and environmental laws. Therefore, considering sustainability while developing an RMS is essential to meeting the demands put forward by the environmental and societal surroundings [65].

4.1 Sustainability issues relating to the effects of reliability and maintainability

According to Dahmani et al. [66], engineering, manufacturing, and design are just a few of the many fields that sustainability has touched. Companies now consider sustainability to be a major problem. Statistics show that over 37%, if not 50%, of the world's total greenhouse gas (GHG) emissions come from manufacturing that uses energy sources, including electricity, coal, oil, and gas. Because of this, businesses have begun to take action to reduce GHG emissions from their products and services. Sustainability has been described as the reorganisation of technical, scientific, environmental, economic, and social resources to allow for the regulation of the causing system in a condition of temporary and spatial balance. In a sustainable future where human life quality is consistently increased in terms of enjoyment and prosperity related to sanitation, education, food, shelter, and employment, the need for healthcare, work happiness, etc., arises swiftly. At the same time, limitations on sustainable growth are set by local and global socioeconomic and statistical settings. Many aspects of sustainability evolution exist, including the economy, environment, and society. Sustainability is the evolution that satisfies the demands of the present without compromising the capacity of future generations to satisfy their own needs. These several factors were acknowledged as the cornerstones of sustainable development, and the sustainability model took them into account. The competitive worldwide environment is impacted by similar issues, such as scheduling and loading challenges, expensive tooling and equipment costs, abundant scrap availability, challenging quality control, and lengthy setup times. To increase firm profitability and improve product support design, a higher level of connection between design and manufacturing processes is needed in Nigeria's production industries. Poor dependability in any manufacturing company results in failure and availability at every level, including design, construction, planning, maintenance, etc. Figure 6 shows the relative analysis of reliability and maintainability when it pertains to the issue of sustainability in the manufacturing industries. The art of maintaining the reliability of a machine through maintainability leads to quality availability, which significantly affects the product's cost.

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Figure 6. Relational study of the effects of reliability and maintainability as regards sustainability issues

The dependability measurement lowers the overall failure rates in Nigerian-producing organisations by quantifying prospective performances [67]. Failure lowers total revenue and production. For businesses aiming to increase dependability, failure must have a clear meaning. Most of the manufacturing process has been centred on scheduling and short-term production planning in Nigerian production enterprises over the previous 20 years. Due to the intense competition around the globe today, manufacturing companies in Nigeria are under pressure to meet the constantly changing needs of their customers quickly. Because the business climate is so fiercely competitive, improving product quality while keeping costs as low as feasible is important. Maintenance service is one of the most often utilised elements, particularly in a manufacturing line that constantly needs repair. To get the best management of production rates, the manufacturing sectors are attempting to improve the operations existing in the production lines. The installed machine in the production line directly impacts the product’s performance. It becomes necessary to analyse the maintainability and reliability to give ideal strategies if the machine introduced into the production lines is not predictable and trustworthy. Failures in the manufacturing lines result in unintended outcomes like lengthened delivery times, subpar products, and negative.

Financial effects like excessive production costs. Maintenance management activities are crucial in lowering the amount and quality of goods produced, the number of faulty components produced and the loss of system running time. They also lower the production system, product quantity, and quality losses. In the past, manufacturing line process failures were eliminated by upgrading functional and operational excess or replacing and evaluating important systems. The high maintenance costs and limited availability introduce a decrease in support time, high dependability, and maintainability in the manufacturing process. Each system component's effective preventative maintenance over time lowers total unforeseen costs and makes it easier for the business to operate within its budget. A manufacturing system or equipment must first be evaluated for performance and upkeep requirements before being acquired by an industrial firm. The maintenance procedure used to keep a system or component at a specific level of dependability and availability is also used to keep product quality at a specific level [68].

Businesses in Nigeria with poor maintenance procedures will incur high production expenses. The dependability analysis, which also provides suitable maintenance methods, should be employed to determine the system's efficacy. The reliability indices and RAM principles are universally recognised technical methods for identifying production bottlenecks, issues with critical components, and optimising maintenance activities [69].

The mean-time-to-repair (MTTR), mean time-between-failures (MTBF), and failure rates influence the dependability of the equipment on the production line. As a result of enhanced maintainability and reliability initiatives, the system will have high availability. Production availability is always tightly associated with the maintenance and reliability of the equipment and components. Any one of the following three criteria can be used to gauge a system's effectiveness: availability, reliability, and maintainability [70]. The RAM analysis would help the Nigerian manufacturing system identify the correct degree of operation and particular safety concerns for continuous development. Ineffective production systems, optimisation and prediction algorithms play a key role.

