Utilization Measurement and Management of Fleet Equipment (2021)

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Guide for Utilization Measurement and Management of Fleet Equipment P A R T I I

C O N T E N T S 33 Chapter 1 Introduction and Purpose 34 Chapter 2 Organization of the Guide 35 Chapter 3 Equipment Classification 37 Chapter 4 Utilization Estimation Factors 37 4.1 Utilization Measurement Metrics 37 4.2 Factors Contributing to Equipment Utilization 38 Chapter 5 Asset Utilization Measurement 38 5.1 Equipment Cost Estimation Models 41 Chapter 6 Equipment Utilization Management Framework 41 6.1 Area-Level Utilization Management 42 6.2 Region-Level Utilization Management 42 6.3 Unit-Level Utilization Management 43 Chapter 7 Equipment Utilization Management Process

33 Introduction and Purpose This guide for utilization measurement and management of fleet equipment discusses (1) data input requirements, (2) utilization measurement models, and (3) a framework for utilization management. The equipment utilization measurement models were developed through rigorous statistical analyses of data obtained from state DOTs to estimate equipment utilization and cost as functions of a set of contributing factors (e.g., fleet size and demand). The management framework uses statistical models and cost functions to determine the optimal equipment utili- zation level, fleet size, and number of equipment fleet units to be purchased/salvaged/relocated in each region. These models were developed for different equipment types and embedded in a software application for utilization predic- tion and management (UPM). The UPM software allows the user to estimate equipment utilization and manage the fleet at a region-level based on available measurable infor- mation. The UPM software identifies individual equipment that is under- or overutilized, needs to be salvaged, or needs to be relocated. The UPM software also helps identify the fleet management strategy that minimizes the total fleet management costs. This guide describes (1) the general methodology for utili- zation measurement and management and (2) the process that should be followed to estimate equipment utilization, find the optimal utilization thresholds for different equip- ment types using the UPM software, and determine under- and overutilized individual equipment and adjust their level of utilization accordingly. In general, the guide helps (1) estimate equipment utili- zation; (2) find the optimal utilization level, fleet size, and number of equipment units to be purchased, salvaged, or relocated in states, counties, and regions; and (3) identify over- or underutilized equipment units. C H A P T E R 1

34 This guide is designed to facilitate use of the UPM software and the interpretation of its output. Chapter 3 of the guide describes equipment types and classifications within each type based on the National Asso- ciation of Fleet Administrators (NAFA) classification system. It also identifies equipment types that are included in the UPM software. Chapter 4 presents the utilization measure- ment metrics and their contributing factors. Chapter 5 details utilization measurement models for each equipment type and the relationships between equipment operational cost, utilization level, and fleet size. Chapter 6 clarifies the role of the mathematical optimization framework in opti- mizing the utilization. Chapter 7 provides a general frame- work for using the UPM software. C H A P T E R 2 Organization of the Guide

35 Equipment Classification The utilization measurement and management framework provides the capability to manage certain fleet equipment types and classes. This guide adopts the NAFA classification system to provide a standardized definition that can be used by different entities. The guide considers 19 equipment types: dump trucks, pickup trucks, automobiles, vans, sport utility vehicles, trailers, front loader trucks, graders, mechanical street sweeper trucks, air street sweeper trucks, riding mowers, truck tractors, snow removal attachments, rollers, drills, asphalt distributors, attachments, man lifts, and large trucks with a special body. Some of these equipment types have several classes based on their weight or their purpose of use; therefore, each type and class of equipment may contain several NAFA codes (see Table 1). Dump trucks, pickup trucks, automobiles, vans, sport utility vehicles, front loader trucks, mechanical street sweeper trucks, air street sweeper trucks, truck tractors, and asphalt distributors are classified solely based on their gross vehicle weight (GVW). Trailers, graders, riding mowers, snow removal attachments, rollers, drills, attachments, man lifts, and large trucks with a special body are classified based on their use. C H A P T E R 3 # Equipment Class NAFA Class Code 1 Dump Truck 8,501-10,000 GVW 2712 10,001-14,000 GVW 3712 14,001-16,000 GVW 4712 16,001-19,500 GVW 5712 19,501-26,000 GVW 6712 26,001-33,000 GVW 7712 > 33,000 GVW 8712 2 Pickup Truck < 8,500 GVW 1510, 1511, 1512, 1513, 1514, 1520, 1521, 1522, 1523, 1524, 1530, 1531, 1532, 1533, 1534, 1540, 1547, 1548 10,001-14,000 GVW 3510, 3511, 3512, 3513, 3514, 3540, 3547, 3548 14,001-16,000 GVW 4510, 4511, 4512, 4513, 4514, 4520, 4527, 4528 8,501-10,000 GVW 2510, 2511, 2512, 2513, 2514, 2540, 2547, 2548 3 Automobile < 8,500 GVW 1310, 1311, 1312, 1313, 1320, 1321, 1322, 1323, 1324, 1330, 1331, 1332, 1333, 1338, 1340, 1341, 1342, 1343, 1348 4 Van < 8,500 GVW 1410, 1411, 1412, 1413, 1414, 1418, 1420, 1421, 1422, 1423, 1424, 1425, 1426, 1427, 1428 10,001-14,000 GVW 3410, 3411, 3412, 3413, 3414, 3420, 3421, 3422, 3423, 3424, 3425, 3426, 3427, 3429 4410, 4411, 4412, 4413, 4414, 4420, 4421, 4422, 4423, 4424, 4425, 4426, 4427, 4429 16,001-19,500 GVW 5420, 5421, 5422, 5423, 5424, 5425, 5426, 5427, 5428, 5429 19,501-26,000 GVW 6420, 6421, 6422, 6423, 6424, 6425, 6426, 6427, 6428, 6429 8,501-10,000 GVW 2410, 2411, 2412, 2413, 2414, 2420, 2421, 2422, 2423, 2424, 2425, 2426, 2427, 2429 5 Sport Utility <8,500 GVW 1610, 1611, 1612, 1620, 1621, 1622, 1623, 1630, 1631, 1632, 1633, 1634, 1640, 1647, 1648 10,001-14,000 GVW 3610, 3611, 3612, 3613, 3614, 3640, 3647, 3648 8,501-10,000 GVW 2610, 2611, 2612, 2613, 2614, 2640, 2647, 2648 14,001-16,000 GVW Table 1. Equipment classification. (continued on next page)

