Defining Recession

A recession is a contraction phase of the business cycle where significant decline in economic activity lasts more than a few months, which is normally visible in real GDP, real income, employment, industrial production, and wholesale-retail sales.

Global Prospective

The current economic recession has hardly spared any country on earth. Rich countries like USA, UK, Germany, Australia, Japan, Canada- almost all the rich countries have got badly hurt from the recession. So, there is no reason to be surprised to know that Indian economy is also getting hurt from the global economic recession.

Impact of Recession on Indian Economy

The following graph shows the changing trend over the Years in all the major sectors which contributes the overall development of the Indian Economy

• Low or No Appraisals • Salary Cuts • Layoffs • Less Hiring's • Minimal projects in hand • Declining share in global market • No Plans for Greenfield projects • No diversification or expansion

Present Scenario

• As per a survey of 480 Indian companies over December 2008 and January 2009 conducted by hr consultancy firm Hewitt - despite the economic slowdown, a majority of Indian companies are still hiring employees. Here are some interesting revelations of this survey • Average salary hike in India in 2009 will be 8.2% (the highest in the Asia pacific region however first time in six years that India is likely to see single-digit salary increases) • Projected salary hike is lower than the increase of 13.3% seen in 2008 • The hike higher than china (8%) USA (3.2%) and Japan (2.3%) • Sectors expected to see the highest raises are FMCG, durables and telecom. • Healthcare is sector that is doing well globally and in India. In 2008, hospitals had awarded the lowest salary increases but have been placed among the top five sectors for 2009.

Nowadays, plant maintenance has gained significant recognition as a very important process, which can be transformed to a potential profit generator for the corporation. The development of a suitable maintenance concept enables the decision of specific maintenance strategies based on the existing situational factors that affect the organisation. A clear maintenance concept permits the design of the maintenance system that will be responsible for efficient and effective plant maintenance.

The definition of maintenance often states maintenance as an activity carried out for any equipment to ensure its reliability to perform its functions. Maintenance to most people is any activity carried out on an asset in order to ensure that the asset continues to perform its intended functions, or to repair any equipment that has failed, or to keep the equipment running, or to restore to its favourable operating condition. Over the years, many new strategies have been implemented as maintenance strategies which are intended to overcome the problems which are related to equipment breakdown. Some of the common maintenance strategies are predictive, preventive and proactive.

Proper maintenance of plant equipment can significantly reduce the overall operating cost, while boosting the productivity of the plant. Although many management personnel often view plant maintenance as an expense, a more positive approach in looking at it is to view maintenance works as a profit center. The key to this approach lies in a new perspective of proactive maintenance approach.

There are a number of important reasons for having an efficient, well‐organized, cost‐effective and innovative maintenance team including:
• Ensure high plant availability
• Ensure equipment reliability
• Deliver effective maintenance
• Ensure value for money
• Provide best maintenance practices
• Guarantee statutory compliance

Effective maintenance requires an understanding of current maintenance practices and capability, clear ideas about areas requiring development and a realistic plan for putting this in place.

There are many other challenges facing Plant staff at this time around the issue of reliability and maintenance, including:

• Plant Maintenance Optimization
• Optimizing Condition‐Based Maintenance
• Cost Constraints of a Budget
• Environment improvement
• Energy management
• Shutdowns & Turnarounds

1.Overview of the elements of Reliability

At its very heart, plant reliability is a quest for profitability. Reliable plants are safer. And improved safety translates into higher profitability by reducing the need for potentially high risk maintenance activities, the likelihood of safety related failures and injuries, and the production of off specification products.

o Cost pressures and reliability o A look at Reliability based strategies o Benchmarks and best practices o Key reliability work processes that will transform your plant o Operations and Maintenance Partnership

2. A comprehensive look at various reliability/maintenance practices
Reliability affects the bottom line. There are both basic and advanced technologies out there that can shape your maintenance program.

o Preventative Maintenance / Essential care o Predictive Maintenance (Condition Monitoring Techniques) o Proactive Maintenance o Operator Driven Reliability

3. PMO – Plant Maintenance Optimization – Maintenance Analysis of the Future

Regardless of how a maintenance has been developed, there is a constant need to review and update the program based on failure history, changing operating circumstances and the advent of new predictive maintenance technologies. The generic process used to perform such analysis is known as PM Optimization
(PMO). PMO as a technique has been refined to reflect the RCM decision logic since the formulation of RCM in 1978 o Cost pressures and reliability o A look at Reliability based strategies o Differences between PMO and RCM: when to apply RCM

