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3 S U M M A R Y Fleet assets are vital resources for highway agency programs and service delivery. Highway agencies make huge capital investments each year to replace equipment and spend equally large sums of money to operate and maintain the fleet. Replacing equipment at the right time reduces the overall cost of equipment ownership. When equipment is kept too long, the costs of maintenance and repairs increase, as does downtime. Higher downtime has a direct impact on service delivery and diminishes the agencyâs ability to accomplish its mission. When equipment is unavailable due to downtime, critical services are underperformed or are performed inefficiently. However, there is no widely accepted process for determining optimal replacement cycles. NCHRP Project 13-04 was performed to accomplish the fol- lowing two objectives: â¢ Develop rational processes that will provide a realistic means of determining optimal replacement cycles. â¢ Include processes and tools for consideration in making decisions regarding the optimal replacement cycles. Three products resulted from the project: a guide for optimal replacement cycles of high- way operations equipment (the guide), a Microsoft Excel-based replacement optimization analysis tool, and the tool user manual. The guide promotes life cycle cost analysis (LCCA) for determining optimal life cycles and advocates a systematic equipment replacement deci- sion process that incorporates LCCA with real-world considerations of the highway opera- tions environment. The optimization tool is accompanied by a user manual that provides step-by-step instructions for its use. The guide and user manual are Parts II and III of this report, respectively. Fleet managers often face difficult challenges in securing sufficient funds to replace their fleet at optimal cycles. Maintaining an old fleet because of replacement budget cuts and immediate reductions in expenditures costs the agency and the public more over time because of higher equipment ownership cost, higher costs of highway operations, and reduced service levels. The research effort focused on developing processes and tools that are rational and real- istic. There is a large amount of literature advocating LCCA for determining optimal equip- ment replacement cycles. Although similar in concept, there are varying approaches for equipment LCCA and different factors used in the analysis. The research team evaluated the approaches and sought to mesh prevailing economic theory with the real-world operating environment and considerations to arrive at a practical solution. The most important aspect recognized in the guide is that making equipment replacement decisions is a process. Determining optimal life cycles and making replacement decisions are Optimal Replacement Cycles of Highway Operations Equipment
4 two distinctly different exercises. Keeping with the project objectives, the project sought to develop processes and tools that are rational and realistic to help fleet managers and adminis- trators with the task of equipment replacement. The equipment replacement process can be summarized in three phases. Data Collection. As with any asset management system, quality data are keys to obtaining dependable cost analysis results. In practice, there appear to be wide variations among fleet agencies in data accuracy, detail, and consistency. These limitations were considered as the project sought to develop practical and rational processes. Analysis. Equipment is an asset and should be subjected to data-driven replacement analy- sis using LCCA, combined with systematic and methodical processes to determine optimal life cycles, identify potential replacement candidates, perform condition assessments, and prioritize replacement needs. Decision Making. Ultimately, fleet managers must combine analysis results with practical knowledge and experience to make replacement decisions and develop an annual equip- ment replacement program that optimizes the use of available replacement funding. Many considerations come into play, including life cycle cost, condition, mission criticality, avail- able replacement budgets, and others. Quality data are extremely important in equipment replacement. Several highway agen- cies were contacted for equipment information and data so that the project could develop the processes and tools based on actual equipment cost data. While sufficiently good data were obtained, it became apparent that more work is needed by the highway industry to standardize equipment reporting and data collection. A large amount of the data reviewed in the project was incomplete or contained many errors. A key shortcoming in the data was the lack of a complete database of equipment history. In many cases, detailed historical data did not exist because agencies have imple- mented new systems for tracking equipment cost, either through their financial or equip- ment management systems. When new systems are implemented, historical data are lost or are carried forward into the new system as a lump sum life-to-date quantity, thus losing annual cost data for the early years of a unitâs life. Additionally, many agencies do not record and track downtime. Downtime is a significant cost in equipment operations. It does not directly affect the fleet budget because there is no direct monetary outlay by the fleet agency. However, downtime has a real and significant cost impact on highway operations that is manifested in higher infrastructure maintenance costs and reduced service levels. The mechanic hourly rate is another data element that bears consideration. Most agen- cies do not fully account for direct and indirect overhead in the labor cost for maintenance and repairs. When this is the case, the equipment operating cost is undervalued. In one case example, an agency charging $35 per hour for mechanic labor should have been charging $53 when accounting for all direct and indirect overhead costs. Using LCCA to determine equipment life cycles requires complete, accurate, and consis- tent data, and a coordinated effort is needed to improve equipment data quality. Recogniz- ing the need for complete and accurate data, the guide provides suggested guidelines that agencies can use for reporting equipment cost, utilization, and downtime. From the literature search, the following 11 factors were initially identified as possible contributors to LCCA and the equipment replacement process. â¢ Age, â¢ Utilization, â¢ Depreciation, â¢ Maintenance and repair cost, â¢ Fuel cost, â¢ Downtime,
5 â¢ Obsolescence, â¢ Replacement cost, â¢ Purchase price, â¢ Cost of money, and â¢ Soft cost. Each of these factors was evaluated to determine its relevance to highway operations equipment. The cost of money is not considered as a significant factor for highway operations equip- ment. Using cost of money as a factor assumes that there are alternative uses for the replace- ment funds, such as investment. This is not a pragmatic assumption, primarily because there is no practical alternative use of the funds. Subsequently, the following three additional factors were identified as significant and rel- evant: â¢ Physical condition â¢ Mission criticality â¢ Overhead cost Not all of these factors are used to perform LCCA. For instance, equipment condition and mission criticality do not affect the economic analysis for equipment, but they are important factors in making equipment replacement decisions. The LCCA concept is illustrated in Figure 1. Performing LCCA for an individual unit of equipment can be helpful in making equipment replacement decisions; however, there are two practical limitations in the interpretation and application of a unit-level cost analysis. First, the point at which the unit reaches its economic life cannot be known until after the fact. Second, if annual cost data are not available for the unitâs early years, which is often the case, the analysis cannot be performed. Recognizing these limitations, the guide uses life-to-date (LTD) equipment history to compute averages for all units in a particular class. In effect, the approach models the life cycle cost of an average unit to determine optimal life cycles at the equipment class level. In real life, equipment cost trends rarely follow the stylized graphic depicted in Figure 1. Most often, the cost curves are erratic and require interpretation. The optimal life is seldom a point in time but is more appropriately considered as a window of time. Although LCCA concepts are fairly straightforward, the process for determining optimal life cycles and making replacement decisions is challenging, sometimes involving as much art as science. Making replacement decisions is a process. It combines cost analysis with CO ST P ER M IL E AGE Operating Cost Ownership Cost Total Cost Target Replacement Figure 1. Equipment LCCA concept.