# Equipment Class NAFA Class Code 14 Roller Static 9441 Vibratory 9442 Compactor 9443 15 Drill Off-Road and Construction 9530 16 Asphalt Distributor 16,001-19,500 GVW 5778 19,501-26,000 GVW 6778 26,001-33,000 GVW 7778 > 33,000 GVW 8778 17 Attachment Spreader 0121 Aerator 0122 Soil Preparation 0123 Planter 124 Shredder/Mulcher 125 Mower 126 Bucket 131 Backhoe 132 Breaker 133 Tamper 134 18 Man Lift Off-Road and Construction 9330 19 Large Truck with Special Body Beverage Body 2716, 3715, 4715, 5715, 6715, 7715, 8715 Crew Cab 4513 Extended Cab 4512 Fifth Wheel 4718, 5718, 6718, 7718, 8718 Flat Bed 2711, 3711, 4711, 5711, 6711, 7711, 8711 Refrigerator Body 2717, 3716, 4716, 5716, 6716, 7716, 8716 Regular Cab 4511 Tanker 2718, 3717, 4717, 5717, 6717, 7717, 8717 Tilt Bed 2714 Utility Bed 2713, 3713, 4514, 4713, 5713, 6713, 7713, 8713 Van Body 2715, 3714, 4714, 5714, 6714, 7714, 8714 6 Trailer Air Compressor 320, 321, 322, 323 Auxiliary Power 390, 397, 398, 399 Boat 780, 781, 782, 783 Concrete Mixer 380, 381, 382, 383 Construction 0360 Dump Body 750, 751, 752, 753 Flat Bed 710, 711, 712, 713 Generator 310, 311, 312, 313, 314, 315, 316, 317, 318 Office 790, 791, 792, 793 Pressure Washer 340 Public Utility 350, 351 Pump 330, 331, 332, 333, 334 Refrigerator 760, 761, 762, 763 Sanitation 770, 771, 772, 773 Sewer Equipment 370, 371, 372, 373, 374 Tank Body 730, 731, 732, 733 Tilt Bed 720, 721, 722, 723 Van Body 740, 741, 742, 743 7 Front Loader 16,001-19,500 GVW 5763 19,501-26,000 GVW 6763 26,001-33,000 GVW 7763 > 33,000 GVW 8763 8 Grader Off-Road and Construction 9160 9 16,001-19,500 GVW 5771 19,501-26,000 GVW 6771Mechanical Street Sweeper Truck 26,001-33,000 GVW 7771 > 33,000 GVW 8771 10 Air Street Sweeper Truck 16,001-19,500 GVW 5772 19,501-26,000 GVW 6772 26,001-33,000 GVW 7772 > 33,000 GVW 8772 11 Riding Mower Off-Road and Construction 9610, 9611, 9612 12 Truck Tractor 19,501-26,000 GVW 6810, 6820, 6830, 6840, 6890 26,001-33,000 GVW 7810, 7820, 7830, 7840, 7890 > 33,000 GVW 8810, 8820, 8830, 8840, 8890 13 Snow Removal Attachment Nose Plows 111 V Plows 112 Wing Plows 113 Underbody Plows 114 De-icer Equipment 115 Snow Blowers 116 Material Spreaders 117 Table 1. (Continued).