4. how to set up an effective Preventative/ Predictive Maintenance Program (condition monitoring program)
A predictive maintenance approach strives to detect the onset of equipment degradation and to address the problems as they are identified. This allows casual stressors to be eliminated or controlled, prior to any significant deterioration in the physical state of the component or equipment. This leads to both current and future functional capabilities. o Reliability Basics o Failure Developing o How to accurately predict equipment breakdown o Equipment life cycle and how to deal with asset deterioration o Selecting the most effective Method o Documentations strategies and pointers on software (CMMS)

5.Root Cause Problem Elimination
An effective root cause analysis process can improve production reliability significantly. But, few organizations have a functioning root cause analysis process in place. This session will discuss common problems and solutions in order to improve root cause problem elimination o An overview o Creative and critical thinking o Root cause steps o Implementing root cause problem elimination in your plant o Case Study

6.Implementing Best Practices in Maintenance Execution, Planning & Scheduling
Given the huge impact maintenance management can have on production output, as well as the increasing tendency for maintenance departments to be asked to do “more with less” – it is essential that Maintenance Managers strive toward the implementation of best practices in maintenance planning& execution o World Class Maintenance Planning o Prioritization and backlog management o Scheduling and Coordination of work o Operations role in Maintenance planning and scheduling o Maintenance of assemblies: Integrating plant, store , workshop and suppliers o Shutdown Management

7.Management aspects if implanting improved reliability
Focusing on management aspects and taking measures to analyze current plans will allow for significant continued improvement of reliability strategies. o Implementation Ideas o Vision, Mission, Goal o Assessing current state vs best practice o Implementation plans o Launching improvement o Cultures and people o Training o Measuring success

What is maintenance

Most engineering, maintenance and operating decisions involve some aspect of cost/risk trade-off. Such decisions range from evaluating a proposed design change, determining the optimal maintenance or inspection interval, when to replace an ageing asset, or which and how many spares to hold. The decisions involve deliberate expenditure in order to achieve some hoped-for reliability, performance or other benefit. We may know the costs involved, but it is often difficult to quantify the potential impact of reduced risks, improved efficiency or safety, or longer equipment life. Not only are the benefits difficult to quantify, but the objectives often conflict with each other (we could clean the heat exchanger more often to achieve better performance, but the cleaning may damage the tubes and shorten their life). Finding the optimal strategy is difficult, therefore, but the wrong maintenance interval will result in excessive costs, risks or losses.
The European collaboration project “MACRO”, has developed a structured set of procedures to make sure that the right questions are asked, and sophisticated “what if?” analysis tools to calculate the optimum combinations of equipment reliability, performance, lifespan and cost. Specifically designed to be used where hard data is poor, and engineering judgement or range-estimates provide the main raw material, these Cost/Risk Optimisation techniques are the acknowledged ‘best practice’ when justifying design, maintenance, condition monitoring, replacement or spares decisions. The following ‘mini-guide’ outlines the underlying concepts of the approach, with illustrations of their application to a variety of decisions.

2 What is “Optimisation”?
The first concept that needs clarifying is the meaning of “optimum”. The word is often used very loosely in phrases such as “the optimum maintenance strategy” or “the optimum performance”. In areas where there are conflicting interests, such as pressures to reduce costs at the same time as the desire to increase reliability/performance/safety, an optimum represents some sort of compromise. It is clearly impossible to achieve the component ideals - zero costs at the same time as total (100%) reliability/safety etc. Reliability costs money, or, to put it the other way around, to spend less money we must choose what not to do or achieve. The resulting and inevitable trade-off can be drawn graphically (see figure 1), but we must be careful with the labelling.

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Cost/Risk Optimisation 2 Copyright The Woodhouse Partnership Ltd 1999

2.1.1 Optimum is defined as minimal Total Business Impact
Many such diagrams show the bottom of the Total Impact curve neatly aligned above the cross-over point of the conflicting components, giving rise to confusion as to where and what is the true optimum. The Total Impact is the sum of the costs and risks etc. When this sum is at a minimum, we have defined the optimum combination of the components: the best value mixture of costs incurred, residual risks, performance losses etc. Crossover points do not signify the optimum; they merely show where the components are equal (i.e. the risks or losses have the same value as the amounts being spent to control them). The concepts of ‘balancing costs and risk’ or finding a ‘breakeven point’ are dangerous, therefore, because they imply this equivalence point as a target, rather than focus on the best value-for-money combination.

