BI-Cycle 2012 for Maximo demo and evaluation offer

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The BI-Cycle 2012 maintenance data mart model has load scripts for Maximo 4.x, 5.x, 6.x, 7.x which can very quickly deliver a proven comprehensive KPI reporting, failure and reliability analysis environment for continuous maintenance improvement.

The BI-Cycle 2012 model includes:

  • KPI Management
  • Reliability Analysis, RCM and FMECA compliant with ISO 14224 coding for Equipment Categories, Equipment Classes, Equipment types, Failure Mechanisms, Failure Modes, Failure Causes, Detection Methods, Maintenance Activities.
  • Master Data Management
  • FastPlan v2

BI-Cycle delivers value from the first time you put data into the model and start looking at your own data in a new light with the analysis tool.

The BI-Cycle Maximo demo and evaluation offer is:

  • to build a BI-Cycle demo model with your data.
  • deliver a web presentation of the BI-Cycle Analysis tools and data mart model using your data.
  • At NO CHARGE

To build the model you need to provide an Oracle .dmp of your Maximo Schema and we can put in place an appropriate Non-disclosure agreement to cover this activity.

Based on the experiences of other BI-Cycle implementations you will probably not be surprised by some of the messages the tool will deliver but it will quickly highlight problem areas, provide the evidence for potential maintenance improvements and show how BI-Cycle can be used to support your maintenance activities.

To progress the offer email: maximodemo@greycloud.co.uk

‘Bucket’ work orders

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‘Bucket’ work orders for recording hours are a sure indicator/sign of business process failure around the CMMS. These buckets of time fulfil a misplaced management need to account for the billing of maintenance hours, even though there is no evidence as to what work was done. As a simple rule of thumb I would suggest that any work order that has a duration longer than one week should be reviewed to be broken  down.

Recording hours – I believe it is very important that the maintenance culture should support the technician recording and taking credit for all the hours that he spends on a work order. This should include safety/review of procedures, wait time (permits/isolations etc.), looking out/collecting materials, wrench time, and fully recording what was done in the CMMS and providing feedback on the planning and content of the work order.

Failure Analysis of ‘Near Misses’

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The upside of condition-based monitoring and digital control systems is that they are proactive in preventing failure but the downside is they frequently mask the cause of failures.

These near misses should be treated as failures and analysed as such.

It is important that every touch/visit/intervention on the equipment is recorded in the CMMS, e.g. trips and resets are not general duties for the electrical crew, they should be recorded as corrective work in the CMMS against the equipment involved. They are frequently an indicator of a problem elsewhere.

It is often impractical and there is a lot of resistance to raising a new work order in these instances for each return visit to the kit to reset, but the simple solution is to raise one corrective work order against the equipment and record each intervention against it until the problem is fixed. A failure problem/cause recorded as ‘Unknown’ should not be acceptable to supervisors/management looking for improvement.

CMMS – Building the ‘Big Picture’

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The Big Picture – to get the big picture of events over time you need to obtain and analyse a lot of data from a number of different sources, CMMS, condition monitoring, SCADA, DCS, Production reporting. It is always difficult to identify links between these different silos of information but the TIME dimension is certainly always one.

The data ‘is what it is’ and the CMMS is normally capable of recording what is needed but it is a fact that as more automated monitoring and control systems are added this data is recorded elsewhere and does not find its way back to the CMMS. This could be one reason why there are so few meter based PMs active, as this data is not directly recorded in the CMMS and so frequency based PMs are the norm. The technician cannot record what he no longer sees.

The big picture shows where we burn the most resources, most failures, lost production, hours, costs and helps identify the bad actors, whether they are machine or human. We can then improve data quality and business processes, repair, redesign, replace equipment with a business case based on evidence and monitor improvement. This is a powerful tool for changing behaviours which is the first step towards continuous improvement.

The BI-Cycle Plant Information Data Mart model delivers the ‘Big Picture’ for the continuous maintenance improvement process.

The Concept of NEGATIVE WORK

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There is a lot of interesting discussion and theory around staff resistance to maintenance program initiatives regarding buy-in, training and supporting the maintenance program, however I think the simple insight is that the Supervisors and Technicians have seen it all many times before. Hence the negativity.

Over the years they have survived new systems and business processes and watched management initiatives come and go. Most of which from their perspective increased their workload rather than reduced it.

The ‘Dilbert Principle’ comes into play – ‘If you’re a surgeon, it takes a great deal of skill and intelligence to perform an organ transplant. It is much less challenging to write a mission statement for the hospital that explains your deep desire to avoid killing patients accidentally.’ – Scott Adams

You don’t want the administrator performing heart bypass surgery on you.

I believe that to achieve ‘buy-in’ from the workforce to continuous maintenance improvement you have to  change management behaviour around the maintenance processes.

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EAM KPI Management and Performance Reporting

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Looking at the EAM marketplace there seems to be a lot of discussion and uncertainty in the user base around reporting and which tool to use.

Using the market leading IBM Maximo as an example, so far we have had SQR, Actuate, BIRT, and now IBM is pushing COGNOS as a higher end approach. There is also a lot of BusinessObjects out there connected to Maximo and other EAM’s.

All these approaches have taken a long time to develop/re-develop and in my experience have not been effective in supporting continuous maintenance improvement.

The business case for the BI-Cycle data mart, Analysis tool and KPI management/web reporting remains as strong as ever. Why burn thousands of dollars on a new reporting environment, specification, development/testing when you can install a validated environment and reports which monitor maintenance processes, master data, reliability etc.. with all the KPI metrics you could wish for.