Sousa et al. [71] argue that the corporate world constantly changes. Dynamic complexity, ambiguities, and uncertainties call for quicker and more assured judgments. Industry 4.0 is a crucial option to remain competitive in this climate. Manufacturing dependability in this context is crucial for businesses to make wise decisions. In the literature, several Industry 4.0-related technologies, such as the Internet of Things (IoT), cyber-physical systems (CPS), blockchain, and data mining, have increased equipment availability. However, survey research still needs to demonstrate how reliability has partnered with support for organisational decision-making in the context of Industry 4.0. Most applications still primarily concentrate on the efficiency and condition of certain pieces of machinery. However, in today's volatile environment, local decisions are no longer adequate in complicated enterprises; an organisation's whole structure must be analysed.

The necessity for trustworthy data on the long-term performance of building materials-producing industries in Nigeria, especially the anticipated service lives of building materials, components, and assemblies, is at the core of sustainable building practices [72]. Given the predicted effects of climate change on the built environment and the numerous global government initiatives to ensure that structures are resilient at construction and can maintain their resilience over time, this need is becoming increasingly obvious. Key climatic factors projected to change and impact how long construction materials last are described, allowing for the specification of goods given the impacts of climate change. Lower heating loads, as seen by quieter heating degree days, and higher cooling loads, particularly in most parts of Nigeria where heat island effects may predominate over climate change for months, will result from rising world temperatures. Inattention to intense heat events may result in overheating in structures, which raises health risks for the most vulnerable members of society, including the elderly, physically ill, and very young people. Buildings may need to be able to operate efficiently in terms of heating or cooling, depending on the season. This might result in inefficient energy usage.

4.2 Maintainability implementation

Zhu et al. [73] investigated and stated that design for maintainability is becoming better known. Unfortunately, there is no comprehensive examination of the numerous connected problems and studies. Meier and Russell [74] found that while maintainability can significantly impact project costs, most businesses need a systematic mechanism for addressing it during the completion of projects. The Building Projects Institute established the Maintainability Study Team to address the potential available to companies by effectively implementing maintainability concepts. Although maintainability can significantly affect project costs, most companies need a structured strategy to handle it throughout the project delivery process. The Construction Sector Institute created the Maintainability Researcher to explore the potential that organisations can take advantage of by effectively using maintainability concepts.

The maintainability research team at the Construction Industry Institute (CII) has created a model method for implementing maintainability with six milestones [75]. Commit to establishing maintainability, set up a maintainability program, get its capabilities, plan for it, carry it out, and update corporate programs. The six benchmarks are divided into corporate and project levels via the CII's milestones for maintainability. Gao et al. [76] provide a conceptual illustration of serverless computing-based WSN maintainability implementation. The ability to meet the minimum resource requirements for the WSN product with a higher likelihood during the setup, trial production, testing, batch production, deployment, operations, and maintenance stages is referred to as the "maintenance-ability implementation.

Saghatforoush et al. [77] examined that, with appropriate and timely inputs into the first phases of the design and planning of a project, the constructability idea unifies individual building functions and experiences. It tries to make the construction process easier to achieve the overall project objectives more effectively and efficiently. Similarly, the operability and maintainability ideas include O&M (operation and maintenance) tasks, project planning, and design knowledge. Several studies claimed that infrastructure projects could have been delivered at their best by implementing these ideas independently.

This study reviews the current literature on the maintainability and reliability of the manufacturing industry in Nigeria with the operation of Industry 4.0 technologies. The study also highlighted its challenges and the way forward. It is worth knowing that Nigerian industrial managers need a culture that can deal with quick changes more successfully if they want to instill a competitive mindset in their manufacturing sectors. To do this, total preventive maintenance (TPM) should be introduced. The challenge of trying to do things better is the foundation of TPM, so coping successfully with change, which frequently requires quick alteration, needs to become ingrained in manufacturing organisations. To successfully adopt TPM, personnel within an organisation must be prepared to accept "change" for the better. The speed at which they move toward that aim depends on how keen they are to accept "change." Only an organisation that provides the required training and time to monitor its success can implement TPM successfully. Or the failure of the subsequent measures for change. With the utilisation of the suggested models and tactics, there should be a new mindset and recalibration of what is anticipated in current organisations. This should be self-assessed and compared to world-class industries with comparable product lines to achieve sustainability in terms of maintainability and reliability in Nigeria’s manufacturing industries. The following are signs of the implementation of this study, they are:

1. The industry will be able to achieve a Lengthen asset lifespan of their equipment for sustainable production.
2. Reduced the risk of a constant equipment breakdown leading to excess idea time. Which, in return, it will increase efficiency and decrease unplanned downtime in the industry.
3. It will promote the safety and health of the workers. And boost customer satisfaction and increase profitability.

The operational process of industrial 4.0 is very significant to enable the industry to automate many operations while reducing stress on the staff.