Tag Archives: Asset Management

This is a guest post written by Copperleaf.  ARMS Reliability is an authorised distributor of Copperleaf’s C55 Asset Investment Planning & Management solution. 

Author: Barry Quart – Copperleaf, VP of Marketing

Close up of hand of man playing chess holding queen. Business ma

In any discussion about asset management these days, the ISO 55000 standard is bound to come up. ISO published the standard in 2014 to provide guidance on best-in-class asset management practices and help organisations “realise the maximum value from their assets.”

In a nutshell, it’s about choosing the ‘right’ things to invest in—the projects that will deliver the highest value, and are most aligned with your company’s strategy.

It’s also about creating a plan—a roadmap for success—laying out what will be done, when, by whom and how it will be evaluated. The plan must address how to keep assets operating at their optimal level of performance, while managing risk, and respecting the available budgets and resources. Goal Wish

Sounds simple but this is no easy task, especially in organisations with tens of thousands, or even millions of diverse assets.

Asset Investment Planning & Management (AIPM) is an evolving discipline that helps organisations focus their available resources on doing the right things at the right time. AIPM can help you:

  • PREDICT the long-term needs of your asset base
  • OPTIMISE portfolios of investments to realize the greatest value from your assets
  • MANAGE your portfolios to achieve the highest execution performance

When these three principles of AIPM are put in place, organisations can start to make these complex investment decisions with confidence. AIPM

PREDICT:  Asset managers must focus on predicting the needs of their corporation’s assets, and on developing a realizable investment strategy to meet those needs.  The key word here is realisable. It’s not just about identifying the ideal thing to do for every asset, because you invariably won’t be able to afford to do every “ideal” thing you are asked to. You need to propose a strategy that you can afford, and have adequate resources to carry out. This is where the second part of the strategy comes in.

OPTIMISE:  If your investment requests exceed your available budget and/or resources, you need to develop a plan that delivers the most value for the money and resources you do have. When you can’t do it all, you need to consider deferring some investments and/or evaluate alternative ways to address the needs identified above. Value-based decision making can help you make the difficult trade-offs between risk, cost, and performance, and ensure that for your available funding and resources, you are always executing a plan that delivers the maximum value from your assets.

MANAGE:  Even the best plans never execute as expected. Emergent work, delays, and cost overruns all affect your organisation’s ability to deliver on the original set of objectives. Actual spend and accomplishments should be compared to the original plan, variances explored, and the plan re-optimised to ensure that looking forward, the organisation is always focused on those activities that deliver the highest value. This process of continuous planning is an integral part of a best-in-class asset investment strategy.

AIPM can help you make higher value investment decisions, and justify those decisions to stakeholders. Learn more about how AIPM supports the ISO 55000 standard.

This is a guest post written by Copperleaf.  ARMS Reliability is an authorized distributor of Copperleaf’s C55 Asset Investment Planning & Management solution. 

Author: Stefan Sadnicki

Modern urban wastewater treatment plant. Close-up view

Anglian Water is an innovative company whose mission is “to put water at the heart of a whole new way of living” and raise awareness about how essential water is to life, to the environment, and to a vibrant and growing economy. The company is the largest water and water recycling company in England and Wales—and Copperleaf’s first client in this sector!

We recently completed the implementation of Copperleaf C55 and it was one of the most challenging, yet rewarding projects any of us have ever worked on. I sat down to catch up with Chris Royce, our primary stakeholder and project champion, to get his thoughts on how everything went. As Head of Strategic Investment Management for Anglian Water, Chris was involved with the project from before it was a project! As the implementation draws to a close, I’d like to share some of the highlights:

What was the most challenging part of the project?

For Copperleaf, this was a new country (UK) and a new sector (water). We could see the potential of the C55 system and the benefits it would provide, and in reality many utility assets are very similar and the principles of risk-based decision making are similar. Ultimately, we now have a fantastic solution that combines the power and capability of the core C55 solution with the maturity of the UK water sector. It’s really exciting to see. This continuous planning and management capability really puts us in a new space.

What was the most rewarding part?

For the procurement process, we put together our set of requirements, including many ambitious areas of functionality that we were going to need to meet future challenges. We were unsure if any suppliers could achieve them all, but we knew what best practice could look like—and the Copperleaf team committed to deliver them all. It’s been hugely rewarding to see the vision become reality throughout the project.

Is there anything unique that AW is doing with C55 – something that hasn’t been done before?

There are lots of things. In particular, we started capturing cost data in 2005 and have been carrying out cost estimation-linked investment planning since 2007, using over 1,800 cost models built up from that data. As such, it was very important for our new solution to be able to build on that library of knowledge. Working closely with our Cost Estimating Team, Copperleaf built out a new Cost Estimation module, integrated with the rest of C55, to execute our cost models within the planning process.

Have there been any other added benefits?

At the start of the process, we undertook a comprehensive process mapping of ‘as is’ and ‘to be’. This highlighted a number of pinch points in our process, which Copperleaf was able to ‘systemise’ as part of the implementation.

How has the C55 solution been received in the wider business?

We’ve had a great response from end users. As one user put it during a training session: “I’ve only been using C55 10 minutes and it’s already a significant improvement over our previous system.”

Any anecdotes from the project?

