Maintenance Staffing Levels for Light Rail Transit (2005)

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There are 20 light rail systems operating in the United States. APTA lists more, but this study excluded those smaller elec- tric rail operations not used primarily for commuting. Of the 20 systems, one is run by a contract operator (the Hudson– Bergen Line in northern New Jersey), making some of its operating information proprietary. In all, 11 of the 20 systems responded to the survey of system characteristics and the questionnaire. To supplement the 2004 information obtained from these 11 properties, information on 8 of the remaining 9 systems was taken from the 2003 NTD. Because the Min- neapolis light rail system opened in mid-2004 and had no full- year statistics to report it was the only light rail system not studied. OVERVIEW OF STATISTICS Tables 1–3 provide the characteristics of each operating LRT system that pertain to system maintenance. There is one table each for LRV maintenance (Table 1), MOW (Table 2), and stations and facilities (Table 3). The top grouping in each table is the 2004 survey information supplied by the respond- ing agencies, the bottom grouping is 2003 information taken from the 2003 NTD. Because the NTD does not ask rail sys- tems to report certain information that was believed to be important for this synthesis, some sections of the lower group- ing are blank. Table 1 shows information on LRV maintenance. Each system’s operating environment typically determines the physical design of its LRV: length, width, articulation, max- imum speed, and floor level. Nevertheless, most light rail systems use an articulated LRV design. With recent vehicles there has generally been an increase in the maximum operat- ing speeds of LRVs, from 50 mph to 65 mph. A recent devel- opment in vehicle design is the introduction of the low-floor railcar, allowing passengers to board the vehicle without climbing steps. A number of factors may influence the level of LRV maintenance; among them are: • Operating environment—more street running results in more stop-and-go operation and more accidents. Extreme weather conditions may also result in more maintenance. 4 • Type of vehicle—technically advanced vehicles most likely require more maintenance. • Experience of the manufacturer—new vehicle designs or a less experienced vendor may result in additional ongoing maintenance. Proprietary parts may be costly to obtain. • Labor constraints—work rules may affect efficiency, and high employee turnover rates lower staff productivity. • Staff experience—new systems may have higher costs because staff is less experienced or is purposefully overstaffed for planned expansions. • Budget constraints—systems often experience budget constraints that limit the amount of maintenance performed. • Spare ratios—a higher spare ratio increases apparent maintenance staff per peak vehicle. Table 2 presents factors involved in the maintenance of the guideway including the track, traction power (substations and overhead catenary), and signal and communication subsys- tems. Light rail systems operate primarily at-grade to reduce capital investment. Operating speeds increase by protecting the at-grade tracks as much as practical from automobile traf- fic. In the best case scenario, light rail trains operate on a ded- icated right-of-way with only occasional street crossings. A number of LRT systems achieve this. Buffalo has the highest percentage of track-miles in subway by far (78%); more than half of all systems have no subway segments. Some of the factors that influence guideway maintenance include: • Climate conditions—Significant range of temperatures or substantial amounts of rain and snow may result in more maintenance. • Operating conditions—Significant on-street running in mixed traffic or on/in structure constrains maintenance of trackway and traction power systems. • Age of infrastructure—Older systems require more maintenance than newer ones because more things wear out over time. • Labor terms—Work rules may affect efficiency and high worker turnover results in a less experienced staff. • Budget constraints—Systems often experience budget constraints that limit maintenance performed. CHAPTER TWO CHARACTERISTICS OF EXISTING LIGHT RAIL TRANSIT SYSTEMS RELATED TO SYSTEM MAINTENANCE

