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Risk-based Analysis ToolsPUBLIC ACCESS

Shrinking Robots and Growing Processors are Taking Minmally Invasive Techniques Where they have Never Gone Before.

[+] Author Notes

John Latcovich is fleet manager, rotating equipment; Evangelos Michalopoulos is a senior consulting engineer; and Bernie Selig is a consultant and retired vice president for technology with the Hartford Steam Boiler Inspection and Insurance Co. in Hartford, Conn.

Mechanical Engineering 120(11), 72-75 (Nov 01, 1998) (4 pages) doi:10.1115/1.1998-NOV-3

Abstract

American Society of Mechanical Engineering’s (ASME) risk-based inspection methodologies are being used to optimize and prioritize equipment overhaul and maintenance, and upgrade decisions. Hartford Steam Boiler Inspection and Insurance Co. (HSB) collaborated with ASME in developing these guidelines, and it used the ASME methodologies to develop its risk-based decision tools for steam turbine generators. The ASME Risk-Based Inspection Guidelines define five primary steps in developing risk-based programs. These are system definition, qualitative risk assessment, system assessment ranking, inspection program development, and economic optimization. In order to differentiate between turbines and generators in several types of service, the team designed a questionnaire that requires the owner or operator to identify equipment design features, monitoring capabilities, past operating and failure history, as well as current operating experience, inspection, and maintenance practices. The STRAP program is presently in the beta-testing phase, where 30 different turbines representing eight different manufacturers and three different industries have been analyzed. Full implementation of the program is expected to occur in the fall of 1998.

Critical Process-Industry Turbines

While the time interval between outages is the major concern for the power generation industry, the availability of steam turbine applications during production operations is the primary concern in the manufacturing and process industries. The photo below shows a typical process steam turbine rotor. When steam turbines are heavily integrated into plant processes, loss of the steam turbine will shut down the process and result in substantial lost production and revenue. Examples of this situation include boiler feed pumps, line shafts for the pulp and paper industry, blowers and generators for the iron and steel industry, and compressors for the refinery, petrochemical, and chemical process industries. In these and other process industries, the cost of the steam turbine, on a relative basis, represents only a fraction of the process plant’s assets. However, each day of lost production attributable to the turbine can result in lost revenue that may reach $1 million per day. This is the critical factor to consider when developing a risk-based analysis tool for the process industries. To quantify the risks associated with steam turbines in critical process service and assist maintenance staffs in making decisions for these critical turbines, HSB assembled a team of manufacturing, process (refinery and petrochemical), turbine repair, consulting engineering, and insurance industry experts to develop a qualitative risk-based tool, which was named STRAP (Steam Turbine Risk Assessment Program). The team included rotating equipment experts from the Dow Chemical Co., Equilon Enterprises LLC, CF Industries, Stone Container Corp., Hickham Industries, Revak Turbomachinery, Radian Corp., and HSB. The development process for this risk model was nearly the same as TOOP. A system including the associated components and subcomponents was established for the steam turbine. Because of the wide variety of steam turbine configurations used in the different process industries, these turbines were separated into five different size and speed classes and four different operating regimes. Failure probabilities and consequences were established for each of the different turbine classes, operating regimes, subcomponents, and applicable failure modes. Risk consequence here is lost production time, expressed in terms of days or in equivalent lost revenue, and/or added expense per day. This approach was used because the cost of the equipment is considered to be inconsequential compared with the amount of lost production revenue. This differs from the situation in the power industry as reflected in TOOP, where consequence was expressed as the cost to repair or replace a failed subcomponent during an unscheduled outage. To account for the differences in service between units, the STRAP model also uses a detailed questionnaire. The responses are used to raise or lower the baseline subcomponent failure probabilities and consequences based on the specifics of the unit being analyzed. As in the power generation risk model, once the baseline steam turbine subcomponent failure modes, probabilities of failure, and associated consequences have been established, then risk can be calculated. Risk-ranking results for a typical turbine are displayed in the screen shot on page 73. The chart displays the percentage of risk by major component; it also ranks the subcomponent risk’s contribution to the total component risk and ranks the failure-mode contribution percentage for each specific subcomponent. From this information, the risk drivers for each of the subcomponents can be identified, and appropriate recommendations can be established to reduce risk in these areas. Risk reduction recommendations and what-if analysis capabilities are provided in the model, as well as the capability of evaluating the return on investment for implementing the recommendations. The risk-based analysis method has cost benefits for almost any industry and type of equipment. As with TOOP, the total risk for the steam turbine can be compared on a relative basis with other steam turbines in a company’s inventory as well as in the industry as a whole. A turbine can be compared with other units in its class, within a company, with comparable industry units, with similar manufacturer’s units, and with similarly driven equipment. This information is important because the results can be used to develop risk-driven inspection plans and to prioritize maintenance actions, spares support, and other turbine decisions for a plant’s or corporation’s fleet of steam turbines. The STRAP program is presently in the beta-testing phase, where 30 different turbines representing eight different manufacturers and three different industries have been analyzed. Full implementation of the program is expected to occur in the fall of 1998. The results to date have been excellent. One major petrochemical company has saved more than$300,000 for spares as a result of STRAP analyses conducted for it during the beta-testing phase. Spares that would normally have been procured were found to be low in risk (not critical); this justified not making the purchase and saved the company money.

In manufacturing and process industries, steam turbines like this one are often heavily integrated into plant processes. Consequently, their loss can shut down the process and result in substantial economic damage.

Risk In An Electrical System

A major manufacturer asked HSB to adapt the risk- based process to evaluate the primary electrical distribution system in one of its plants, in order to see if we could determine the change in risk that would occur if some built-in redundancies were reduced and maintenance activities optimized. For this analysis, the risk- based methodologies for the previous two programs were used. Failure frequencies for transformers, switches, and other components were obtained from IEEE Standard 493, the HSB claims database, and the manufacturer’s own experience. For this model the major consequences of concern were lost production time, and equipment replacement and installation costs.

Since there were a number of electrical equipment rooms in the one plant, and decisions had to be made about one equipment room relative to another, the risk assessment process had to be more quantitative. Therefore, fault and event trees were constructed to determine failure rates and consequences more accurately. In addition, once the risks were calculated, safety and economic considerations had to be considered together. To accomplish this, the decision analysis software tool was used to perform pairwise comparisons as the basis for decision making.

These programs were a direct result of participating in the CRTD risk-based analysis process in ASME and then aggressively pursuing the company’s own needs, using what had been learned from the CRTD program. The use of risk-based analysis tools combines the technical and reliability factors of equipment with financial consequences so that the limited company resources available can be applied to the equipment that has the greatest need. The risk-based analysis method is an excellent way to help manage operations and maintenance activities, with cost benefits for almost any industry and type of equipment.

While we have used the term “risk,” risk reduction is, in most cases, analogous to increased reliability. This is especially so in an effective risk management program, where the risk analysis results are effectively used to perform the appropriate inspections and maintenance at the right time.

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