Predictive Maintenance Program Implementation and Improvement

In today’s business climate, it has become apparent that a quality predictive maintenance program is not only beneficial but paramount to running a quality maintenance... Read more »

In today’s business climate, it has become apparent that a quality predictive maintenance program is not only beneficial but paramount to running a quality maintenance program. The largest hurdle to clear is how to get started and how to avoid roadblocks that could damage the program prior to maturation.

Predictive Maintenance Program Initiation

The work that is done prior to startup will determine the success of the program as it moves forward. There are certain questions that need answered to assist in making the right decisions concerning how to set up the program.

First and foremost, it needs to be determined what is in place currently in regards to personnel and financial flexibility. To make any program successful, it has to have representatives from the maintenance team, operations and safety departments. Having this cross-functional team in place will guarantee that there is plant-wide buy-in and each department has a reason to see the program succeed. Each area of the team needs to be aware of their financial responsibility for the program prior to startup.

The next question is how this program will be measured. What maintenance key performance indicators (KPIs) will be affected by the predictive maintenance program and how will the results be communicated? By being able to tie in the results of a predictive maintenance program with corporate goals and KPIs, it will assist in keeping this program in the forefront of management’s mind. By combining cost avoidance savings from predictive maintenance finds with positive KPI improvements, the program’s successes can be published and assist in defending against any budgetary cutbacks.

Once the team is built and the measurements are in place, it is always advantageous to find out if any other departments or divisions within the organization have gone down this road in the past. The ability to mesh predictive maintenance programs within an organization will assist in avoiding in-house roadblocks.

Finally, the predictive maintenance team will need to agree on a criticality list plant-wide so the program can be developed around them. One of the major problems companies have is monitoring the wrong equipment. The equipment needs to truly be in the “A” and “B” categories so cost justification can be accomplished. Now it’s time to decide if the program is going to stay in-house or be contracted out.

In-house vs. Contracted Predictive Maintenance Programs

Once it has been determined that a predictive maintenance program is viable within the organization, it needs to be decided whether the program is going to be contracted out or kept in-house. Below is a list of questions that will be paramount in determining the correct course of action:

  1. Which predictive maintenance technologies are going to be implemented and what are their frequencies?
  2. Is there sustainable manpower to collect and analyze all of the predictive maintenance data?
  3. Is it feasible to initiate a training program for collection and analyzation or should it be contracted out?
  4. Does the budget include financial flexibility for equipment, software and training?
  5. How are the predictive maintenance anomalies going to be communicated along with any corrections to the customer?
  6. Is a root cause analysis (RCA) protocol in place?
  7. How can cost avoidance savings be extrapolated and communicated?
  8. What identifiers will be used to track predictive maintenance work within the CMMS?
  9. What type of turnover contingency plan will be put in place to ensure the program is sustainable?
  10. An annual audit of the program will need to be completed to ensure the correct equipment and frequencies are being utilized?
  11. If contracted out, what safety barriers will need to be overcome?
  12. Is a third-party contractor available to provide a full predictive maintenance program?
  13. What type of reporting can a contractor provide past the basic equipment software?
  14. Are the contractors familiar with the industry and equipment types?
  15. Can the contractor provide the opportunity for benchmarking at other locations?

By answering these questions, it should become obvious which direction best suits an organizational situation. Processing the questions above will provide a good indication of what people and processes will need to be in place and in what areas a company is lacking. Not all of these questions might be able to be answered at this time, but this will assist in developing a roadmap to success.

When looking at organizations to assist in a contracted predictive maintenance program, it is also wise to look at a company that is a third party. It is important that the success of the program is their sole deliverable as a program moves forward. Validity of the information is paramount, and by hiring a company that sells parts and/or services, the equipment can lead to distrust and weakening of the program as a whole.

Next, it is important to note that there are variations of predictive maintenance programs that are contracted. Some reputable companies provide analysis while the organization collects the data. This can be a viable option until the organization is ready to complete the remaining steps to bring a full program in-house.

The steps above should assist in avoiding many of the stumbling blocks as a program is put into place. It should be noted that this isn’t something that has to be undertaken all at once, but by utilizing this protocol, the priorities have been identified for success. The work put into the planning of this predictive maintenance program will pay dividends in the end. One of the byproducts of a well-planned predictive maintenance implementation is a culture shift that is fueled by input and participation from a multitude of departments and personnel. There are no cookie-cutter predictive maintenance programs. Each organization is different. By implementing the steps and procedures mentioned in this article, the tools to build a quality predictive maintenance program are attainable.

By Aron Brendes

Originally published in Noria’s Reliable Plant 2015 Conference Proceedings

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