Category Archives: Reliability Training

Author: Scott Gloyna

For any given asset there are typically dozens of different predictive or preventive maintenance tasks that could be performed, however selecting the right maintenance tasks that contribute effectively to your overall strategy can be tricky, The benefit is the difference between meeting production targets and the alternative of lost revenue, late night callouts, and added stress from unplanned downtime events. Construction Worker Pointing With Finger. Ready For Sample Text

Step 1: Build out your FMEA (Failure Mode Effects Analysis) for the asset under consideration. 

Make sure you get down to appropriate failure modes in enough detail so that the causes are understood and you can identify the proper maintenance to address each specific failure mode.

Once you’ve made a list of failure modes, then it’s detailed analysis time. If you want to be truly rigorous, perform the following analysis for every potential failure mode. Depending on the criticality of the asset you can simplify by paring down your list to include only the failure modes that are most frequent or result in significant downtime.

Step 2: Identify the consequences of each failure mode on your list.

Failure modes can result in multiple types of negative impact. Typically, these failure effects include production costs, safety risks, and environmental impacts. It is your job to identify the effects of each failure mode and quantify them in a manner that allows them to be reviewed against your business’s goals. Often when I am facilitating a maintenance optimization study people will say things like “There is no effect when that piece of equipment fails.” If that’s the case, why is that equipment there? All failures have effects, they may just be small or hard to quantify, perhaps because of available workarounds or maybe there is a certain amount of time after the failure before an effect is realized.

Step 3: Understand the failure rate for each particular mode.

Gather information on the failure rates from any available industry data and personnel with experience on the asset or a similar asset and installation, as well as any records of past failure events at your facility. This data can be used to evaluate the frequency of failure through a variety of methods — ranging from a simple Mean Time To Failure (MTTF) to a more in-depth review utilizing Weibull distributions.

(Note: The Weibull module of Isograph’s Availability Workbench™ can help you to quickly and easily understand the likelihood of different failure modes occurring.)

Step 4: Make a list of possible reactive, planned or inspection tasks to address each failure mode.

Usually, you start by listing the actions you take when that failure mode occurs (reactive maintenance). Then broaden your list to any potential preventive maintenance and/or inspection tasks that could help prevent the failure mode from happening, or reduce the frequency at which it occurs.

  • Reactive tasks
    • Replacement
    • Repair
  • Preventive tasks
    • Daily routines (clean, adjust, lubricate)
    • Periodic overhauls, refurbishments, etc.
    • Planned replacement
  • Inspection tasks
    • Manual (sight, sound, touch)
    • Condition monitoring (vibration, thermography, ultrasonics, x-ray and gamma ray)

Step 5: Gather details about each potential task.

In order to compare and contrast different tasks, you have to understand the requirements of each:

  • What exactly does the task entail? (basic description)
  • How long would the work take?
  • How long would it take to start the work after shutdown/failure?
  • Who would do the work?
  • What labor costs are involved? (the hourly rates of the employees or outside contractors who would perform the task)
  • Would any spare parts be required? If so, how much would they cost?
  • Would you need to rent any specialized equipment? If so, how much would it cost?
  • Do you have to take the equipment offline? If so, for how long?
  • How often would you need to perform this task (frequency)?

A key consideration for inspection tasks only: What is the P-F interval for this failure mode? This is the window between the time you can detect a potential failure (P) and when it actually fails (F) — similar to calculating how long you can drive your car after the fuel light comes on, before you actually run out of fuel Understanding the P-F interval is key in determining the interval for each inspection task.

The P-F interval can vary from hours to years and is specific to the type of inspection, the specific failure mode and even the operating context of the machinery.

It can be hard to determine the P-F interval precisely but it is very important to ensure that the best approximation is made because of the impact it has on task selection and frequency.

Step 6: Evaluate the lifetime costs of different maintenance approaches.

Once you understand the cost and frequency of different failure modes, as well as the cost and frequency of various maintenance tasks to address them, you can model the overall lifetime costs of various options.

For example, say you have a failure mode with a moderate business impact — enough to affect production, but not nosedive your profits for the quarter. If that failure mode has a mean time between failures (MTBF) of six months, you might take a very aggressive maintenance approach. On the other hand, if that failure mode only happens once every ten years, your approach would be very different. “Run to Failure” is often a completely legitimate choice, but you need to understand and be able to justify that choice.

These calculations can be done manually, in spreadsheets or using specialized modeling software such as the RCMCost™ module of Isographs Availability Workbench™.

Ultimately you try to choose the least expensive maintenance task that provides the best overall business outcome.

 Ready to learn more? Gain the skills needed to develop optimized maintenance strategies through our training course: Introduction to Maintenance Strategy Development

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Author: Dan DeGrendel

Regardless of industry or discipline, we can probably all agree that routine maintenance — sometimes referred to as preventative, predictive, or even scheduled maintenance — is a good thing. Unfortunately, through the years I’ve found that most companies don’t have the robust strategies they need.

