Author Archives: Philip Sage

SAP PM Expert - Design Architect of Green Field SAP and Reliability Plant. SAP MM QM, HR, PP extremely knowledgeable. Configured SAP DMS and integrated with SAP PM.

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.

improve-reliabilityPhilip Sage, Principal Engineer

An “unreliable” manufacturing process costs more money to operate.

Management “always says” we need to improve.

Individually, we know that “You cannot improve what you do not measure”.

So we must conclude if we want to make our process “reliable” we must measure the process reliability.

The search for measurable data that can be utilised may seem hard.  Equally hard could be a high level understanding of when a process is reliable, and what specifically must a process exhibit to be deemed reliable? Read More →

The key to efficiency is found along the shortest path between any two points.

It is remarkably simple to think of an efficient operation as one that runs in a straight line. Getting from point A to point B is rather “straight forward” they say.1

The challenge is to step back far enough from the daily nuances to be able to see the path we propose. With a clear view, we can see if it is relatively straight or if it is “remarkable” (in its curviness).

In order to travel the path of “straightness”, we need to understand each step we must take along the path. This allows us to understand which steps are then deemed as “extra steps” and are wasted energy without value. Knowing which steps we do not need helps us sharpen the focus on those we do need.
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The “extra steps” that do not need to be taken – do not need to be taken.

They are simply wasted energy.

In Reliability circles, the Path between point A and Point B is the path between the RCM study and the fully prepared CMMS system that has delivered a new work instruction document to the technician. Arguably they contain more than just a few simple steps as I have illustrated.

This has added complexity when you are confronted with so many new technical jargons like maintenance items, schedule suppression, document information records, PRT, task lists, secondary tasks, and the like. The hidden purpose of these terms might seem like it is to simply confuse the issue, so set them aside for now, and just focus on getting from point A to point B.

The action of integrating a process for efficient action invokes a myriad of words that include “combination, amalgamation, unification, merging, fusing, meshing and blending”. The use of a consistent tool, like the Reliability Integration Tool (RIT), allows you to navigate this jargon with a simple process and traverse from point A to Point B easily.

When we integrate RCM with a leading CMMS like SAP or MAXIMO® we are faced with many additional choices. These additional choices arise because the flexibility in modern CMMS systems has evolved to service a broader spectrum of the market. The market has pushed the CMMS designer, to allow for their CMMS to fit a great many organisations easily. This means the CMMS can probably do anything, but in doing so the CMMS can also do several things you probably don’t need.

Knowing which CMMS features you need now is perhaps the most important “current issue” you will have to solve.

Key in this choice is to not install what I call a “Glass Ceiling”. A glass ceiling is an artificial barrier which limits your organisation growth, because you have configured your CMMS to accidently retard future growth. This can be avoided if you know which CMMS features you will “need in the next three years” before you lock down how your CMMS should operate today.

Today, your goal is still to get from point A to point B. Deliver into the hands of the waiting technician a fully featured professional work instruction when it is required, using the data from your RCM study.

To illustrate the point a little more clearly, let us consider we own a new large piece of equipment.

To ensure the equipment provides many years of trouble free operation, you will apply the RCM method to generate the “content” needed to prepare your initial maintenance strategy.

We can call this Point A!

It is with the application of this initial strategy and some improvement activities, you intend to operate the new asset, following the straightforward, prudent application of maintenance when it is needed, not before or later than needed. This is all considered best practice stuff – well done!

Now – let’s define Point B as the Preventative Work Instruction you will print from a CMMS work order and hand to your technician. This document is very important because it will serve as the transfer vehicle for all of your hard work. Recall you started with RCM preparing the maintenance strategy and have transitioned to the work instruction content that the technician can execute.

The challenge is of course getting the CMMS to print this document, on time, not early, and complete in the format needed by the technician.

This is not as easy as it sounds.

Understanding the underlying RCM Analysis database tables alone is complex. Aligning the RCM tables to the CMMS database tables is complex integration work that forces the data into load sheets for each CMMS table. This typically is a format that few understand well.

Factor in the requirement to produce a work instruction document using a standard template that looks like a professional work Instruction document, will generally involve a “heap” of work.

Faced with such a large amount of work, we all want an “easy” way out. What you need is a simple to use, consistently formatted set of tools that help you get from point A to point B. It is important to know that such a set of tools exist and they are easy to use. The ARMS Reliability’s Reliability Integration Tool (RIT) is the leading example of one of the tools currently available.

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The individual toolset items take more space than that provided in this blog, so I will leave you with a teaser.

The tools do exist – and working with ARMS Reliability we can help you travel from point A to point B easily. We can help you do this without wasted steps and produce professional work instruction documents AND also load SAP, MAXIMO and most every other CMMS known to man.

To learn more:

This is just one of the many topics we will cover at the Reliability Summit 2014, October 27 to 30th. For further event details on speakers, topics, workshops, visit armsreliabilityevents.com. If you would like to discuss in further detail the Reliability Integration Tool with one of our consultants, please contact us at info@armsreliability.com

Reliability Summit Monochrome

 

By Philip Sage

Work instructions are written documents intended to convey how to do a job.

They are an integral part of the process that begins with designing the maintenance strategy using RCM and ends with the execution of the work delivering value to the machine.

Just how important is it to develop and produce excellent work instructions? Read More →

What I want to know from my failure data is “where” to focus limited resources to make the largest impact now.

It is that simple. And as a rule KISS (Keep it simple stupid) applies.

For me – “if” I am collecting failure data , I want to use it to prevent failures in the most useful way. ISO 55000 will be released next year and that standard for asset management includes requirements for robust FRACAS (Failure Reporting and Corrective Action System). Read More →

KIT UP

Kit up is a simple concept, and is one whereby you preassemble work packages and prepare them for execution off line to the repair, so that when the craftsman engages the work activity, they have every thing they will need in their kit.

Measurement of the kit up rate is an excellent metric, because in order to produce a kit up, the reliability of the planning, scheduling and warehouse methods must be high. It is thus a good thing!

To demonstrate why the reliability of the subordinate processes must be high, we need to examine the serial nature of the process of producing a kit. Read More →

RCM and LEAN Do they mix or are they like Oil and Water?

RCM studies are a pain – usually because they take so much effort and so many steps that it is common they often never finish. When a cool tool comes along to make that process easier – well even “easy?”, that is worth blogging about. Read More →

A good friend once told me “If you don’t know where you are going, any road will take you there.”

As we start a journey to talk about the reliability business, first we must talk about “direction” and recount some thoughts I wrote into a recent book on Business Performance Management  (The Maximo Managers Guide to Business Performance Management). Read More →