37 Utilization Estimation Factors This chapter introduces the utilization measurement metrics and describes the factors that are important to the utilization estimation of fleet equipment. 4.1 Utilization Measurement Metrics Annual mileage, annual engine hours, usage over the last 12 months, and frequency of use are the utilization metrics most widely used by state DOTs. While annual mileage can only be used for moving equipment and annual engine hours can be used for equipment that has an engine, other measure- ment metrics can be used for all types of equipment. A recent survey performed as part of this project indicated that 72% of state DOTs use “driven miles” as a utilization metric. The survey results also indicated that state DOTs believe that mileage metering is accurate, is easy to report, indicates actual usage, makes replacement predictable, and is consis- tent across various classes of an equipment type, but it does not report unit conditions and is hard to collect in equip- ment without an odometer. Therefore, “annual mileage” is used as the utilization metric for moving equipment with an odometer. The survey also indicated that 62.5% of respondents use “equipment age” and “engine hours” to measure utilization. The respondents also noted that engine hours can provide the actual utilization of equipment and is easy to use, but it does not report unit conditions and is confusing to collect for equipment with two engines. Therefore, “engine hours” and “frequency of use” are used as the utilization metrics for stationary equipment with an engine and stationary equip- ment without an engine, respectively. 4.2 Factors Contributing to Equipment Utilization Factors that contribute to equipment utilization in a region were identified based on the review of the literature, the agency survey, and statistical modeling results. These factors are: • In-service age, • Fleet size in a region, • Annual downtime hours, and • Cost factors (purchase cost, annual maintenance cost, and annual unscheduled repair cost). C H A P T E R 4

38 The UPM software estimates either average annual mileage, annual engine hours, or frequency of usage for each equip- ment type and class at a region-level based on the data pro- vided by the user for the equipment types and classes listed in Table 1. The factors contributing to region-level utilization and their definitions are listed in Table 2. Data for these factors are required for each equipment type in order to estimate the annual mileage. Table 3 lists the models developed and validated in this research for the equipment types listed in Table 1. 5.1 Equipment Cost Estimation Models In addition to the utilization estimation models, models to estimate the annual operating cost of the 19 equipment types are required to provide a relationship between the average operational cost of an equipment type, average utili zation, and fleet size. The annual operating cost func- tion (xOC) is defined as the summation of annual fuel cost, unscheduled repair cost, and scheduled maintenance cost; it is influenced by (a) annual mileage, (b) annual downtime hours, (c) in-service age, (d) fleet size in a region, and (e) class of equipment. Table 4 lists the cost functions (the variables are explained in Table 2). C H A P T E R 5 Asset Utilization Measurement Factor Description : Annual Mileage Average annual mileage in a region : Annual Engine Hours Average annual engine hours in a region : Frequency of Usage Average frequency of usage in a region : Purchase Cost ($1,000) Average equipment purchase cost in a region : Annual Downtime Hours Average equipment annual downtime hours in a region : Annual Scheduled Maintenance Cost ($1,000) Average equipment annual scheduled maintenance cost in a region : Annual Unscheduled Repair Cost ($1,000) Average equipment annual unscheduled repair cost in a region : In-Service Age Average equipment in-service age in a region Fleet Size Average fleet size in a region Class 1: if the equipment is in class based on the NAFA class code Table 2. Parameters in utilization models.