Typical issues and the kinds of trouble they can create:

service engineer worker at industrial compressor refrigeration s1. Lack of structure and schedule

In many cases, routine tasks are just entries on a to-do list of work that needs to be performed — with nothing within the work pack to drive compliance. In particular, a list of tasks beginning with “Check” which have no guidance of an acceptable limit can have limited value. The result can be a “tick and flick” style routine maintenance program that fails to identify impending failure warning conditions.

2. Similar assets, similar duty, different strategies

Oftentimes, maintenance views each piece of equipment as a standalone object, with its own unique maintenance strategy. As a result, one organization could have dozens of maintenance strategies to manage, eating up time and resources. In extreme cases, this can lead to similar assets having completely different recorded failure mechanisms and routine tasks, worded differently, grouped differently and structured differently within the CMMS.

3. Operational focus 

Operations might be reluctant to take equipment out of service for maintenance, so they delay or even cancel the appropriate scheduled maintenance. At times this decision is driven by the thought that the repair activity is the same in a planned or reactive manner. But experience tells us that without maintenance, the risk is even longer downtime and more expensive repairs when something fails.

4. Reactive routines

Sometimes, when an organization has been burned in the past by a preventable failure, they overcompensate by performing maintenance tasks more often than necessary. The problem is, the team might be wasting time doing unnecessary work — worse still it might even increase the likelihood of future problems, simply because unnecessary intrusive maintenance can increase the risk of failure.

5. Over-reliance on past experience 

There’s no substitute for direct experience and expertise. But when tasks and frequencies are too solely based on opinions and “what we’ve always done” — rather than sound assumptions — maintenance teams can run into trouble through either over or under maintaining. Without documented assumptions, business decisions are based on little more than a hunch. “Doing what we’ve always done” might not be the right approach for the current equipment, with the current duty, in the current business environment (and it certainly makes future review difficult).

6. Failure to address infrequent but high consequence failures 

Naturally, routine tasks account for the most common failure modes. They should however also address failures that happen less frequently, but may have a significant impact on the business. Developing a maintenance plan which addresses both types, prevents unnecessary risk. For example, a bearing may be set up on a lubrication schedule, but if there’s no plan to detect performance degradations due to a lubrication deficiency, misalignment, material defect, etc then undetected high consequence failures can occur.

7. Inadequate task instructions

Developing maintenance guidelines and best practices takes time and effort. Yet, all too often, the maintenance organization fails to capture all that hard-won knowledge by creating clear, detailed instructions. Instead, they fall back on the maintenance person’s knowledge — only to lose it when a person leaves the team. Over time, incomplete instructions can lead to poorly executed, “bandaid-style” tasks that get worse as the months go by.

8. Assuming new equipment will operate without failure for a period of time

There’s a unique situation that often occurs when new equipment is brought online. Maintenance teams assume they have to operate the new equipment first to see how it fails before they can identify and create the appropriate maintenance tasks. It’s easy to overlook the fact that they likely have similar equipment with similar points of failure. Their data from related equipment provides a basic foundation for constructing effective routine maintenance.

9. Missing opportunity to improve

If completed tasks aren’t reviewed regularly to gather feedback on instructions, tools needed, spare parts needed, and frequency; the maintenance process never gets better. The quality or effectiveness of the tasks then degrade over time and, with it, so does the equipment.

10. Doing what we can and not what we should 

Too often, maintenance teams decide which tasks to perform based on their present skill sets — rather than equipment requirements. Technical competency gaps can be addressed with a training plan and/or new hires, as necessary, but the tasks should be driven by what the equipment needs.

Without a robust routine maintenance plan, you’re nearly always in reactive mode — conducting ad-hoc maintenance that takes more time, uses more resources, and could incur more downtime than simply taking care of things more proactively. What’s worse, it’s a vicious cycle. The more time maintenance personnel spend fighting fires, the more their morale, productivity, and budget erodes. The less effective routine work that is performed, the more equipment uptime and business profitability suffer.  At a certain point, it takes a herculean effort simply to regain stability and prevent further performance declines.

Here’s the good news: An optimized maintenance strategy, constructed with the right structure is simpler and easier to sustain. By fine-tuning your approach, you make sure your team is executing the right number and type of maintenance tasks, at the right intervals, in the right way, using an appropriate amount of resources and spare parts. And with a framework for continuous improvement, you can ultimately drive towards higher reliability, availability and more efficient use of your production equipment.

Want to learn more? Check out our next blog in this series, Plans Can Always Be Improved:  Top 5 Reasons to Optimize Your Maintenance Strategy.