3 Why this is difficult to find
If we knew exactly what the risks were, and what they are worth, we could calculate the optimum amount of risk to take, and costs to incur. Similarly, we could make better (more optimal) decisions if we knew the value of improved performance, longer life, greater safety or quality. But the risks are difficult to quantify and many of the factors are “intangible”; i.e. it is extremely difficult to place an economic value on them. The first barrier, therefore, to cost/risk optimisation is the

_ lack of relevant hard data.
This is not the only constraint. Whether or not there is suitable information, the complexity of the interactions is also a barrier. Reliability is a complex subject: the effects of one failure mode upon the probabilities of suffering other forms of failure involve nasty mathematics. These relationships have been known for a long time (over 20 years) but, especially in the absence of useful data, they have been limited in usefulness to academic or special case studies. So, whatever the state of information, the additional problem is

_ how we would use the data if it were available.

3.1.1 “What data?” versus “How would we use it?”
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These problems appear to be linked (if we do not have suitable data, how can we improve the usage mechanisms?) but have, in fact, quite separate effects. The traditional reaction to poor data and subjective decision-making is to a) start collecting more/better data and b) hope that it will somehow tell us what to do. This approach does not work. Without knowing how we would use it, how do we know what data is worth collecting in the first place? Even if we were lucky enough to guess correctly on the data that is needed, how (and when) would we know that we had collected enough? What is “enough”, and is it physically/economically possible to collect it?
Without a clear idea of how it will be used, and the sensitivity to data inaccuracy, it is impossible to say what data is needed, and to what precision. The first challenge is therefore the understanding of what information is required for specific decisions, and how it should be used. This issue can be addressed by designing and using templates and checklists; to make sure that the right questions are asked in the first place.
Even if hard data is not available, there is a considerable volume of knowledge in the operators, maintainers and engineers. This can be obtained in the form of range estimates or “worst case” and “best case” extremes of opinion. With a range of possible interpretation, we can see if the decision is affected – whether we need to dig deeper, and at what cost. This is achievable if we have the means rapidly to calculate the Total Impact for different assumptions. We must adopt a “What if?” approach to the problem: try the optimistic extreme and the pessimistic – does the data uncertainty have a significant effect?
The calculations require specialist software tools – the maths are too hard for mental arithmetic or even spreadsheets. Given their availability, however, even rough or range estimates can be explored for their effect. Sensitivity testing reveals which pieces of information are important, and which have little or no effect upon the relevant decision. Even with rough guesses, we can find the ‘envelope’ in which the optimum strategy must lie. In a surprising proportion of cases, this reveals that the decision is robust over the full range of data interpretation (i.e. the range estimates are enough to arrive at a firm and provable conclusion).

3.1.2 Using range estimates to locate optimum strategy

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3.2 Example: pump overhauls
If the performance of a pump deteriorates as its impeller becomes fouled, and the reduced capacity is having an effect upon production or process efficiency, then there must be an optimum time to clean the impeller. To determine the best maintenance strategy, we need to know how the performance falls with time or use, the economic effect of the losses (perhaps the pump has to operate for longer to deliver the required volumes, or maybe the drive motor draws more electricity to compensate). We also need the cost of cleaning (including any operational downtime to do it). Some of this information may be known if there is some operational experience, but otherwise it must be range-estimated and explored for sensitivity:
3.2.1 Data estimates:
_ By 6 months of operation, pump performance is 5-10% down, and this is likely to accelerate if left further.
_ 10% lost performance is worth £10-30/day in extra energy/production impact or extended operating costs.
_ The costs of cleaning or overhaul are £6-800 in labour and materials, and 2-
3 hours downtime to swap over to an alternative pump.

