Using information technology to optimize maintenance operations

Last month's Management Side of Engineering column looked at important information to consider when preparing to improve the company's maintenance operations. The discussion concludes this month as the author examines maintenance optimization, the role of information technology, and value-based asset management.

06/01/2001


Last month's Management Side of Engineering column looked at important information to consider when preparing to improve the company's maintenance operations. The discussion concludes this month as the author examines maintenance optimization, the role of information technology, and value-based asset management.

Maintenance optimization is an evaluation process that examines current functions, tasks, and activities to achieve the proper investment balance between reactive, preventive, predictive, and proactive activities. This process is only achieved through a fundamental understanding of the predominant failure modes of the equipment. By understanding the problem and looking at the probability of failure for a particular subcomponent, the best judgement is made regarding the appropriate long-term and short-term corrective actions.

In some cases, a preventive maintenance approach is inappropriate for equipment; for example, where the design life of the parts involved in the failure mode is less than the expected minimum maintenance cycle. In this case, a change in the design specifications is often necessary to achieve reliability improvement.

A failure caused by inadequate or improper repair procedures is another instance where a PM strategy is inappropriate. This failure shows up as an "infant mortality" or "early wear-out" problem.

Diagnostic technologies (vibration, thermography, or performance tests) can play a role in identifying symptoms associated with problems before a machine is put back into service. However, unless this information is readily available to the workers performing repairs, these kinds of problems are rarely identified before recommissioning.

By maximizing individual worker effectiveness, the value of each employee's contribution to overall plant reliability is increased. This action improves the work environment because each employee then realizes a greater share of the company's success.

The term "optimization" implies a single point or goal of maximum plant production capacity at minimum cost. The goal of maintenance optimization is to achieve the highest level of reliability for the least investment in parts and labor. Management begins to realize these benefits by leveraging against the investment in information technology.

Maintenance optimization helps strike a balance between cost and reliability. Looking at cost per day of a "run to failure" strategy shows low costs early in the life of the equipment, but increasing expenses as reliability decreases. By overlaying the costs of an associated PM to address the failure mode, initial costs are high, but expenses per unit of time decrease as time progresses. This optimization occurs at a point where the total cost function (sum of the two cost functions) is at a minimum. The time at which the minimum occurs is the optimum time to perform maintenance.

Role of information technology

In the context of this article, information technology includes all computer networks and systems, intranet and internet applications, automation systems such as distributed control systems (DCSs) and programmable logic controllers (PLCs), and continuous or periodic diagnostic monitoring systems. Also included in the realm of information technology are engineering documentation systems, maintenance management, resource planning and scheduling, and financial systems (timekeeping, payroll, etc.).

The current state of technology allows for the integration of information into a single coherent system for optimum decision making. Advanced information technology makes optimization possible because the data is available for determining the proper time to perform maintenance.

Today's computer technology allows data from multiple sources to be viewed from a single MS-Windows application, such as Internet Explorer. This technology gives workers the ability to apply decision-making criteria uniformly based on common data and a standard set of procedures and prioritization systems. Maintenance optimization requires that a single response be generated for a given set of circumstances, independent of personnel involved.

Variations in decision making are caused by an individual's aversion to risk, which is the probability of failure as perceived by the person responsible for analyzing and authorizing corrective actions. The degree of acceptable risk varies from person-to-person based on:

  • Previous experience with this type of problem

  • Amount of information available regarding the equipment in distress

  • Confidence in the accuracy of each data source.

    • In order to achieve an optimum response to a given set of circumstances, workers must have previously defined these conditions, along with appropriate action. In addition, details of the response must be readily accessible to the workers once the conditions are met.

      Diagnostic information, such as vibration analysis, helps identify the risk in a trouble situation. Vibration is combined with reliability data to help workers evaluate risk and make the best decision. However, vibration data alone does not provide a complete picture.

      Value-based asset management

      Strategies that maximize online production time, such as extending the interval between major outages, shortening their duration, and avoiding periods of unexpected downtime, are critical to operating in a competitive environment. One such strategy is value-based asset management.

      In order to optimize maintenance, the company needs to move from a "cost-based" approach to asset management to a "value-based" plan. The key difference between the two is that the value-based concept involves strategic decision making that takes the long-term effect of repairs into account when making replace, repair, overhaul, retrofit, or refurbish decisions. The cost-based approach relies on the available budget for maintenance decision making that often ignores long-term reliability considerations. Cost-based decisions are based on experience; value-based decisions are based on experience and information.

      A value-based information system brings together maintenance, operations, and performance information. The fundamental feature of a value-based asset management system is that it decouples the installed asset from the function that the asset performs. Once the performance of the asset is objectively viewed, workers make comparisons with other like equipment or use published data to identify systematic or repetitive problems.

      Managers and engineers require access to more and more data to make these decisions effectively. Along with this need for information comes a new emphasis on reliability, driven by competition for online production time. Equipment unreliability often causes production restrictions or frequent startups and shutdowns. Improved reliability means less time in a transition state that causes temperature variations and can ultimately affect reliability.

      While these affects are not directly related, the secondary results of disturbances in an operation cause a reduction in overall capacity. Conversely, by closely monitoring reliability problems at the component level, workers improve reliability by spotting problems easily and early.

      Robert L. Matusheski works as a senior consultant helping clients in the petrochemical and chemical process industries conduct equipment reliability analysis and statistical process control. Mr. Matusheski has developed a process of maintenance program assessment and improvement that has helped over 50 companies reduce costs and improve components and overall plant reliability. Mr. Matusheski is willing to answer questions about this article. He can be reached at 540-344-9205; bmatusheski@meridium.com .



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