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Author: Dan DeGrendel

Maintenance optimization doesn’t have to be time-consuming or difficult. Really it doesn’t. Yet many organizations simply can’t get their maintenance teams out of a reactive “firefighting mode” so they can focus on improving their overall maintenance strategy. Development And Growth

Stepping back to evaluate and optimize does take time and resources, which is why some organizations struggle to justify the project. They lack the data and/or the framework to demonstrate the real, concrete business value that can be gained.

And even when organizations do start to work on optimization, sometimes their efforts stall when priorities shift, results are not immediate and the overall objectives fade from sight.

If any of these challenges sound familiar, there are some very convincing reasons to forge ahead with maintenance optimization:

1. You can make sure every maintenance task adds value to the business

Through the optimization process, you can eliminate redundant and unnecessary maintenance activities, and make sure your team is focused on what’s really important. You’ll outline the proper maintenance tasks, schedules and personnel assignments; then incorporate everything into the overall equipment utilization schedule and departmental plans to help drive compliance. Over time, an optimized maintenance strategy will save time and resources — including reducing the hidden costs of insufficient maintenance (production downtime, scrap product, risks to personnel or equipment and expediting and warehousing of spare parts, etc.).

2. You’ll be able to plan better

Through the optimization process, you’ll be allocating resources to various tasks and scheduling them throughout the year. This gives you the ability to forecast resource needs, by trade, along with spare parts and outside services. It also helps you create plans for training and personnel development based on concrete needs.

3. You’ll have a solid framework for a realistic maintenance budget

The plans you establish through the optimization process give you a real-world outline of what’s needed in your maintenance department, why it’s needed, and how it will impact your organization. You can use this framework to establish a realistic budget with strong supporting rationales to help you get it approved. Any challenges to the budget can be assessed and a response prepared to indicate the impact on performance that any changes might make.

4. You’ll just keep improving

Optimization is a project that turns into an ongoing cycle of performing tasks, collecting feedback and data, reviewing performance, and tweaking maintenance strategies based on current performance and business drivers.

5. You’ll help the whole business be more productive and profitable

Better maintenance strategies keep your production equipment aligned to performance requirements, with fewer interruptions. That means people can get more done, more of the time. That’s the whole point, isn’t it?

Hopefully, this article has convinced you of the benefits of optimizing your maintenance strategies. Ready to get started or re-energize your maintenance optimization project? Check out our next blog article, How To Optimize Your Maintenance Strategy: A 1,000-Foot View.

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Author: Dan DeGrendel

Optimizing your maintenance strategy doesn’t have to be a huge undertaking. The key is to follow core steps and best practices using a structured approach. If you’re struggling to improve your maintenance strategy — or just want to make sure you’ve checked all the boxes — here’s a 1000-foot view of the process.

1. Sync up

  • Identify key stakeholders from maintenance, engineering, production, and operations — plus the actual hands-on members of your optimization team.
  • Get everybody on board with the process and trained in the steps you’re planning to take.  A mix of short awareness sessions and detailed educations sessions to the right people are vital for success.
  • Make sure you fully understand how your optimized maintenance strategies will be loaded and executed from your Computer Maintenance Management System (CMMS)

2. Organize

  • Review/revise the site’s asset hierarchy for accuracy and completeness. Standardize the structure if possible.
  • Gather all relevant information for each piece of equipment.
    • Empirical data sources: CMMS, FMEA (Failure Mode and Effects Analysis) studies, industry standards, OEM recommended maintenance
    • Qualitative data sources: Team knowledge and past records

3. Prioritize

  • Assign a criticality level for each piece of equipment; align this to any existing risk management framework
  • Consider performing a Pareto analysis to identify equipment causing the most production downtime, highest maintenance costs, etc.
  • Determine the level of analysis to perform on each resulting criticality level

4. Strategize

  • Using the information you’ve gathered, define the failure modes, or apply an existing library template. Determine existing and potential modes for each piece of equipment
  • Assign tasks to mitigate the failure modes.
  • Assign resources to each task (e.g, the time, number of mechanics, tools, spare parts needed, etc.)
  • Compare various options to determine the most cost-effective strategy
  • Bundle selected activities to develop an ideal maintenance task schedule (considering shutdown opportunities). Use standard grouping rules if available.

This is your proposed new maintenance strategy.

5. Re-sync

  • Review the proposed maintenance strategy with the stakeholders you identified above, then get their buy-in and/or feedback (and adjust as needed)

6. Go!

  • Implement the approved maintenance strategy by loading all of the associated tasks into your CMMS — ideally through direct integration with your RCM simulation software, manually, or via Excel sheet loader.

7. Keep getting better

  • Continue to collect information from work orders and other empirical and qualitative data sources.
  • Periodically review maintenance tasks so you can make continual improvements.
  • Monitor equipment maintenance activity for unanticipated defects, new equipment and changing plant conditions. Update your maintenance strategy accordingly.
  • Build a library of maintenance strategies for your equipment.
  • Take what you’ve learned and the strategies and best practices you’ve developed and share them across the entire organization, wherever they are relevant.