3.2.2 Calculating the impact
The first step involves ‘fitting’ a performance curve to the examples given:
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Then, a series of calculations can show the Total Impact of performance losses, cleaning costs and equipment downtime for various maintenance intervals:
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3.2.3 Sensitivity testing
The “worst case” and “best case” interpretations combine the extremes of all the range-estimates. They show that the cleaning interval must be between 11 and 16 months. No interpretation of the problem could justify more, or less, frequent cleaning: [pic]
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DEVELOPING A MAINTENANCE STRATEGY
Presented by
Peter Stock
New Dimension Solutions, Inc.
1 INTRODUCTION
The world of physical asset management has changed dramatically over the last twenty to thirty years. These changes have come in light of businesses becoming more and more dependant on machines, leading to an explosive growth in the numbers of machines that need to be maintained throughout the world. The designs of the physical assets have also changed from robust over-designed machines that required minimal maintenance in 1940’s to more complex and highly automated, mechanized processes of today. Along with this growth our expectations as users and owners of these machines have also changed. Previously our focus was primarily on minimizing downtime and reducing maintenance costs, whereas today not only do we focus just higher availability but we also focus on higher reliability, as well as better product quality. Our attention has also been focused on those failures that have serious safety and environmental consequences. No longer is it acceptable to allow equipment to fail where it is not going to conform to society’s safety and environmental expectations, otherwise we will get shutdown. Finally, as our dependence on physical assets grows so does the cost of owning and operating them continue to escalate.
This is going to have an impact on our return on investment if it not managed properly, hence we need to ensure that the machines operate efficiently and are maintained cost effectively throughout their technological useful lives.
Another area of change is challenging our fundamental belief about the relationship between operating age and failure. In the past we were led to believe that most failures were age related and as a result developed maintenance policies accordingly. This was generally true for those failures where the equipment came into direct contact with the product, i.e. a pump impeller. However, through new research, it is apparent that there is less and less connection between the operating age of most physical assets and how likely they are to fail. We need to point out though that the equipment itself has become more complex and has led to substantial changes in the failure behavior. Consequently, there is not just one pattern of failure but six and these need to be recognized when selecting suitable failure management policies.
Finally, another area where there has been rapid growth is in new maintenance techniques and concepts.
Looking at condition monitoring on its own there are between 300 and 400 techniques of which about a third can be applied effectively to modern day physical assets. Engineers are also are a lot more focused about reliability and maintainability when it comes to designing equipment. Another trend with organizations today is the shift towards teamwork and more involvement of the work force in decision making.
In light of the above, the challenge facing organizations today is to find out which of these techniques will be worthwhile and cost effective.

2 DEVELOPING A MAINTENANCE STRATEGY
Given all the day-to-day pressures facing maintenance managers, the first question is where does one start? The answer lies with the fact that every physical asset is put into service because someone wants its to do something. In other words, it is expected to fulfil a specific function or functions. Therefore maintenance is all about preserving the functions of physical assets to ensure they continue to do what their users want them to do. It is only when these functions have been defined that it becomes clear exactly what maintenance is trying to achieve and precisely what is meant by “failed”. This makes it possible to move on the next step, which is to identify the reasonably likely causes and effects of each failed state. Once failure causes (or failure modes) and effects have been identified, we are then in a position to assess how much each failure matters. This in turn enables us to determine which of the full array of failure management options should be used to manage each failure mode.
At this point, we have decided what must be done to preserve the functions of our assets. This process is often called “work identification”.
When the tasks that need to be done – the maintenance requirements of each asset – have been clearly identified, the next step is to decide sensibly what resources are needed to do each task by asking the following questions:
• Who is to do each task: skilled maintainer? The operator? A contractor? The training department
(if training is required)? Engineers (if the asset must be redesigned)?
• What spares and tools are needed to do each task, including tools such as condition monitoring equipment.
It is only when the resource requirements are clearly understood that we can decide exactly what systems are needed to manage the resources in such a way that the task gets done, and hence that the functions of the assets are preserved.
This process can be likened to building a house. The foundations are the maintenance requirements of each asset, the walls are the resources required to fulfil the maintenance requirements (people/skills and spares/materials/tools) and the roof represents the systems needed to manage the resources (CMMS).
To summarize, a maintenance strategy is developed and executed in three stages:
• To formulate a maintenance strategy for each asset (work identification)
• Acquire the resources needed to execute the strategy effectively (people, spares, tools)
• Execute the strategy (acquire, deploy and operate the systems needed to manage the resources efficiently). In other words build your foundations first, then your walls, then your roof.
In the absence of any comparable asset management strategy formulation processes, the only really effective way to do all this at once for modern, complex industrial processes is to arrange for groups of appropriately trained operators, maintainers, supervisors and specialists who live with the asset on a day-today basis to apply Reliability-Centered Maintenance under the guidance of a suitably qualified facilitator.

