Enhancing Compressor Productivity How to get more from your machinery assets

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1 Enhancing Compressor Productivity How to get more from your machinery assets Bryan Long, Ph.D., P.Eng. Tom Van Hardeveld, M.Sc., P.Eng. BETA Machinery Analysis, Calgary, Alberta GPAC 18 th Annual Operations/Maintenance Conference Friday, April 21, 26 Calgary, Alberta Abstract: Many operators of gas compression equipment generate significant incremental cash flow by optimizing and improving the productivity of their machinery assets. This paper outlines approaches, trends and tips for managing these programs for compression equipment the work horse of the gas processing industry. It is widely recognized that many opportunities exist to improve the profitability of machinery intensive operations. A properly executed improvement program improves cash flow by: Reducing Equipment Downtime (preventing unplanned downtime, minimizing planned downtime) Improving Performance (improving efficiency, reducing HP losses and operating costs) Reducing Maintenance Costs (eliminating unnecessary overhauls and repetitive call-outs) Optimizing Operations (enabling reconfiguration to improve capacity/reliability and/or meet new conditions) A successful program requires the ability to identify improvement opportunities as well as teamwork from operations, maintenance and reliability staff to implement the recommendations. These key success factors are discussed in the following sections of the presentation. Identify Improvement Opportunities Monitoring is the central component of a machinery improvement and optimization program providing both quantitative and qualitative measures that drive the process. A number of monitoring techniques have been applied to industrial machinery. In the specific case of reciprocating compressors, some methods that are often employed include: Front line surveillance by operators o identify obvious leaks or problems o collect machine information via paper log sheets or automatic collection by the control system Lube oil analysis Valve monitoring o infra red temperature or ultrasonics 1

2 Engine and compressor inspections using sophisticated analyzers o analysis of vibration spectra; resonant vibration vs. crankshaft angle; P-V curves o portable, periodic or online, continuous Analysis of operating parameters o key indicators developed from processing operating data (log sheets) o normalized measures, deviations from baselines, trends, etc. The last approach is an extension of front line surveillance programs. Traditional surveillance programs rely on the operator recognizing a change in the readings being recorded. Such programs are beneficial, but are unable to detect many subtle changes and do not provide quantitative measures of key attributes such as efficiency, capacity utilization and economic factors, which are dependent on a range of simple to extensive calculations. In addition, operators typically do not have the time, or the tools to sift through the massive amount of data and perform detailed analytical calculations. The result is that equipment data is often not being analyzed to pinpoint improvement initiatives. Put Your Data to Work Using Analytical Tools Analysis of operating parameters uses the data already being recorded, for the most part, to develop these important indicators and trend them over both the short and long term. The table below lists some of the mechanical faults, performance deviations and optimization measures that can be quantified through mining of existing operational data. There are certain faults that cannot be detected in this manner, but most can be. Measures can often be expressed in dollar terms, enabling informed decisions on allocation of maintenance, operation and capital resources. Reciprocating Compressor Failure Mode or Fault Diagnostic Indication Leaking valves Leaking rings Improper valve dynamics No * High valve losses Excessive rod load Inadequate rod reversal Loss of throughput Overload Excess component temperatures Crosshead/pin knocks No * Improper control system performance Under utilization of capacity/power Low reliability/availability and/or utilization Table 1 Reciprocating compressor faults detected by analysis of operating data (* indicates fault modes inspected using compressor analyzers). 2

3 As illustrated in the following examples, inexpensive analysis tools are now available to extract insights and identify pending failures from existing data. Correlations, deviations, and baselines are some of the powerful tools available for engineers and maintenance teams who manage these assets. Example 1: Benefit of Tracking Key Fault Indicators (rather than trending raw data) Operators manually log readings from a medium size sales compressor. The gauge readings include suction and discharge pressures, and temperatures. These values vary substantially in normal operation, which tend to mask developing faults. A normalized, key indicator called discharge temperature deviation was developed from knowledge of equipment operation. Rising values, as seen in Figure 1, indicate a possible internal leak (valves or rings). The cash flow impact of this impending failure was estimated at $8K production at risk due to possible cylinder liner damage plus extra maintenance cost. Tracking the key fault indicators allows local managers to make an informed decision. Figure 1 Rising trend of discharge temperature deviation indicates a problem. Example 2: Baselines Are A Powerful Tool For Managing Equipment The development of sensitive, normalized fault indicators is illustrated in a second example. This illustrates why simple trend graphs are often not useful for detecting improvement opportunities; and they create frustration for operations staff who have to make maintenance p 6 recommendations. 4 The example outlines the steps used in Beta s analytic tools to create a baseline (Figure 2): The red line (top line of Figure 2) trends power turbine lube oil drain temperature from a gas turbine. As this temperature is influenced by bearing problems, some operators try to use it to monitor the bearing; but DEV.PT BRG TEMP DIFF (DEG C) Log Date Figure 2 Red (top) line is trend of oil drain temperature. Green (bottom) line is temperature difference (in vs. out). 6 PT LO DRAIN TEMP (DEG C) 3