Of course, this list provides only a very high-level view of the optimization process.

If you’re looking for support in optimizing your maintenance strategies, or want to understand how to drive ongoing optimization, ARMS Reliability is here to help.

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Author: Philip Sage, CMRP, CRL

Traditionally, SAP is populated with Master Data with no real consideration of future reliability improvement. Only once that maintenance is actually being executed does the real pressure of any under performing assets drive the consideration of the reliability strategy. At that point the mechanics of what’s required for ongoing reliability improvement, based upon the SAP Master Data structure, is exposed and, quite typically, almost unviable. ???????????????????????????????????????????????????????????????????????????

The EAM system is meant to support reliability. Getting your EAM system to support reliability requires some firm understanding of what must happen. If we look a little closer at reliability and the phases of life of an asset, we can see why the EAM settings must vary and not be fixed.

The initial reliability performance of any system is actually determined by its design and component selection.

This is probably not a big surprise for anyone close to reliability, but it may spark some debate from those who have not heard this before.

As evidence to support this statement, a newly commissioned and debugged system should operate nearly failure free for an initial period of time and only become affected by chance failures on some components. An even closer inspection can show that during this period, we can expect that most wear out failures would be absent after a new machine or system is placed into service. During this “honeymoon period” preventative replacement is actually not necessary nor would an inspection strategy provide benefit until such time as wear (or unpredictable wear) raises the possibility of a failure. Within this honeymoon period the components of the system behave exponentially and fail due to their individual chance failures only. They should only be replaced if they actually fail and not because of some schedule. Minor lubrication or service might be required, but during this initial period, the system is predominantly maintenance free and largely free from failure.

Here is where the first hurdle occurs.

After the initial period of service has passed, then it is reasonable to expect both predictable and unpredictable forms of wear out failures to gradually occur and increase in rate, as more components reach their first wear out time.

Now if repair maintenance (fixing failures) is the only strategy practiced, then the system failure rate would be driven by the sporadic arrivals of the component wear out failures, which will predictably rise rather drastically, then fluctuate wildly resulting in “good” days followed by “bad” days. The system failure rate driven by component wear out failures, would finally settle to a comparatively high random failure rate, predominantly caused by the wear out of components then occurring in an asynchronous manner.

With a practice heavily dependent upon repair maintenance, the strength of the storeroom becomes critical, as it makes or breaks the system availability which can only be maintained by fast and efficient firefighting repairs. The speed at which corrective repairs can be actioned and the logistical delays encountered, drive the system availability performance.

From this environment, “maintenance heroes” are born.

As the initial honeymoon period passes, the overall reliability the system becomes a function of the maintenance policy, i.e. the overhaul, parts replacement, and inspection schedules.

The primary role of the EAM is to manage these schedules.

The reduction or elimination of predictable failures is meant to be managed through preventative maintenance tasks, housed inside the EAM that counter wear out failures. Scheduled inspections help to counter the unpredictable failure patterns of other components.

If the EAM is properly configured for reliability, there is a tremendous difference in the reliability of a system. The system reliability becomes a function of whether or not preventative maintenance is practiced or “only run to failure then repair” maintenance is practiced. As a hint: the industry wide belief is that some form of preventative practice is better than none at all.

Preventative maintenance is defined as the practice that prevents the wear failure by preemptively replacing, discarding or performing an overhaul to “prevent” failure.  For long life systems the concept revolves around making a minimal repair that is made by replacement of the failed component, and resulting in the system then restored to service in “like new” condition. Repair maintenance was defined as a strategy that waits until the component in the system fails during the system’s operation.

If the EAM is not programmed correctly or if the preventative tasks are not actioned, then the reliability of a system can fall to ridiculously low levels, where random failures of components of the recoverable system, plague the performance and start the death spiral into full reactive maintenance.

This is quite costly, as in order to be marginally effective the additional requirement is a fully stocked storeroom, which raises the inventory carry costs. Without a well-stocked storeroom, there are additional logistical delays associated with each component, that are additive in their impact on the system availability, and the system uptime, and so system availability becomes a function of spare parts.

An ounce of prevention goes a long way.

Perhaps everything should be put on a PM schedule…? This is actually the old school approach, and I find it still exists in practice all over the world.

The reliability of a system is an unknown hazard and is affected by the relative timing of the preventative task. This timing comes from the EAM in the form of a work order which is supposed to be generated relative to the wear out of the component. How well this task aligns with reality is quite important. If the preventative work order produced by the EAM system comes out at the wrong time, there is a direct adverse effect on system reliability.