6 other factors and considerations to arrive at the best decision. The process is time consum- ing and requires continual effort. Measuring asset conditions is a fundamental principle of asset management that applies to equipment assets in much the same way as infrastructure assets. Performing equipment condition assessments is an important step in an effective replacement process but has been largely ignored in practice. Recognizing its importance, the guide outlines recommended procedures for performing condition assessments, assigning mission criticality levels to equipment units, and incorporating the condition/criticality scores into the decision process. The optimization tool includes an Excel spreadsheet to support the condition assessments. The guide presents a systematic, 12-step process comprising the following major activities: â¢ Start with good quality data. Download data from the agencyâs equipment information systems. Clean up the data by correcting errors and eliminating units that do not have sufficient cost history to represent a valid cost trend. â¢ Make sure that there are enough units in the class to provide a statistically valid sample of units for the class-level LCCA. Perform the class-level LCCA to determine optimal life cycles. If there are not enough units to perform a class-level LCCA and if complete histori- cal data are available, a unit-level LCCA can analyze the costs of individual units. â¢ Identify replacement candidates based on a unitâs LTD miles, hours, or cost. â¢ Perform condition assessments on the candidate units and prioritize units for replace- ment based on mission criticality, condition, and cost analysis. â¢ Make final replacement decisions based on available replacement funding and other agency-specific factors and considerations. â¢ Develop a 5-year plan and analyze the cost consequences of various replacement scenarios to provide the fleet manager with information to make a business case for future funding levels. The Excel-based optimization tool performs LCCA and supports the annual equipment replacement process with analysis and outputs to assist in making replacement decisions. The tool is a set of spreadsheets with the following features: â¢ It provides a configuration file with preloaded replacement factors and default values that the user agency may choose to adopt or override with agency-specific values. â¢ It performs class-level LCCA to determine optimal life cycles for 40 major equipment classes. â¢ It performs unit-level LCCA to analyze the equipment cost of individual pieces of equipment. â¢ It identifies potential replacement candidates based on utilization and LTD cost derived from LCCA. â¢ It provides a spreadsheet for performing condition assessments and computes a condition score based on condition and mission criticality. â¢ It prioritizes equipment replacements by using a priority ranking system based on a unitâs LTD cost and condition. â¢ It develops a 5-year plan of future replacement needs and budgets based on the projected replacement year of individual equipment units. â¢ It analyzes cost consequences of various equipment replacement cycles. The accompanying tool user manual provides step-by-step instructions for using the optimization tool. Although the project achieved its objectives, more effort is needed to make equipment replacement easier and provide more reliable cost analysis results.
7 The project research identified data quality as a major concern. An effort should be made to develop standards or guidelines for reporting and tracking equipment main- tenance and repair cost. The guidelines should incorporate recommended data quality control procedures. Excel was chosen for development of the optimization tool because of its ready availabil- ity. The Excel-based tool provided the appropriate features to support equipment replace- ment. However, the toolâs functionality could be enhanced with more robust software that would make the tool more user-friendly. Guidelines should be developed for determining the true cost of mechanic labor rates. Prevailing practices fail to account fully for direct and indirect overhead expenses, and equipment operating costs are being understated. Guidelines should also be developed for measuring, reporting, and tracking equipment downtime. It appears that most agencies do not currently track downtime, resulting in the true cost of equipment operations being understated. The guide developed in this project addresses all of these concerns and provides guidelines and recommended procedures for cleaning up data, reporting maintenance cost, account- ing for overhead expenses, and tracking downtime. The guidelines contained in the guide should be considered as starting points for future refinement with the goal of achieving more standardized practices. User training is necessary when any new software system is implemented in an agency. Such is the case with the equipment replacement processes and optimization tool contained in Parts II and III. Implementation of the tool will require training to understand the recom- mended processes supported by the tool and how to apply the tool in performing LCCA and making effective replacement decisions. System training is a normal and important step for successful system implementation. Also, ongoing system support will be required and is a natural step in the implementa- tion and ongoing use of the tool. An organization such as AASHTO is most likely the best organization to provide the ongoing support.