Click for next page ( 30


The National Academies | 500 Fifth St. N.W. | Washington, D.C. 20001
Copyright © National Academy of Sciences. All rights reserved.
Terms of Use and Privacy Statement



Below are the first 10 and last 10 pages of uncorrected machine-read text (when available) of this chapter, followed by the top 30 algorithmically extracted key phrases from the chapter as a whole.
Intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text on the opening pages of each chapter. Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.

Do not use for reproduction, copying, pasting, or reading; exclusively for search engines.

OCR for page 29
29 CHAPTER FIVE CONCLUSIONS Each light rail transit (LRT) agency operates in a unique The need for and efficient use of common spare parts was environment. For this reason, it is difficult to guide a light rail noted by many transit systems. Although this is difficult to agency to an optimal maintenance staff. However, it is nat- achieve given the number of railcar vendors in the market, ural for managers to be curious as to how they are doing; to the industry might want to select and standardize key com- compare themselves with industry norms. This synthesis of ponents with high failure/replacement rates. industry practice offers some information in this area. The industry does not use part-time employees: only 4 of It does not appear that the number of vehicle maintenance the LRT industry's approximately 3,400 maintenance work- staff has any direct relationship to vehicle type, average vehi- ers are designated as such. Moreover, there is universal agree- cle age, or rate of revenue service failures. Nor does climate ment that it is less expensive to implement overtime than to or even age of system infrastructure allow for any firm con- hire additional staff. clusions on the optimal maintenance of way (MOW) staff lev- els. There are too many factors involved to be able to isolate The case studies were helpful in providing information any one as causal, and too few LRT systems to perform a on maintenance staff levels. The four systems chosen for meaningful regression analysis. There are also nonquantifi- review were organized somewhat differently and had differ- able factors involved, including budget constraints, collective ent numbers of maintenance positions. Overall productivity bargaining agreements, worker morale, and/or management as measured by total maintenance employees per unit of philosophies. It is not possible to extract from published sys- common measure (track-mile, peak vehicle, or car-mile) tem statistics clear guidance on maintenance staffing. appears to be better with simpler organizations and fewer job classifications. Certain indicators are used by most agencies as bench- marks. The most widely used is the "number of revenue sys- There also seems to be a fairly consistent range of tem failures" for light rail vehicle maintenance. However, accurate information on this indicator is lacking owing to the maintainers-to-manager ratios across the industry. These varied definitions in use. National Transit Database statistics vary somewhat by the technical nature of the maintenance show reported annual revenue system mechanical failures function. For example, most agencies reviewed had more ranging from zero to several thousand. This range appears to managers to maintainers in the signal and communications be large. Because of its importance to maintenance man- functional area than in any other. This makes sense given the agers, the industry could benefit from a consistent definition critical nature of this subsystem. The study results could be of "revenue system failures." used to confirm whether a staffing plan has a reasonable blend of managers and maintainers. For MOW maintenance the benchmark most used is "cost per track-mile." Comparing the cost to maintain a track-mile The staff productivity indicators--employees per unit of among U.S. cities, however, is difficult, because each system is measure--vary as well among the agencies surveyed. It in a different cost-of-living area. Spare parts, on the other hand, was nevertheless possible to recognize a possible common are often purchased on the national or even global market. Some range. Light rail transit systems can use these common useful non-cost indicator of MOW maintenance performance staffing ranges (summarized in chapter four) as a check on could be selected by the industry as its standard benchmark. reasonableness.