EAM systems are particularly good at forecasting the due date of the next work order and creating a work order to combat a component wear out failure. However, wear is not always easily predicted by the EAM and so we see in practice, that not all EAM generated work orders suppress the wear out failures. One reason for this variance is the EAM system work order was produced based on the system calendar time base along with a programmed periodicity that was established in the past to predict the future wear performance.

We don’t always get this right.

As a result we generate work orders for work that is not required, or work that should have been performed before the component failed, not just after the component failed.

Maybe this sounds familiar?

Calendar based forecasts assume wear is constant with time. It is not.

A metric based in operating hours is often a more complete and precise predictor of a future failure. It’s true most EAM systems today allow predictable work to be actioned and released by either calendar time or operating hours and allow other types of time indexed counters to trigger PM work orders.

A key to success is producing the work order just ahead of the period of increased risk to failure due to wear. Whether by calendar or some other counter we call the anticipation of failure, and the work order to combat it, the traditional view of maintenance.

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This all sounds simple enough.

The basic job of a reliability engineer is to figure out when something will likely fail based on its past performance and schedule a repair or part change. The EAM functionality is used to produce a work order ahead of the failure, and if that work is performed on-time, we should then operate the system with high reliability.

The reliability side of this conjecture, when combined with an EAM to support, is problematic.

If the work order is either ill-timed from the EAM or not performed on time during the maintenance work execution, there is an increased finite probability that the preventative task will not succeed in its purpose to prevent a failure. Equally devastating, if the PM schedule is poorly aligned or poorly actioned, the general result mirrors the performance expected from a repair maintenance policy, and the system can decay into a ridiculously low level of reliability, with near constant sporadic wear out of one of the many components within the system.

When preventative maintenance is properly practiced so that it embraces all components known to be subject to wear out, a repairable system can operate at high reliability and availability with a very low “pure chance” failure rate and do so for indefinitely long periods of time.

Determining what to put into the EAM is really where the game begins.

FIND OUT MORE AT:

MASTERING ENTERPRISE ASSET MANAGEMENT WITH SAP, 23-26 October 0216, Crown Promenade, Melbourne

Phil Sage will be running a full day workshop “Using SAP with Centralised Planning to Continually Improve RCM Derived Maintenance Strategies” Wednesday 26 October

Come learn what works, and what does not work, as you integrate SAP EAM to support your reliability and excellence initiatives, which are needed to be best in class in asset management. The workshop covers how and where these tools fit into an integrated SAP framework, what is required to make the process work, and the key links between reliability excellence, failure management and work execution using SAP PM.

By: Gary Tyne CMRP, CRL

Engineering Manager – ARMS Reliability Europe

Working for a global organization has taken me to some weird and wonderful places around the world. Different cultures, traditions, religions and people certainly enlightens you to the wonderful and colorful place we all call home.

I would say in most of these countries I have at some stage taken a taxi or at least been chauffeured by a driver in a customer’s company vehicle. These experiences have led to some interesting conversations on life, travel, politics, and football with some very knowledgeable and diverse taxi drivers. On the other hand, I have had drivers that have not spoken a word and have just delivered me to my destination in silence, even after trying to engage in conversation, their chosen dialogue is nil speak. bigstock--131191391

A recent taxi encounter occurred when I had just left my customer and was going to call for a taxi, when I spotted someone being dropped off at my current location. I asked the driver if he could take me to Dublin airport and he obliged.

This is when I met Mohammed, an immigrant from Kenya who had moved to Ireland 17 years ago. He was smiling and cheerful and had a generally happy persona about him. We discussed weather in Ireland versus Mombasa, we mentioned football briefly, and then we started to discuss cars. This occurred when a brand new Mercedes went past us in the fast lane and I passed comment on what a beautiful car that was.

Mohammed started to discuss the Toyota Corolla in which we were driving and how he loved his car for its level of reliability. I asked how many miles his vehicle had driven and he pointed out that he had covered over 300,000 miles since he purchased the car brand new in Northern Ireland. He went onto explain how he ensured that it was regularly maintained to a high standard with the best quality oil and original OEM parts being used when any replacements were required. The engine and gearbox were original and providing ‘you look after your car, it will look after you.’ Mohammed was proud of the length of service he had achieved from his vehicle and that the car had never let him down. However, as the vehicle operator he recognized the importance of regular maintenance and the use of the right quality parts. He also said that he only allowed one mechanic to work on his vehicle because he was very skilled and competent at his job and could not trust others to do work on his taxi.

Mohammed was also proud to be a taxi driver in Ireland and combined with his ‘Reliability’ story certainly made the trip to Dublin airport a memorable one. Mohammed did not know my job role and that I had spent over 30 years in Maintenance and Reliability, but he gave me a text book account of what is ‘Reliability’! I said goodbye to Mohammed after he let me take a picture of his mileage and car. I wished him luck and many more years of happy motoring in his reliable Toyota motor vehicle.