4 this data, taken over a period of known normal operation, shows widely varying lube oil drain temperatures. Detection of a small change due to a bearing problem would be unlikely. The green line (bottom line of Figure 2) is an improved measure, trending the difference between lube oil temperature in and out (temperature difference). Notice there is still a lot of variability which reduces the usefulness of this measure. A scatter graph of power turbine speed versus lube oil temperature rise, as shown in Figure 3, was created. Clearly there is a strong correlation between speed and temperature difference. If the equipment starts to deviate from this curve, then there is very high likelihood that a problem is developing. Alarms are triggered to warn operating staff when events occur outside the operating envelope. Trending these curves allow for accurate predictions. PT L/O BRG TEMP DIFF Problem identified (outside normal condition) P.T. SPEED N3 * Normal operating envelope (baseline) Figure 3 Gas generator speed vs. oil temperature rise shows a strong correlation. P P 4 P 1 C O D T S A Many Companies Now Outsource The Analysis Of Compressor Data A basic compressor monitoring program can be implemented with a modest incremental effort. But some difficulties are experienced throughout the gas production industry: lack of TIME to analyze data lack of SPECIALISTS to review equipment data and recommend changes staff TURN-OVER, which cripples a program program COSTS; expensive software/hardware, training, and staffing issues getting sufficient VALUE from the program challenges with data analysis from MULTIPLE LOCATIONS A solution adopted by many operators is to outsource portions of the monitoring and optimization program. In these cases, data is analyzed remotely by a company with the analytical tools and machine experts required to provide recommendations to the operations staff. Partnering with a firm whose core business is machinery reliability and performance overcomes issues of training, program continuity, lack of specialist skills and lack of time. In addition, the initial investment is small and the costs are usually a low monthly fee per machine. 4

5 Implementation Success Requires Cross-Functional Teaming A successful machinery improvement program involves acting on recommendations and effectively implementing equipment changes. For many companies, this is easier said than done. Often challenges emerge in communication and involvement from different groups. Here are some roles that must be included in a program for it to succeed: maintenance staff use the information and recommendations to support doing what is needed, when its needed (condition driven maintenance) operations management need to measure availability, reliability, and the economic impact of optimization and improvement initiatives engineering operations use the measures to ensure the machinery is operating to its design capacity, or within an acceptable margin, and that prudent limits are observed to preserve reliability engineering facilities and design use the information to identify the need or opportunity for machine improvements in capacity, reliability and/or efficiency, and so improving the baseline capabilities As illustrated in Figure 4, there are four key elements for successfully managing the equipment productivity: Machine specifications Machine operating data and condition (key performance indicators for machine health) Experience with equipment, problems, other localized factors Operators, mechanics Implementation Capacity requirements Field development plans Economics Implementation Experts in performance, reliability, optimization Management of the data mining process Analysis, reporting, recommendations Implementation Figure 4 Elements of a successful machinery monitoring, improvement, and optimization program. Data obviously originates with the operating company in one or more of several possible ways, as noted previously. Data mining, interpretation and identification of proposed improvements will mostly originate with the monitoring specialists the outsource partner. Operating company personnel are vital team members providing operational inputs to decisions. In-house maintenance personnel need to play a similar role. When 5

6 the operator has some in-house engineering capacity, the role and responsibility of the internal versus the external players must be defined, but this is not hard to do. These stakeholders must come together as a team in order to make good decisions and ensure that the decisions are properly executed. This is where many monitoring programs have fallen short over the years. An important function of the monitoring program is to measure improvements, in economic terms where possible. The following three examples illustrate the potential results achieved through a well managed machinery improvement program. Example 3: Optimization Restaging Saves $17K per year Monitoring on a two stage compressor showed poor efficiency in stage 2 and high HP losses. Adiabatic efficiency in stage 2 was running around 4%. Analysis of the configuration indicated that a single stage configuration would be better. ADIABATIC EFFY ST1 (%) Log Date OPERATING HOURS: DATE: TIME: 16: SEQUENCE: ADIABATIC EFFY ST1 (%) = ADIABATIC EFFY ST2 (%) = Figure 5 Efficiency of Stage 2 cylinder improved after reconfiguration ADIABATIC EFFY ST2 (%) COMPRESSOR BRAKE PWR (KWb) Log Date Figure 6 Power decreased after reconfiguration After the reconfiguration to single stage, efficiency improved to over 7%, as shown by the step improvement in the red curve of stage 2 efficiency. At the same time, power decreased by about 2KW, as shown in Figure 6. The resulting saving in fuel was about $17K /yr. 6

