Good alignment of machine shafts results in lower power usage, longer coupling, bearing and seal life and ultimately less maintenance.

Machines that change temperature between offline and running condition pose a challenge as the shafts need to be purposefully misaligned to end up at the correct position in running condition.

Hot alignments and thermal growth calculations used to be the only tools available to overcome this hurdle. Today hot alignments are still prescribed by a large number of OEMs and equipment packagers. In practice, hot alignments have been proven to produce inaccurate results due to the large initial movement just moments after machine shut down. Hot alignment practices will not capture this initial movement due to the setup time required for the alignment measurement.

Recently SVT was asked by a client to correct the alignment for a number of critical machines. By accurate measurement on one package type it was found that within 5 minutes after shut down the machines had already moved by 1 times the accepted alignment tolerance.

In the time taken to isolate the machine (which is typically around 30 minutes across most sites – shutting down, removing guards, locking on) that dynamic movement and cooling had caused the alignment tolerances to be exceeded six fold.

The data illustrates why hot alignment is a flawed practice that results in shaft alignments being outside standard tolerances and hence premature failures in couplings, bearings and seals occur.

Thermal growth causing dynamic misalignment

Dynamic misalignment occurs when machines run up and reach operating temperature, changing the relative offset and angle at which shaft centrelines connect at the coupling. Original Equipment Manufacturers (OEMs) attempt to provide guidance to help align the machines they sell, but this is not adequate once they have been packaged onto a skid.

OEMs only specify the thermal growth for their machines, but this information isn’t combined with the other machines that they’re coupled to or the thermal growth of the skid they’re mounted on. The measured growth on their machines may well be accurate, but this is in isolation and doesn’t give the whole picture.

Often the driven compressor or pump is working with process that is very hot or very cold, which affects the way it, the pipework and the skid around it grows.

As a trial thermal measurements were taken around the machines and skid to attempt to calculate the thermal growth using known linear growth formulas. The results were still not satisfactory: the alignment would have still been 3-4 times outside of the tolerance.

This shows that thermal growth and dynamic machine movement is a complex problem that can’t be overcome by using the old methods.

To align properly you need to measure the relative casing movement from an offline situation to running situation (or the reverse) to determine the actual thermal and dynamic offsets. The results of both of these scenarios should show the same relative movement of the machines.

Knowing the relative movement allows alignment compensation to obtain a good alignment in running condition.

SVT can measure dynamic offsets if applicable, align your machines, review your practices and train your on-site staff to improve alignment on your site.

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Gerard Brookhuis is a senior consultant in the rotating equipment reliability team at SVT Engineering Consultants with 15 years' experience.

Getting certified in Machine Condition Monitoring techniques is becoming more important as operators increasingly require it to work on their sites.

Operators across the oil & gas, mining, utilities and government sectors are more often than not requiring that their recruits, existing staff and contractors have a certain level of certification to perform condition monitoring tasks, including data collection, analysis and interpretation, prognosis, and recommendation for targeted remedial action.

The requirement to be certified is being driven by the need to develop independently assessed competency in technologies that reduce operating costs, improve machine reliability and availability, reduce downtime and manage operational risk. 

Detecting early symptoms of functional failure before it impacts your operations, safety and the environment, is vital in managing operating costs and risk. The decision is in making informed operational and maintenance decisions, as opposed to reaction based decisions which are often far more costly, dangerous and can have a direct impact on production.

Getting certified in vibration, lubrication and infrared thermography for condition monitoring is a stamp of recognition to show that you understand the theory, its application and have the relevant experience necessary to competently measure and analyse the data.

Being certified to ISO standards means practitioners have been trained to comply with an internationally recognised body of knowledge.

A condition monitoring program relies on consistently collected quality data to provide the basis for meaningful interpretation and recommendations. Training ensures you’re doing things the right way that produces consistent outcomes, essential to getting value out of your program on site.

To be internationally recognised, a condition monitoring technician needs to take part in three party certification: the student, the trainer and the certification body all independent from one another.

Our courses are approved by the British Institute of Non-Destructive Testing (BINDT) and the Australian Institute of Non-Destructive Testing (AINDT).