Sitting in the departure lounge my trip to the airport and conversation with Mohammed certainly made me think: mileage

  • Do we see this level of passion and ownership amongst today’s industrial operators?
  • Should Operators take more care for their assets, ensuring high reliability through a program of basic care?
  • How do we ensure the right levels of competence in our technicians?
  • How do we ensure that the correct specification and quality of parts are being purchased?
  • How do we ensure that maintenance is being performed at the right frequency on the right asset?

This ‘Reliability Tale from the Taxi’ may have also generated further questions in your own mind, for me, it provided me with  another great ‘Reliability’ story that I can share during one of our global reliability training courses.

 

As its name suggests, an “asset” is a useful or valuable thing. Indeed, the antonym of “asset” is “liability”. Hence, an organization’s assets should deliver value; not cost money. With the right techniques and strategies in place, asset managers can ensure that their plant and equipment is performing at and being maintained at optimum levels. These many and varied techniques can be applied across the different phases of an asset’s life to ensure that,  instead of draining money from the bottom line, it actively contributes to margin increases. F

Managed the right way, assets can contribute significantly to profit margins. It takes a strategic approach to maintenance and asset management, in key areas such as:

  1. Increasing availability and plant capacity
  2. Reducing unnecessary maintenance costs
  3. Reducing unnecessary spares holding costs
  4. Planning optimum retirement of plant and equipment

Once you determine a key focus area, it’s important to apply the right technique.

Margin Increase Techniques

System Analysis

The primary objective of System Analysis is to identify and eliminate bottlenecks in a system, and is particularly useful in complex operations where the contribution of different parts of the system are not clear. An analyst performing System Analysis builds a representative model using reliability block diagrams, and runs a simulation to produce a quantitative view of the contribution of all parts of a system. The technique is used to assess the reliability of individual components and their dependencies on other events or assets in order to assess the overall availability of the system. This helps to determine the importance of each element, so that the analyst can play “what if” with different levels of redundancy, size of buffers, maintenance strategies, and spares holding levels, in order to find the optimum.

Maintenance Benefit Analysis

Unfortunately, there has been a long tradition of organizations fostering a culture of maintenance in which the maintenance crews are lauded as heroes when they step in to fix things that are broken. In such cultures, preventative maintenance is less appreciated, despite it being proven to save money. Maintenance Benefit Analysis – similar to Maintenance Optimization– is used to evaluate a maintenance plan and identify any areas where maintenance is either not needed or is not optimal. A Maintenance Benefit Analysis is used to identify where alternatives to current practice can be improved by choosing a different type of strategy or frequency.

Spares Optimization

Typically, maintenance crews love spares and want lots of them in their plant or facility. Yet plant managers resent having too many spares in stock as they tie up capital and take up storage space. Spares Optimization is all about finding the optimum level of spares to hold; a level that balances the cost of not having spares available against the cost of holding the spares in stock.

Repair vs Replace Analysis

Knowing when to replace a piece of equipment shouldn’t be guesswork, as the right time to replace can save hundreds of thousands of dollars in repairs. Repair vs Replace Analysis is used to predict or track the costs of repairs against the cost of replacement. As the cost of repairs increases (which incorporates costs like labor and parts), it becomes less viable to maintain the asset. Plus, as the cost of new equipment falls, it becomes more viable to buy it new. Life Cycle Cost analysis can be applied to assess the optimum point to switch from repair-mode to replace-mode.

ARMS Reliability can show you how to achieve great cost savings and margin increases across the whole organization by using these techniques and their associated software tools; and will train your team to implement and manage these changes proactively.

In most cases, there is much to gain by working through maintenance strategy optimization. To identify where your company’s maintenance strategy sits on the spectrum, you can perform a simple self-assessment that looks for the most common symptoms, which are described in detail in our guide “5 Symptoms Your Maintenance Strategy Needs Optimizing.” If the symptoms are evident, then there is a strong business case to invest in maintenance strategy optimization. The primary question in diagnosing the health of your maintenance strategy is a simple one. Does your maintenance strategy need optimizing? Ideally, your maintenance strategy is already optimized. Perhaps it was, but is in need of a tune-up. Or, as is the case in many companies, maybe you are experiencing endemic symptoms that lead to: M

  • Recurring problems with equipment.
  • Budget blow-outs from costly fixes to broken equipment.
  • Unplanned downtime that has a flow-on effect on production.
  • Using equipment that is not performing at 100 percent.
  • Risk of safety and environmental incidents.
  • Risk of catastrophic failure and major events.

To identify where your company’s maintenance strategy sits on the spectrum, you can perform a simple self-assessment that looks for the most common symptoms.