System Y e a r o f S t a r t - U p E q u i p m e n t T y p e ( m a x i m u m s p e e d ) * V e h i c l e s O p e r a t e d i n M a x i m u m S e r v i c e T o t a l A c t i v e F l e e t A v e r a g e A g e o f F l e e t ( Y e a r s ) T o t a l A n n u a l R e v e n u e M e c h a n i c a l F a i l u r e s A n n u a l V e h i c l e R e v e n u e - M i l e s R e v e n u e V e h i c l e - M i l e s p e r R e v e n u e M e c h a n i c a l F a i l u r e A n n u a l L a b o r H o u r s f o r I n s p e c t i o n a n d M a i n t e n a n c e A n n u a l V e h i c l e M a i n t e n a n c e E x p e n s e s M a i n t e n a n c e C o s t p e r V e h i c l e R e v e n u e - M i l e M a i n t e n a n c e C o s t p e r V e h i c l e O p e r a t e d i n M a x i m u m S e r v i c e FY2004 STATISTICS FROM STUDY SURVEY (2004$) (2004$) (2004$) Buffalo 1985 HL/LL (?) 23 27 19 555 765,082 1,379 39,520 $2,249,087 $2.94 $97,786 Cleveland 1989a ART (55 mph) 16 48 22 90 954,081 10,601 64,254 $2,391,337 $2.51 $149,459 Dallas 1996 95 ART, 1 LF (65 mph) 84 95 6 135 5,372,890 39,799 94,556 $7,917,463 $1.47 $94,256 Denverc 1994 ART (55 mph) 45 49 5 0 3,764,205 0 76,222 NP NP NP Houston 2003 LF (?) 15 17 1 119 478,398 4,020 19,741 $2,525,300 $5.28 $168,353 Philadelphia 1980b not-ART (?) 115 141 24 825 1,598,000 1,937 131,000 $10,800,000 $6.76 $93,913 Pittsburgh 1985 not provided 48 70 10.9 454 1,224,844 2,698 199,360 $9,537,598 $7.79 $198,700 Portland 1986 30% HF, 70% LF (?) 83 95 9.2 1,990 6,775,188 3,405 107,440 $13,406,170 $1.98 $161,520 Salt Lake City 1999 ART (55 mph) 39 46 5.6 72 2,355,429 32,714 49,213 $3,680,000 $1.56 $94,359 San Diego 1979 ART (50 mph) 83 123 14.2 150 7,078,660 47,191 153,574 $8,056,896 $1.14 $97,071 San Francisco 1912 ART (?) 110 151 4 2,583 5,616,212 2,174 791,932 NP NP NP FY2003 STATISTICS FROM NATIONAL TRANSIT DATABASE (2003$) (2003$) (2003$) Baltimore 1992 — 49 53 8.3 96 2,634,883 27,447 83,677 $4,935,321 $1.87 $100,721 Boston 1890 — 155 199 19.1 1,190 5,689,117 4,781 345,280 $15,790,689 $2.78 $101,875 Hudson-Bergen 2002 — 15 29 14.6 N/A 704,864 N/A N/A $6,142,483 $8.71 $409,499 Los Angeles 1990 — 69 102 8.8 2,489 5,781,961 2,323 384,591 $16,255,679 $2.81 $235,590 Newark 1930 — 12 16 34.5 45 478,913 10,643 136,146 $4,927,404 $10.29 $410,617 Sacramento 1988 — 32 36 13.9 40 2,128,498 53,212 160,524 $6,000,779 $2.82 $187,524 Santa Clara 1988 — 41 66 15.6 98 2,466,130 25,165 191,360 $12,406,691 $5.03 $302,602 St. Louis 1991 — 49 65 5.1 297 5,156,197 17,361 84,850 $6,111,400 $1.19 $124,722 Notes: — = NTD did not ask for this information; NP = not provided by agency; N/A = not available (proprietary). *Notes on equipment type: ART = articulated; LF = low floor; HF = high floor; HL/LL high level, low level. aCleveland inaugurated its rebuilt LRT system in 1989. bPhiladelphia received its rebuilt LRV fleet in 1980. In addition, Philadelphia uses single-ended cab cars in its Central Division, double-ended cabs in its Surburban Division. cDenver’s information is from 2003. TABLE 1 VEHICLE MAINTENANCE CHARACTERISTICS AND COSTS