SVT offers varying levels of certification in vibration (VCAT I, II & III), lubrication (LCAT I & II) and thermography (TCAT I & II), making us the largest provider of certified integrated condition monitoring training in Australia.

Bassim Ismail is the head of the Training arm of SVT Engineering Consultants and has more than 25 years’ experience in condition monitoring.

Driving continuous improvement using maintenance data is an emerging opportunity to unlock additional value from integrity and condition management.

Large, multi-dimensional data sets can now be collated and analysed using business intelligence tools, illuminating opportunities to improve availability while reducing maintenance cost.

The potential return from monitoring the condition and integrity of production assets is accepted in industry. Operating companies willingly spend millions of dollars annually on condition monitoring and inspection. In return, they receive assurance that their equipment will function as intended and data that they can use to demonstrate compliance. 

The challenge facing operators is how to enable their people to maximise the value derived from these activities.

This is important because the value is often not as high as it could be. Condition data is rarely used to optimise future inspection cycles, which means that the full benefit of risk-based inspection planning is not realised. Recommendations to repair assets are not consistently acted on, so the activity of reviewing condition data does not deliver the desired restoration of function and performance.

Re-engineered business processes can enhance continuous improvement loops, reducing unnecessary maintenance over time. For example, an SVT study identified that bearing failures at a gas plant were caused by the same sub-optimal lubrication practice. Changing the lubrication practices resulted in avoidance of $2 million per annum in unplanned maintenance.

The challenges in achieving such improvements should not be underestimated. These can be technical in nature, for example finding cost-effective ways to clean and verify data, or find ways to automatically access data while meeting security and other corporate IT standards. 

Driving improvement may also necessitate training maintainers and operations in new work practices. We have helped schedulers to link work orders with damage mechanisms and failure modes in their Computerised Maintenance Management System (CMMS). This helped identify root causes of persistent failures across the plant, enabling the operator to take cost-effective action.

Closing the loop

Cyclical processes are a proven way to deliver continuous improvement. In asset performance management, inaction on recommendations is a common point of process failure. Such oversight can reappear down the track as non-compliances detected by regulators, breakdowns that stop production or reportable hydrocarbon releases.

Engineering work practices should include translation of recommendations to a work order in the company CMMS, triggering action.

Using data to optimise future monitoring

Optimising future inspection plans using actual plant degradation data is a basic principle of Risk Based Inspection. 

Companies that have an Inspection Data Management System (IDMS) in place will be able to identify opportunities to safely increase inspection intervals. Faster than predicted degradation rates can also flag that equipment needs to be inspected more regularly than planned. 

Identifying improvement opportunities

Even greater value can be obtained by mining maintenance data for improvement opportunities. 

In our experience, the issues that warrant action fall into two distinct subsets: multiple failures that have a low individual consequence, but could be solved with a single solution; and unique issues that have a high consequence. The latter are generally already known and mitigated.

The former are harder to identify, however the return is likely to be high. For example, deferring planned maintenance where the machine condition data shows that it is not needed often yields significant improvements in cost. This strategy can yield quick maintenance cost wins for balance-of-plant equipment.

Implementation of new or modified business processes are often necessary for organisations to realise the benefits of maintenance improvement. Deferring unnecessary planned maintenance, for example, would require a new condition based process that would interrupt the existing planned maintenance process. Key decision makers and doers have to be engaged with and supportive of the change.

Finding the right problems to focus on is also a challenge. This usually requires aggregating and interrogating disparate data sets that are not clearly connected and not readily accessible by one person. 

This is where business intelligence (BI) software can help. 

Designed to be intuitive to use, these tools place a useable ‘Single Version of the Truth’ in the hands of people who can interpret and act on it without imposing long hours of manual data handling every time. We see BI as a necessity for organisation’s that are seeking to consistently drive continuous improvement in asset management.

Effective engagement and process supported by BI are necessities for organisation’s seeking to consistently drive continuous improvement in asset management.

What to do

Companies seeking to get full value should:

• Engage: make sure key people are prepared to help make improvements.
• Close the loop: Ensure that recommended actions are correctly captured in their systems.
• Optimise using data: Optimise inspection cycles using actual equipment degradation data.
• Automate data visualisation: Implement dashboards driven by business intelligence tools that make it easy to identify ways to improve availability, risk and maintenance cost.