  1. Increase in unplanned maintenance – A sure sign that your maintenance strategy is not working is the simple fact that you are performing more unplanned maintenance, which is caused by an increase in the occurrence of breakdowns.
  2.  Rising maintenance costs – In companies that apply best practice maintenance strategy optimization, total maintenance costs are flat or slightly decreasing month-on-month. These optimized strategies combine preventative tasks with various inspection and root cause elimination tasks which in turn produces the lowest cost solution.
  3. Excessive variation in output – A simple definition of the reliability of any process is that it does the same thing every day. In other words, equipment should run at nameplate capacity day in and day out. When it doesn’t, this is an indication that some portion of the maintenance strategy is misaligned and not fully effective.
  4. Strategy sticks to OEM recommendation -Sticking to the maintenance schedule prescribed by Original Equipment Manufacturers (OEMs) may seem like a good starting point for new equipment. But it’s only that a starting point. There are many reasons why you should create your own optimized maintenance strategy soon after implementation.
  5. An inconsistent approach – Consistency implies lack of deviation. And this implies standardisation. When it comes to maintenance strategies, standardization is essential.

For an in depth look at these symptoms download the complete guide “5 Symptoms Your Maintenance Strategy Needs Optimizing” 

Can you quantify the financial impact of your maintenance program on your business? Do you take into account not only the direct costs of maintaining equipment, such as labour and parts, but also the costs of not maintaining equipment effectively, such as unplanned downtime, equipment failures and production losses?

The total financial impact of maintenance can be difficult to measure, yet it is a very valuable task to undertake. It is the first step in finding ways to improve profit and loss. In other words, it is the first step towards an optimised maintenance strategy.

In a 2001 study of maintenance costs for six open pit mines in Chile [1], maintenance costs were found to average 44% of mining costs. It’s a significant figure, and it highlights the direct relationship between maintenance and the financial performance of mines. More recently, a 2013 Industry Mining Intelligence and Benchmarking study [2] reported that mining equipment productivity has decreased 18% since 2007; and it fell 5% in 2013 alone. Besides payload, operating time was a key factor.  

So how do you know if you are spending too much or too little on maintenance? Certainly, Industry Benchmarks provide a guide. In manufacturing best practice, benchmarks are less than 10% of the total manufacturing costs, or less than 3% of asset replacement value [3].

While these benchmarks may be useful, a more effective way to answer the question is to look at the symptoms of over- or under-spending in maintenance. After all, benchmarks cannot take into account your unique history and circumstance.

Symptoms of under-spending on maintenance include:

  • Rising ‘hidden failure costs’ due to lost production
  • Safety or environmental risks and events
  • Equipment damage
  • Reputation damage
  • Waiting time for spares
  • Higher spares logistics cost
  • Lower labour utilisation
  • Delays to product shipments
  • Stockpile depletion or stock outs

Other symptoms are explored in more detail in our guide: 5 Symptoms Your Maintenance Strategy Needs Optimizing.

Man in front of computer screen

Figure 1

In most cases, it is these ‘hidden failure costs’ that have the most impact on your bottom line. These costs can be many times higher than the direct cost of maintenance – causing significant and unanticipated business disruption. As such, it is very important to find ways to measure the effects of not spending enough on maintaining equipment.

Various tools and software exist to help simulate the scenarios that can play out when equipment is damaged, fails or, conversely, is proactively maintained. A Failure Modes Effects and Criticality Analysis (FMECA) is a proven methodology for evaluating all the likely failure modes for a piece of equipment, along with the consequences of those failure modes.

Extending the FMECA to Reliability Centred Maintenance (RCM) provides guidance on the optimum choice of maintenance task. Combining RCM with a simulation engine allows rapid feedback on the worth of maintenance and the financial impact of not performing maintenance.

Armed with the information gathered in these analyses, you will gain a clear picture of the optimum costs of maintenance for particular equipment – and can use the data to test different ways to reduce costs. It may be that there are redundant maintenance plans that can be removed; or a maintenance schedule that can become more efficient and effective; or opportunity costs associated with a particular turnaround frequency and duration. Perhaps it is more beneficial to replace equipment rather than continue to maintain it.

It’s all about optimising plant performance for peak production; while minimising the risk of failure for key pieces of equipment. Get it right, and overall business costs will fall.

Want to read on? Download our guide: 5 Symptoms Your Maintenance Strategy Needs Optimizing.

 

[1] Knights, P.F. and Oyanander, P (2005, Jun) “Best-in-class maintenance benchmarks in Chilean open pit mines”, The CIM Bulletin, p 93

[2] PwC (2013, Dec) “PwC’s Mining Intelligence and Benchmarking, Service Overview”, www.pwc.com.au

[3] http://www.maintenancebenchmarking.com/best_practice_maintenance.htm

Figure 1:  This image shows Isograph’s RCMCostTM software module which is part of their Availability WorkbenchTM. Availability Workbench, Reliability Workbench, FaultTree+, Hazop+ and NAP are registered trademarks of Isograph Software. ARMS Reliability are authorized distributors, trainers and implementors.