3 RELIABILITY-CENTERED MAINTENANCE
Reliability-centered Maintenance is defined as ‘a process used to determine what must be done to ensure that any physical asset continues to do whatever its users want it to do in its present operating context’. The RCM process entails asking seven questions about the asset or system under review, as follows:
• What are the functions and associated performance standards of the asset in its present operating context?
• In what ways does it fail to fulfill its functions?
• What causes each functional failure?
• What happens when each failure occurs?
• In what way does each failure matter?
• What can be done to predict or prevent each failure?
• What should be done if a suitable proactive task cannot be found?

3.1 Functions and Performance Standards
Part two of this paper mentioned that it is only when the functions of an asset have been defined that it becomes clear exactly what maintenance is trying to achieve, and also precisely what is meant by “failed”.
For this reason the first step in the RCM process is to define the functions of each asset in its operating context, together with the associated desired standards of performance. The users of the assets are usually in the best position to know exactly what contribution each asset makes to the physical and financial wellbeing of the organization as a whole, so it is essential that they are involved in the RCM process from the outset.

3.2 Functional Failures

The objectives of maintenance are defined by the functions and associated performance expectations of the asset. But how does maintenance achieve these objectives? The only occurrence that is likely to stop any asset performing to a standard required by its users is some kind of failure. However, before we can apply a suitable blend of failure management tools, we need to identify what failures can occur. The RCM process does this at two levels:

• By identifying what circumstances amount to a failed state
• Then by asking what events can cause the asset to get into a failed state.
In the world of RCM, failed states are known as functional failures because they occur when an asset is unable to fulfill a function to a standard of performance which is acceptable to the user. In addition to the total inability to function, this definition encompasses partial failures, where the asset still functions but at an unacceptable level of performance (including situations where the asset cannot sustain acceptable levels of quality or accuracy).

3.3 Failure Modes

Once each functional failure has been identified, the next step is to try to identify all the events, which are reasonably likely to cause each failed state. These events are known as failure modes. ‘Reasonably likely’ failure modes include those that have occurred on the same or similar equipment operating in the same context, failures, which are currently being prevented by existing maintenance regimes, and failures that have not happened yet but that are considered to be real possibilities in the context in question. Most traditional lists of failure modes incorporate failures by deterioration or normal wear and tear.

However, the list should include failures caused by human errors (by operators or maintainers) and design flaws so that all reasonably likely causes of equipment failure can be identified and dealt with appropriately. It is also important to identify the cause of each failure in enough detail to make it possible to identify a suitable failure management policy.

3.4 Failure Effects
The fourth step in the RCM process entails listing failure effects, which describe what physically happens when each failure mode occurs. These descriptions should include all the information needed to support the evaluation of the consequences of failure, such as:
• What evidence (if any) that the failure has occurred?
• In what ways (if any) it poses a threat to safety or the environment?
• In what ways (if any) it affects production or operations?
• What physical damage (if any) is caused by the failure?
• What must be done to repair the failure?

3.5 Failure Consequences
A detailed analysis of an average industrial undertaking is likely to yield between three and ten thousand possible failure modes. As mentioned in the introduction of this paper, each of these failures affects the organization in some way, but in each case, the consequences are different. The RCM process classifies these consequences into four groups, as follows:
• Hidden failure consequences: Hidden failures have no direct impact, but they expose the organization to multiple failures with serious, often catastrophic, consequences.
• Safety and environmental consequences: A failure has safety consequences if it could hurt or kill someone. It has environmental consequences if it could lead to a breach of any corporate, regional, national or international environmental standard.
• Operational consequences: A failure has operational consequences if it affects production (output, product quality, customer service or operating costs in addition to direct cost of repair)
• Non-operational consequences: Evident failures that fall into this category affect neither safety or production, so they involve only the direct cost of repair.
The RCM process uses these categories as the basis of a strategic framework for maintenance decisionmaking.
By forcing a structured review of the consequences of each failure mode in terms of these categories, it focuses attention on the maintenance activities which have the most effect on the performance of the organization, and diverts energy away from those that have little or no effect (or which may even be actively counterproductive). It also encourages users to think more broadly about different ways of managing failure, rather than to concentrate only on failure prevention.

3.6 Failure Management Policy Selection
Failure management policies are divided into two categories:
• Proactive tasks: these tasks undertaken before a failure occurs, in order to prevent the item from getting into a failed state. As discussed below, RCM further subdivides these tasks into scheduled restoration, scheduled discard and on-condition maintenance
• Default actions: these deal with the failed state, and are chosen when it is not possible to identify an effective proactive task. Default actions include failure-finding, redesign and run-to-failure. Scheduled restoration and scheduled discard tasks
Scheduled restoration entails remanufacturing a component or overhauling an assembly at or before a specified age limit, regardless of its condition at the time. Similarly, scheduled discard entails discarding an item at or before a specified life limit, regardless of its condition at the time. Collectively, these two types of tasks are now generally known as preventive maintenance.