System A v e r a g e T e m p e r a t u r e H i g h / L o w ( ° F ) A v e r a g e P r e c i p i t a t i o n ( i n c h e s ) W e a t h e r F a c t o r * T r a c k - M i l e s A t - G r a d e , E x c l u s i v e T r a c k - M i l e s A t - G r a d e , w i t h C r o s s T r a f f i c T r a c k - M i l e s A t - G r a d e , M i x e d F l o w w i t h C r o s s T r a f f i c T r a c k - M i l e s o n S t r u c t u r e T r a c k - M i l e s o n F i l l T r a c k - M i l e s i n S u b w a y T r a c k - M i l e s i n O p e n C u t T o t a l T r a c k - M i l e s D i r e c t i o n a l R o u t e - M i l e s A n n u a l T r a c k M a i n t e n a n c e C o s t s A n n u a l T r a c k M a i n t e n a n c e C o s t s p e r T r a c k - M i l e A n n u a l P o w e r M a i n t e n a n c e C o s t s A n n u a l P o w e r M a i n t e n a n c e C o s t s p e r T r a c k - M i l e FY2004 STATISTICS FROM STUDY SURVEY (2004$) (2004$) (2004$) (2004$) Buffalo 81/18 39 4 0 2.8 0 0 0 9.7 0 12.4 6.2 $400,000 $32,258 $875,000 $70,565 Cleveland 83/19 47 4 12.5 14.5 0 0.9 2.0 0 3.1 33.0 16.5 $1,755,000 $53,182 $985,000 $29,848 Dallas 96/34 33 2 79.4 2.5 0 11.5 0 6.2 1.8 101.5 44.5 $1,915,208 $18,869 $6,465,415 $63,699 Denver 88/16 17 3 15.2 4.3 0 3.4 7.0 0 2.2 32.1 31.6 NP NP NP NP Houston 94/41 48 2 0 19.8 0.2 0 0 0 0 20.0 15.3 $415,211 $20,761 $377,255 $18,863 Philadelphia 87/24 41 4 21.0 145.0 0 0 0 4.0 0 171.0 69.3 NP NP NP NP Pittsburgh 83/20 37 4 36.8 0.3 4.7 3.0 — 4.0 0 48.8 34.8 $1,781,000 $36,496 $2,320,000 $47,541 Portland 80/34 35 2 14.0 50.0 5.0 2.6 1.0 6.0 10.0 88.6 81.3 $1,946,600 $21,971 $1,863,000 $21,027 Salt Lake City 92/20 16 3 26.3 12.6 0 0 0 0 — 38.9 19.5 $368,800 $9,481 $75,600 $1,943 San Diego 77/48 10 1 0 80.2 8.0 6.0 1.8 0 0.6 96.6 96.6 $1,176,500 $12,179 $1,011,750 $10,474 San Francisco 70/46 20 1 5.0 6.0 48.0 0 0 15.0 0 74.0 72.9 NP NP NP NP FY2003 STATISTICS FROM NATIONAL TRANSIT DATABASE (2003$) (2003$) (2003$) (2003$) Baltimore 88/24 41 4 37.0 10.0 3.0 2.0 0 0 0 52.0 57.6 — — — — Boston 82/22 43 4 29.0 29.0 2.0 4.0 0 14.0 0 78.0 51.0 — — — — Hudson-Bergen 85/26 46 4 11.0 7.0 2.0 0 0 0.0 0 20.0 16.6 — — — — Los Angeles 82/48 14 1 4.0 31.0 0 12.0 24.0 0 1.0 87.0 82.4 — — — — Newark 85/26 46 4 6.0 0 0 0 0 3.0 0 9.0 8.3 — — — — Sacramento 93/38 17 1 9.9 19.4 6.8 1.8 1.5 0 0 39.4 40.7 — — — — Santa Clara 70/46 20 1 12.0 37.0 0 1.0 7.0 1.0 0 58.0 58.4 — — — — St. Louis 89/21 37 4 44.0 1.0 0 5.0 10.0 11.0 3.0 74.0 68.8 — — — — Notes: — = NTD did not ask for this information; NP = not provided by agency. Shaded areas indicate estimated by agency. *Weather factor: 1 = no freezing, little precipitation; 2 = no freezing, more precipitation; 3 = freezing, little precipitation; 4 = freezing, more precipitation; 5 = very cold in winter. TABLE 2 OPERATING ENVIRONMENT AND GUIDEWAY MAINTENANCE CHARACTERISTICS AND COSTS

System S t a t i o n s A t - G r a d e S t a t i o n s o n S t r u c t u r e S t a t i o n s o n F i l l S t a t i o n s i n O p e n C u t S t a t i o n s i n S u b w a y T o t a l S t a t i o n s A n n u a l S t a t i o n M a i n t e n a n c e C o s t s A n n u a l S t a t i o n M a i n t e n a n c e C o s t s p e r S t a t i o n N u m b e r o f T V M s A n n u a l T V M M a i n t e n a n c e C o s t s A n n u a l M a i n t e n a n c e C o s t p e r T V M D o n e I n - H o u s e ? N u m b e r o f R a i l M a i n t e n a n c e F a c i l i t i e s A n n u a l C o s t f o r M a i n t e n a n c e F a c i l i t i e s M a i n t e n a n c e C o s t p e r F a c i l i t y FY2004 STATISTICS FROM STUDY SURVEY (2004$) (2004$) (2004$) (2004$) (2004$) (2004$) Buffalo 7 0 0 0 8 15 $1,000,000 $66,667 42 $400,000 $9,524 Yes 1 $250,000 $250,000 Cleveland 31 0 0 3 0 34 $1,300,000 $38,235 13 $20,000 $1,538 Yes 1 $291,000 $291,000 Dallas 29 4 0 1 1 35 $3,852,202 $110,063 120 $410,338 $3,419 Yes 1 $253,925 $253,925 Denver 24 0 0 0 0 24 NP NP 42 $115,757 $2,756 Yes 1 NP NP Houston 16 0 0 0 0 16 $704,172 $44,032 58 $443,747 $7,651 Yes 1 $441,306 $441,306 Philadelphia 9 0 0 0 15 24 NP NP 0 N/A N/A N/A 3 $400,000 $133,333 Pittsburgh 