Author: Ben Rowland

A colleague and I were discussing how his nine year old son had completed his Cub Scouts Cyclist Activity badge. We noticed how some of the bike maintenance tasks that had been identified were, shall we say, less than ‘optimal’.

Now you might say this is a bit unfair to judge a Cub Scout lesson through the eyes of a reliability professional (and you’d be right) but what was interesting is that we often see the same sorts of issues within the industry.

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bike1

 

The first thing we noticed is the tasks aren’t really tasks, but a list of components; i.e. they tell you what to look at but not what to look for.

In other words, how a task is written is clearly very important.  In the example above “check the back tire” does not help us know what to look for. Is it there? Is it worn? Does it have air in it? Is it damaged? With vague work instructions like these maintainers are left to decide what to inspect for, which will inevitably lead to inconsistent maintenance.

Some of the examples above are better than others, “your helmet fits” for example, is more specific and much better than “check helmet.”

While working with clients to develop their maintenance plans, the RCM process we use ensures that each maintenance task addresses a specific failure mode, or modes. We can run a report that shows this link, which in turn allows the maintainer to understand the purpose of the inspection. The task can also be written in such a way as to focus the maintenance on identifying the potential failure.

Another issue with the tasks above is there isn’t any data or figures included in the task.  How much tire wear is acceptable? What is the minimum tread depth?  What pressure should the tire be at? Is there a minimum and maximum?

There also needs to be instruction as to how frequently to do the bicycle checks.  Every ride? Every month?  Things like checking your wheels are fitted tightly might need to be performed prior to every ride, but checking a chain for wear could be performed every few months. Not having this information can lead to items being under or over maintained, leading to possibly unsafe equipment condition or wasted effort.

“Okay then, you do it!”

Well it’s only fair after criticizing the Cub Scout’s effort that we have a go ourselves. So below is an example of how we might construct a FMEA and maintenance strategy for a bicycle, in the Availability Work Bench™ (AWB) RCM-Cost software¹:

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AWB

We can see that for the failure mode ‘chain worn’ we’ve identified an inspection task to periodically check the chain for wear to address that failure mode. We’ve specified the method to use (a wear gauge, as opposed to a simple visual check or performing a measurement) and an acceptable limit (less than 75% worn).  This is a clear communication of what is required, minimizing the chances of ineffective maintenance.

“How do I choose which task to perform?”

In the example above I touched on the point that there may be a choice of maintenance tasks that could be performed, as well as whether or not to perform any maintenance at all.  The RCM process also helps us to choose an appropriate maintenance task and it is essentially a balance between the severity of the failure vs. the cost or effort to perform the maintenance. Often severity is thought of in terms of cost e.g. lost production, but it also covers the impact on safety or operational impact. The operating context of the equipment also affects the severity. The example below shows how we use the AWB software to select an optimal maintenance task interval.

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Optimization Curve Image

Imagine we only ride our bike for getting around the town we live in for non-essential tasks, such as popping to the shops to buy some milk and a newspaper. In this case a punctured tire is not critical and we might decide not to carry a spare tube and tools to change it (pump, tire levers etc.) and instead to perform ‘breakdown maintenance’ i.e. walk the bike home and repair it there.  Now if we were instead on a vacation touring a remote location, far from any nearby towns, this ‘run to fail’ strategy would result in a very long walk and clearly not be suitable!

 Hidden Failures

So assuming we were carrying a spare tube, and relying on it in remote locations, what happens if there is a problem with the spare tube? “Did I remember to fix it after my last puncture?” What if there is a manufacturing defect?” Or “what if I didn’t find the thorn that caused the first puncture still stuck in the tire and got a second puncture?” These are called ‘hidden failures’ and require failure finding tasks in order to mitigate them.

 Operator Maintenance

We might also set our bicycle maintenance strategy assuming we do all the checks at home in the garage, but do we also need to consider operating checks?  For our bike this might include using our senses to listen for any abnormal noises, rattles, looseness, creaks or squeaks when riding the bike. We are also checking the operation of the gears and brakes through use, cleaning the bicycle down after use and oiling the chain afterwards to prevent corrosion. This is an example of ‘operator maintenance’.

How do we manage failures during use? If we notice something is wrong during use that we can’t fix, we would note it and arrange some planned maintenance at the bike shop before the warning becomes an actual failure that renders the bike out of action.  For operating failures that occur with little or no warning time we can address these in a number of ways; carrying spares (e.g. a spare inner tube), or tools to repair the failure out in the field (puncture repair kit).  We can also introduce re-designs (sealant in the tire to seal holes as they occur).

So there it is, writing an effective maintenance strategy can be as easy as riding a bike.

 

¹Availability Workbench™ is authored by Isograph Ltd. ARMS Reliability are authorized global distributors, re-sellers and implementers of the software application.