On-condition tasks
On-condition techniques rely on the fact that most failures give some warning of the fact that they are about to occur. These warnings are known as potential failures, and are defined as identifiable physical conditions, which indicate that a functional failure is about to occur or is in the process of occurring.
On-condition tasks are used to detect potential failures so that action can be taken to reduce or eliminate the consequences that could occur if they were to degenerate into functional failures. This category of tasks includes all forms of predictive maintenance, condition-based maintenance and condition monitoring.
Failure-finding
Failure-finding entails checking hidden functions to find out if they have failed (as opposed to the on condition tasks described above, which entail checking if something is failing).

Redesign
Redesign entails making any one-time change to the built-in capability of a system. This includes changes to hardware, one-time changes to procedures and if necessary, training.

No scheduled maintenance
This default entails making no effort to anticipate or prevent failure modes to which it is applied, and so those failures are simply allowed to occur and then repaired. This default is also called run-to-failure.

3.7 The RCM Task Selection Process
The RCM process applies a highly structured consequence evaluation and policy selection algorithm to each failure mode. It incorporates precise and easily understood criteria for deciding which (if any) of the proactive tasks is technically feasible in any context, and if so for deciding how often and by whom the tasks should be done. It also incorporates criteria for deciding whether any task is worth doing, a decision, which is governed by how well, the candidate task deals with the consequences of the failure. Finally, if a proactive task cannot be found that is both technically feasible and worth doing, the algorithm leads users to the most suitable default action for dealing with the failure.
This approach means that proactive tasks are only specified for failures that really need them, which in turn leads to substantial reductions in routine workloads. In fact, if RCM is correctly applied to existing maintenance programs, it reduces the amount of routine work (in other words, tasks to be undertaken on cyclic basis) issued in each period, usually by 40% to 70%. On the other hand, if RCM is used to develop a new maintenance program, the resulting scheduled workload is much lower than if the program is developed by traditional methods. Less routine work also means that the remaining tasks are more likely to be done properly. This together with the elimination of counterproductive tasks leads to more effective maintenance.

CASE STUDY 1
A brewery neglected to perform routine maintenance on its compressed air system for years. As a result, two of its centrifugal compressors, whose impellers had been rubbing against their shrouds, were unable to deliver the volume of air they were rated for and one of those units had burned up several motors during its lifetime. In addition, plant personnel did not inspect the system’s condensate traps regularly. These traps were of a type that clogged easily, which prevented the removal of moisture and affected product quality. Also, the condensate drains were set to operate under the highest humidity conditions, so they would actuate frequently, which increased the system’s air demand. As a result, energy use was excessively high, equipment repair and replacement costs were incurred unnecessarily, and product quality suffered. All of this could have been avoided through regular maintenance.
Like all electro-mechanical equipment, industrial compressed air systems require periodic maintenance to operate at peak efficiency and minimize unscheduled downtime. Inadequate maintenance can increase energy consumption via lower compression efficiency, air leakage, or pressure variability. It also can lead to high operating temperatures, poor moisture control, excessive contamination, and unsafe working environments. Most issues are minor and can be corrected with simple adjustments, cleaning, part replacement, or elimination of adverse conditions. Compressed air system maintenance is similar to that performed on cars; filters and fluids are replaced, cooling water is inspected, belts are adjusted, and leaks are identified and repaired.
A good example of excess costs from inadequate maintenance can be seen with pipeline filter elements. Dirty filters increase pressure drop, which decreases the efficiency of a compressor. For example, a compressed air system that is served by a 100-horsepower (hp) compressor operating continuously at a cost of $0.08/kilowatt-hour (kWh) has annual energy costs of $63,232. With a dirty coalescing filter (not changed at regular intervals), the pressure drop across the filter could increase to as much as 6 pounds per square inch (psi), vs. 2 psi when clean, resulting in a need for increased system pressure. The pressure drop of 4 psi above the normal drop of 2 psi accounts for 2% of the system’s annual compressed air energy costs, or $1,265 per year. A pressure differential gauge is recommended to monitor the condition of compressor inlet filters. A rule of thumb is that a pressure drop of 2 psi will reduce the capacity by 1%.