0 21 0 0 3 24 $1,200,000 $50,000 0 N/A N/A N/A 1 NP NP Portland 58 1 1 1 1 62 $2,730,000 $44,032 183 $1,144,500 $6,254 Yes 2 $1,178,000 $589,000 Salt Lake City 23 0 0 0 0 23 $345,000 $15,000 62 $180,000 $2,903 Yes 1 $260,000 $260,000 San Diego* 47 2 0 0 0 49 $2,229,000 $45,490 119 $967,000 $8,126 Yes 2 $1,341,300 $670,650 San Francisco 0 0 0 0 9 9 NP NP NP NP NP NP 2 NP NP FY2003 STATISTICS FROM NATIONAL TRANSIT DATABASE (2003$) (2003$) (2003$) (2003$) (2003$) (2003$) Baltimore — — — — — 32 — — — — — — 1 — — Boston — — — — — 78 — — — — — — 4.3 — — Hudson-Bergen — — — — — 15 — — — — — — 1 — — Los Angeles — — — — — 36 — — — — — — 2 — — Newark — — — — — 11 — — — — — — 1 — — Sacramento — — — — — 29 — — — — — — 1 — — Santa Clara — — — — — 44 — — — — — — 1 — — St. Louis — — — — — 26 — — — — — — 2 — — Notes: — = NTD did not ask for this information; NP = not provided by agency; N/A = not available; TVM = ticket vending machine. Shaded areas indicate estimated by agency. *San Diego's Facilities Maintenance is included in Station Maintenance and Equipment Maintenance is included in MOW, LRV, and Facilities. TABLE 3 STATION AND FACILITIES CHARACTERISTICS AND MAINTENANCE COSTS

Table 3 shows information on each light rail system’s sta- tions and maintenance facilities. Most light rail systems have at-grade stations. These stations, however, may be substan- tial, incorporating weather protection, raised platforms, closed circuit television (CCTV) and public address systems, ticket vending machines (TVMs), artwork, and large parking lots. The stations require ongoing cleaning and maintenance. SEARCHING FOR PATTERNS Factors noted in the previous section—and more—influence light rail system maintenance staffing. One would expect rela- tionships between certain factors and LRV maintenance efforts. For example, the average age of the LRV fleet should influence the amount of maintenance needed. The data, how- ever, do not suggest this, as can be seen in Figure 1. (Support- ing data are in Appendix A.) Nor could a relationship be found using such indicators as LRV maintenance task-hours ver- sus revenue mechanical failures, maintenance task-hours per track-mile by climate type, and so forth. In short, enough fac- tors are apparently involved in each system’s level of LRV maintenance that it is not possible to strongly link any one fac- tor with any particular light rail maintenance effort. Moreover, it is also not possible to perform a meaningful regression analysis given the limited sample. Again, outside influences that could affect maintenance effort might include budget con- straints, labor agreements, and organizational structure. PRODUCTIVITY INDICATORS A major indicator of productivity is the number of annual task- hours per employee. The fewer annual task-hours available, the more employees it will take to do the work required. The 8 following illustrates the issue. A full-time worker is typically paid for 2,080 h of work annually (52 weeks × 40 h/week). How much of that time is really productive? Table 4 shows a simple analysis done in 1995 by Portland TriMet’s vehicle maintenance department. The exact numbers will vary by agency, and clearly some reduction in time (such as shift start- 0 1000 2000 3000 4000 5000 6000 7000 Sa lt L ak e Ci ty De nv er Da lla s St . L ou is Ba ltim or e Lo s An ge les Po rtl an d Sa n Di eg o Sa cr am en to Sa nt a Cl ar a Pi tts bu rg h Bu ffa lo Sa n Fr an cis co Bo st on Cl ev ela nd Ph ila de lph ia System An nu al L R V M ai nt en an ce T as k- H ou rs 0 5 10 15 20 25 Av er ag e Ve hi cle A ge in Y ea rs Task-Hours Average Age FIGURE 1 Annual LRV maintenance task-hours by average age of vehicle. Description of Time Hours Annual Pay Hours (straight time) Lost Time Hours: Vacation (2.5 week average = 100 h) Holidays (6 days) Floating holidays (3 days) Birthday (1 day) Absences (based on department’s employee absentee rate of 5%) Net After Lost Time Hours Non-Task Hours: Shift start-up and task assignments (15 min per shift) Coffee break (15 min) Lunch break (45 min) Coffee break (15 min) Miscellaneous [e.g., bathroom (5 min)] Shift end, clean-up (15 min) 110 min/shift x 230 shifts/yr x 1 h/60 min = 422 h Total Productive Hours per Year: 2,080 (100) (48) (24) (8) (104) 1,796 (422) 1,374 TABLE 4 TRIMET LABOR PRODUCTIVITY EXERCISE