7 Example 4: Optimization Improved Capacity Enables Incremental 2MMSCF/D This example deals with a medium size (14 HP), four throw, two stage compressor required to cover widely varying operating conditions. It was found that, in some of those conditions, the unit was unable to deliver the required throughput. The power demanded at various operating conditions is shown in Figure 7. Those conditions that exceed available power are marked. High flow rate conditions where required compressor BHP exceeds available power from engine (15-19 MMSCFD) 1 TOTAL BHP Vs.DRIVER RATED BHP % 75 5 Total BHP HP Due to Acoustical Recommendations Pressure losses (HP) due to orifice plates CONDITION NUMBERS Figure 7 Power requirements at various operating conditions. The power consumed for pulsation control (orifice plates and choke tubes) is shown in Figure 7 also, and is a significant factor. The black curve in Figure 8 shows the same information more clearly. Through modeling and design analyses, improvements were made to pulsation control and piping configuration, resulting in reduced power losses, while maintaining reliability. The mauve (bottom) line in Figure 8 shows the power for pulsation control a very large reduction in power in the optimized design, especially at operating conditions that were previously power limited. 7

8 POWER CONSUMPTION (HP) BEFORE: - As found - HP Losses Range between 5 and 175 (3.5% - 12%) Guideline AFTER: - Beta recommendations - HP losses reduced below optimization guideline CONDITION NUMBERS Figure 8 Power losses for pulsation control before and after optimization. It was calculated that the saving in fuel gas consumed would be worth about $75, per year. But the real benefit arises from being able to increase the throughput at the previously power limited conditions. Table 2 identifies the incremental revenue rate at these conditions. Operating Condition # HP Savings HP/Q Ratio Incremental Q (Capacity in MMSCFD) Incremental Revenue (Annual) $6.1 $5.3 $4.2 $3.2 $3. $3.2 Table 2 Incremental revenue potential at high power operating conditions. Quantifying the economic losses being experienced and potential improvement in economic terms supported an informed business decision. Example 5: Optimization Fleet Management Improvements A monitoring program should track key operating metrics including utilization, availability and reliability both for individual units and for the fleet. Figure 9 shows a history of fleet average availability for a group of field compressors. Note that the availability fell short of the 98% target for most months between May and October,

9 This summary and the corresponding individual unit results can be used to focus attention on remedial steps. The associated key indicators from the monitoring program play an important role Availability (%) of Compressor Fleet: NW Alberta Region 98% (Target per budget) May-5 Jun-5 Jul-5 Aug-5 Sep-5 Oct-5 Nov-5 Dec-5 Jan-6 Figure 9 Monitoring fleet and unit Improved Availability of Fleet (9 compressors): 2% increase in availability = $5K incremental revenue per year The improved fleet average availability over the next three months enabled increased production and cash flow. Other Observations For Successful Programs: Operating philosophy: a proactive approach provides better results than run to failure, except for smaller, non-critical equipment. A monitoring program should be applied to other important machinery o not just a program for reciprocating compressors o o the engine or motor (driver) is often the weak link in reliability also monitor screw compressors, centrifugal compressors, critical pumps, etc. Canned analysis programs are not sufficient: o analysis and data mining tools need to be flexible o instrumentation in place varies widely o must be able to monitor different machine types o need to be able to modify and customize analytical methods and algorithms to support ongoing program improvements o reliance on automatic diagnoses results in too many false positives and too many false negatives; interpretation and confirmation by specialists is essential Vibration analysis or compressor analyzers may be required for some applications in order to adequately cover failure modes of concern. 9

10 Conclusion In summary, the incremental returns from improved machinery productivity are significant. To realize optimization and improvement benefits, successful programs address the following issues and questions: What equipment is important to your operation and should be included in the program? What program is best for your operation? Who will analyze the data and provide recommendations? Who gets reports and what do they do with them? How are recommendations communicated and implemented? $35K Preventable Loss An example of how NOT to execute a machinery monitoring program! 19 HP Engine: Vibration signatures from turbocharger Typical vibration in previous inspections Increasing levels associated with turbocharger run speeds Replacement was recommended but not carried out... and as a result... Quoting from page 6 in this document: These stakeholders must come together as a team to make decisions and ensure that the decisions are properly executed. This is where many monitoring programs have fallen short over the years. 1

rd and 4 th stages, see Fig. 2). If unchecked, fouling steam turbine steam rate and requires a maximum can cost over /day.

rd and 4 th stages, see Fig. 2). If unchecked, fouling steam turbine steam rate and requires a maximum can cost over /day. Application Note Ethylene Plant Machine Condition and Performance Monitoring The critical compressor trains in an ethylene plant can result in millions in lost production as a result of unnecessary downtime

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