During evaluation, we held a number of reference calls and I joked that Copperleaf must have some magic stardust they put on their users’ keyboards, because I had never heard such positive references about an IT provider. I have to say they were honest! I believe it’s Copperleaf’s focus on the customer experience that made the difference.

What made the project a success?

It may be a cliché, but the joint Anglian Water and Copperleaf delivery team deserves a large amount of credit. We started from a strong position; we had a clear idea of what we wanted to achieve due to our maturity, and the right product to deliver it. But ultimately, the drive and dedication of the team is what has carried us to a successful go-live. Anglian Water is very strong in alliancing and is recognised as an industry leader in this regard, so I wanted to carry this through into this project. And on the Copperleaf side, just the simple thing of having one dedicated project manager for the duration of the project made all the difference in having a collaborative and innovative delivery approach.

To learn more about Copperleaf’s work with Anglian Water, click here.

About Stefan Sadnicki

Stefan is Managing Director for Copperleaf in Europe. He works both with Copperleaf partners and directly with asset-intensive organisations to solve their asset investment planning challenges. His background is in business analytics and consulting and he is an active member of The Institute of Asset Management (IAM). Connect with him on LinkedIn.

Author: Jason Ballentine

As with any budget, you’ve only got a certain amount of money to spend on maintenance in the coming year. How do you make better decisions so you can spend that budget wisely and get maximum performance out of your facility? ??????????????????????????????????????????????

It is possible to be strategic about allocating funds if you understand the relative risk and value of different approaches. As a result, you can get more bang for the same bucks.

How can you make better budget decisions?

It can be tempting to just “go with your gut” on these things. However, by taking a systematic approach to budget allocation, you’ll make smarter decisions — and more importantly you’ll have concrete rationales for why you made those decisions —  which can be improved over time. Work to identify the specific pieces of equipment (or types of equipment) that are most critical to your business, then compare the costs and risks of letting that equipment run to failure against the costs and risks of performing proactive maintenance on that equipment. Let’s take a closer look at how you can do that.

4 steps to maximize your maintenance budget

1.  Assign a criticality level for each piece of equipment. Generally, this is going to result in a list of equipment that would cause the most pain — be it financial, production loss, safety, or environmental pain — in the event of failure. Perform a Pareto analysis for maximum detail. 

2.  For your most critical equipment, calculate the ramifications of a reactive/run-to-failure approach.

  • Quantify the relative risk of failure. (You can use the RCMCost™ module of Isograph’s Availability Workbench™ to better understand the risk of different failure modes.)
  • Quantify the costs of failure. Keep in mind that equipment failures can affect multiple aspects of your business in different ways — not just direct hard costs. In every case, consider all possible negative effects, including potential risks.
    • Maintenance: Staff utilization, spare parts logistics, equipment damage, etc.
    • Production Impact: Downtime, shipment delays, stock depletion or out-of-stock, rejected/reworked product, etc.
    • Environmental Health & Safety (EHS) Impact: Injuries, actual/potential releases to the environment, EPA visits/fines, etc.
    • Business Impact: Lost revenue, brand damage, regulatory issues, etc.

For a more detailed explanation of the various potential costs of failure, consult our eBook, Building a Business Case for Maintenance Strategy Optimization.

3.  Next, calculate the impact of a proactive maintenance approach for this equipment

  • Outline the tasks that would best mitigate existing and potential failure modes
  • Evaluate the cost of performing those tasks, based on the staff time and resources required to complete them.
  • Specify any risks associated with the proactive maintenance tasks. These risks could include the possibility of equipment damage during the maintenance task, induced failures, and/or infant mortality for newly replaced or reinstalled parts.

4. Compare the relative risk costs between these approaches for each maintenance activity. This will show you where to focus your maintenance budget for maximum return.

When is proactive maintenance not the best plan?

For the most part, you’ll want to allocate more of your budget towards proactive maintenance for equipment that has the highest risk and the greatest potential negative impact in the event of failure. Proactive work is more efficient so your team can get more done for the same dollar value. Letting an item run to failure can create an “all hands on deck” scenario under which nothing else gets done, whereas many proactive tasks can be performed quickly and possibly even concurrently.

That said, it’s absolutely true that sometimes run-to-failure is the most appropriate approach for even a critical piece of equipment. For example, a maintenance team might have a scheduled task to replace a component after five years, but the problem is that component doesn’t really age -— the only known failure mode is getting struck by lightning. No matter how old that component is, the risk is the same. Performing replacement maintenance on this type of component might actually cost more than simply letting it run until it fails. (In these cases, a proactive strategy would focus on minimizing the impact of a failure event by adding redundancy or stocking spares.) But you can’t know that without quantifying the probability and cost of failure.

Side note: Performing this analysis can help you see where your maintenance budget could be reduced without a dramatic negative effect on performance or availability. Alternatively, this analysis can help you demonstrate the likely impact of a forced budget reduction. This can be very helpful in the event of budget pressure coming down from above.   

At ARMS Reliability, we help organizations understand how to forecast, justify and prioritize their maintenance budgets for the best possible chances of success. Contact us to learn more.

Availability Workbench™, Reliability Workbench™, FaultTree+™, and Hazop+™ are trademarks of Isograph Limited the author and owner of products bearing these marks. ARMS Reliability is an authorised distributor of those products, and a trainer in respect of their use.

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.