Yokogawa Digital Solutions

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Advanced Preventative Maintenance

Introduction

It can be said that when a plant manager is tasked to cut overall costs, the ‘easy’ cost-cut that is considered to be maintenance. Reductions in maintenance budgets are becoming more common at many manufacturing plants, even after instruments are expired. With reductions in maintenance budget, it becomes more difficult to sustain stable production, having a negative impact on the business, especially in the event of plant shutdown.

Minimizing maintenance costs (the more the better) while avoiding major mishaps and plant shutdown is neither safe nor logical, creating a perilous environment for all who are involved.

Besides the risk of compromising maintenance quality due to reductions in budget, companies also face the issue of losing high-level maintenance capability as veteran technicians and operators leave the industry. Their skills and knowledge are not transferred properly, if at all.

It is understood by most that cost reduction is still necessary element in creating a profitable business due to higher competition, however, we all know that the costs that come with plant shutdown and production loss will always amount to more than the cost of maintenance in the first place.

Isn’t there a happy medium? A way to cut maintenance frequency and costs without compromising the stability, reliability and safety of the plant? Isn’t there anything we can do to mitigate losing the high-level veteran knowledge and know-how that adds value to the company? Yes, in fact there is….

Solutions

One of my favorite words is data. Plant data indicates all information which exists, stemming from maintenance, to the production site as a whole. Such as operating data, daily inspections, calibration and repair records, set value, analysis results, design information and much more. My suggestion is to use this data to improve our processes and approach to preventative maintenance.

Figure 1. Integrated system architecture for Advanced Preventive Maintenance

Figure 1 represents an example of how several common products can be used to create one comprehensive Operation Data Collection tool. The amount of information that this tool can gather is vast and comprehensive. Valuable information like this (with both width and depth) can be utilized to support operations, data analysis services, and countless other areas. We know that products in IA have a specific purpose and are designed to work effectively on a stand-alone basis, but as an industry, we are coming to learn that the greatest benefits are achieved by integrating various products and respective information together.

Let us accumulate maintenance and operation data in CMMS (Computerised Maintenance Management System). Daily maintenance records are stored in CMMS directly and CMMS integrates with Data Analysis System and Plant Information Management System to acquire operation data related to maintenance.

For example, sending the operational data of running hours and process data accumulated by the plant information management system to CMMS enables you to alert the maintenance team when key values exceed predefined thresholds. Also Data Analysis Systems can issue alerts to CMMS when it detected abnormal trends. By utilising integrating data together, it is now becoming possible to prevent large mishaps by integrating data and analytics together to detect abnormalities at an early stage.

Now that we are able to fully leverage available data, our maintenance activities that have been performed regularly thus far, can now be adjusted to the best timing according to production load and equipment health. Ideally, this information could then inform us that maintenance is not needed as frequently as the regular schedule, and an adjustment would save the company money via reducing maintenance overheads. Small adjustments and savings such as this, when accumulated, can lead to big savings per annum. In the meantime the maintenance team can concentrate on proactive maintenance and extending the life of the assets, eventually leading to further maintenance reduction and maintenance cost savings.

Whilst it is great to be able to reduce our costs and extend the operating life of our equipment, as an industry we are now on the verge of an even larger problem. It is well known that many experienced operators are retiring from the workforce and taking with them many decades of experience; the situation is the same for our maintenance workforce. Their knowledge of the subtle impacts that various types of degradation will cause, and how to resolve them, are slowly disappearing. Further compounding this problem, in many cases the experienced staff members are not being replaced upon retirement.

By leveraging some of the tools and integrating their data together into one holistic system, we can gain access to useful analytic information. If this can then be enhanced with the heuristic knowledge from our experienced maintenance staff, we believe this will go a long way in reducing the gap in lost knowledge.

Conclusion

To perform such advanced preventive maintenance requires that each system is working healthy and properly. Not only to utilize plant data to support maintenance, but maintenance data also to be utilised for production optimisation. To integrate operation and maintenance together; sharing data between these two areas is key to perform not only Advanced Preventative Maintenance, but also advanced Kaizen in the process industry.