Measuring, one of the Principles to Achieve Success in Maintenance Management

If you can't measure something, you can't manage it;
If you can’t define something, you can’t measure it;
If you can’t understand something, you can’t define it;
Where there is no management there is no success;

William Edwards Deming

Although this quote from William Deming dates back to the last century its message is still relevant in today’s management.  In the field of Maintenance Management I find measuring is essential to management, as only concrete data and constant pursuit of continuous improvement will allow us to be more efficient and to improve our results.

Fairly often in industry we still come across companies where there are no reliable records demonstrating the actual figures of equipment malfunction and helping identify its sources. This lack of record-keeping generates grey areas and as a rule equipments are blamed for the various sorts of existing inefficiencies – “we have many equipment problems” is indeed a commonly heard justification for negative results: Deming’s key-points come to our mind: we do not measure, nor do we define problems, we do not manage and we do not achieve success.

Without concrete information the maintenance manager cannot justify the achieved results, nor is he able to quantify and identify the causes of major problems; he will focus exclusively on removing the consequences of day-to-day problems and will never break away from this cycle.

A possible solution involves developing a plan to get away from this situation bearing in mind the following action steps:

Creating measuring techniques and tools

These tools should be created in such a way as to collect concrete and reliable data on faulty equipment and technical issues, equipment breakdowns, intervention time with records of date and time, etc.  Specific data to be collected will be determined by each company’s reality.

Once data collection is over one of the first conclusions that are usually drawn upon starting the data analysis is that apart from equipment problems there are several operational inefficiencies which were camouflaged due to lack of data and which can be removed relatively easily.

The following example comes from a company with no information available on equipment downtime, for which equipment malfunction was usually blamed. Upon starting stoppage records and their causes the following conclusions were drawn:

 

This downtime analysis leads us to the conclusion that only 35 (50%) out of the 70 minutes of downtime are associated with technical equipment problems.

Availability	960
Downtime	70
Overall Uptime	92,7%
Equipment Breakdown	35
Equipment Uptime	96,4%

Taking a look at uptime we find a high-uptime facility – 92,7% – and a high technical equipment uptime  -  96,4%.

Setting goals and indicators

Once data collection has been completed a history record of measured parameters starts being kept, trends and average figures included. The data analysis process starts at this stage together with identification both of indicators and targets for the same. Currently a wide range of maintenance indicators is available: uptime, failure rates, MTBF, MTTR, preventive/corrective, compliance with preventive maintenance plan, etc. In my view, although the manager is in a position to calculate all indicators for his management he should select no less than two and no more than four for discussion with his team and these should always be tangible goals. This enables him to keep his team focused and avoids some degree of confusion in the analysis caused by a high number of targets.

One method that can be applied when selecting indicators is the SMART way. The chosen indicators should be correlated among them and should complement one another for the purposes of outcome analysis, one good example being uptime determination and the failure rate where stoppage time and the number of existing stops can be assessed.

Checking and analyzing outcomes

The maintenance manager should establish the frequency and time intervals of the outcome analysis together with his team. Data presentation should preferably use a graph so as to make it easily understandable to everyone. The outcome analysis should include identification of existing problems and critical equipment as well as causes of inefficiencies.

One of the most powerful tools to keep your team motivated is monitoring the results of their day-to-day performance. If team members are given a measurable feedback on their performance and are able to monitor their progress over time, they will become more motivated to increase their daily efficiency and improve the outcome of their work.  

Defining improvement plans

One of the objects of outcome analysis meetings should be the identification of the root causes for existing problems, and whenever these are identified and easily solved  action plans should be developed to reduce or to remove them. In cases involving more complex issues the maintenance manager should build specific work teams; sometimes cooperation from other departments is required in order to identify the underlying causes of problems and possible solutions and consequently develop an appropriate action plan. The Ishikawa Cause & Effect Diagram, also called “Fishbone”, is one of the available methods of problem analyzing and solving. Similar meetings should be held to address improvement projects aimed at optimizing the existing indicators.

ISHIKAWA CAUSE & EFFECT DIAGRAM - FISHBONE

It can therefore be concluded that measuring is essential both to maintenance management and to general management, in order to obtain actual data that can help managers and their teams identify the root cause of problems and their removal as well as monitorize performance and implementation of potential improvements. This is the only way to improve business efficiency, to boost the productivity of your company and to keep it on the path to success.