90 500 1000 1500 2000 2500 3000 3500 4000 4500 5000 S an D ie go S t. Lo ui s C le ve la nd B uf fa lo D en ve r B al tim or e B os to n P hi la de lp hi a D al la s S an ta C la ra S al t L ak e C ity P or tla nd P itt sb ur gh Lo s A ng el es S ac ra m en to S an F ra nc is co System A nn ua l T as k- H ou rs p er V O M S FIGURE 3 Annual maintenance task-hours per vehicle operated in maximum service. 1400 1500 1600 1700 1800 1900 2000 2100 2200 2300 Ba ltim or e Da lla s Po rtl an d Sa lt L ak e Ci ty Cl ev ela nd Bu ffa lo De nv er Sa cr am en to St . L ou is Ph ila de lph ia Pi tts bu rg h Bo st on Sa n Di eg o Sa nt a Cl ar a Sa n Fr an cis co Ne wa rk Lo s An ge les System An nu al T as k- H ou rs p er E m pl oy ee 2,080 hours FIGURE 2 Annual LRV maintenance task-hours per employee.

10 have hours above 2,080, which may indicate a substantial amount of overtime per employee. The range is from 72% to 107% of the 2,080-h baseline. The true range among LRT agencies of average annual task-hours per employee is prob- ably narrower and most often toward the lower end. Another productivity indicator is the annual number of task-hours needed to maintain one unit of product, in this case railcars. The number of annual task-hours to maintain each LRV operated in maximum service (the peak period) as reported in the NTD ranges from 1,230 to 4,650. Figure 3 shows LRT systems from least to most annual LRV mainte- nance task-hours per vehicle operated in maximum service (VOMS) (see also Appendix A, Table A3). The broad range may result from a number of factors including vehicle design, maintenance budget, work rules, and available spare ratio. For example, the three agencies with the lowest task-hours per vehicle (San Diego, St. Louis, and Cleveland) also have high spare ratios of 48%, 67%, and 320%, respectively. Cleveland has also had a budget problem that has affected its ability to conduct as much maintenance as it wants. On the other hand, Sacramento and Salt Lake City have very tight spare ratios. This may necessitate more maintenance on their well-used fleets. The same broad range occurs for nonvehi- cle maintenance. up meetings) could be considered productive. However, it is crucial to note how much productive time is reduced by various factors. Given the vacation, holiday, and sick time an employee receives each year, the maximum number of annual work hours per employee is approximately 1,900 before overtime. Since the exercise in Table 4 was conducted, Congress passed the Family Medical Leave Act (FMLA), which allows any employee to take additional time off for illness or family- related reasons. Ten additional FMLA days would lessen the 1,374 annual productive hours shown in Table 4 to approxi- mately 1,300. The inevitable reduction of actual work time illustrated in Table 4 makes it difficult to reconcile some of the “annual maintenance hours per employee” figures reported in the NTD. The reported numbers are shown in Figure 2 for vehi- cle maintenance employees; reported annual maintenance- hours for nonvehicle maintenance employees are similar. (Supporting data can be found in Appendix A, Table A2.) The systems are listed by increasing number of average annual task-hours per employee. A number of agencies report num- bers well in excess of 1,900 h, some exactly 2,080 h. A few