39 Equipment Type Utilization Metric Utilization Estimation Model Dump Truck Annual Mileage log( ) = 9.321 + 0.238 log( ) − 0.635 log( ) + 0.129 log( ⁄ ) − 0.503 ( 5 + 6 + 7 ) Pickup Truck Annual Mileage log( ) = 7.081 + 0.461 log( ) − 0.153 ( )0.5 + 0.275 log( ⁄ ) + 0.237 log( ) − 0.024 ( )0.5 − 0.049 2 − 0.144 3 − 0.464 4 Automobile Annual Mileage log( ) = 9.119 + 0.256 + 0.0781 log( ) − 0.147 log( ) Van Annual Mileage log( ) = 9.256 − 0.111 + 0.103 log( ⁄ ) + 0.188 log( ) − 0.002 + 0.289 ( 5 + 6 ) Sport Utility Vehicle Annual Mileage log( ) = 10.222 − 0.461 log( ) + 0.248 log( ) − 0.002 Trailer Annual Mileage log( ) = 5.349 + 0.814 log( ) − 0.003 ( )2 + 0.663 log( ) + 0.481 log( ) − 0.009 Frequency of Usage = 135.65 + 1.365 + 18.073 log( ) − 125.681 12 + 61.966 14 + 46.051 17 Front Loader Truck Annual Mileage log( ) = 5.590 − 0.004 ( ) 2 + 0.786 ( 3 + 4 ) Grader Annual Mileage log( ) = 6.710 − 0.861 log( ) + 0.493 log( ) + 0.905 log( ) Engine Hours log( ) = 7.619 + 0.505 log( ) + 1.113 log( ) − 0.455 log( ) Mechanical Sweeper Truck Annual Mileage log( ) = 12.985 − 1.812 log( ) + 0.343 log( ⁄ ) − 0.470 log( ) − 0.096 log( ) + 0.973 4 Engine Hours log( ) = 6.291 − 0.220 + 0.541 log( ) + 0.416 log( ) Air Street Sweeper Truck Annual Mileage log( ) = 12.985 − 1.812 log( ) + 0.343 log( ⁄ ) − 0.470 log( ) − 0.096 log( ) + 0.973 4 Engine Hours log( ) = 6.291 − 0.220 + 0.541 log( ) + 0.416 log( ) Riding Mower Annual Mileage log( ) = 4.445 + 0.222 log( ) + 0.440 log( ) Frequency of Usage log( ) = −0.921 + 0.512 log( ) − 0.042 − 0.441 + 1.384 log( ) Truck Tractor Annual Mileage log( ) = 10.014 − 0.004 ( × 10−1)2 − 0.810 log( ) + 0.061 + 1.064 3 Snow Removal Attachment Annual Mileage log( ) = −0.674 + 1.042 log( ) + 0.095 ( ⁄ ) − 0.015 Roller Annual Mileage log( ) = 4.399 + 1.095 log( ) − 1.148 log( ) + 1.072 log( ) − 0.872 2 + 0.624 3 Engine Hours log( ) = 4.196 + 10.235 ( )−2 − 0.004 − 0.806 log( ) log( ) + 2.084 2 Frequency of Usage log( ) = 129.893 + 0.316 ( ⁄ ) 2+107.621 3 Drill Annual Mileage log( ) = 4.079 + 0.008 + 0.163 − 0.153 ( ) 0.5 Engine Hours = 26.481 + 16.841 ( ⁄ ) Asphalt Distributor Annual Mileage log( ) = 22.406 − 2.417 log( ) − 0.476 log( ) − 0.005 ( )2 − 3.527 ( )2 Attachment Annual Mileage log( ) = 5.056 + 0.354 log( ) − 0.127 ( ) 0.5−1.031 2 Man Lift Annual Mileage log( ) = 4.101 + 0.938 log( ) + 0.317 − 0.167 ( ) 0.5 Engine Hours log( ) = 7.766 − 0.031 ( ) 2 + 1.653 − 0.754 log( ) Large Truck with Special Body nnual A Mileage log( ) = 9.712 − 0.080 + 0.158 log( ) − 9.27 ( × 10−3)2 + 0.284 2 − 0.296 5 − 1.032 8 − 0.278 11 Table 3. Equipment utilization estimation models.

40 + Equipment Type Operating Cost Estimation Model Dump Trucks = 12.3 × 10−9 ( ) (2( )2 − 27.244 + 6262.58 1 2 + 3 + 4 ) + 14161.67 5 + 13891.45 ( 6 + 7 ) Pickup Trucks = 0.174 − 0.018 + 2719.20 ( 1 + 2 ) + 3442.98 ( 3 + 4 ) Automobiles = 0.14 − 3.90 + 699.72 ( )0.5 − 0.73 ( )0.5 Vans = 0.36 − 3.85 + 145.84 Sport Utility Vehicles = 0.24 − 1115.04 log( ) + 2679.59 log( ) − 3.99 Trailers = 0.002 ( )2 + 1300.84 1 + 2264.87 3 + 1286.74 5 + 399.71 6 + 1420.31 7 + 718.24 8 + 7828.37 9 + 873.75 10 + 1383.05 11 + 1315.92 12 + 2005.43 14 + 1699.40 16 + 633.10 17 Front Loader Trucks = 0.048 ( ) 2 + 2818.14 1 + 2 + 8296.82 ( 3 + 4 )( ) Graders = 359.76 ( ⁄ ) − 21.43 Mechanical/ Air Street Sweeper Trucks = 19.87 + 51.72 ( )2 Riding Mowers = 2.87 − 8274.57 ( ⁄ ) Truck Tractors = 0.92 − 25.349 + 3093.94 2 + 6933.45 3 Snow Removal Attachments = 11.4 × 10 −5 ( 2 )⁄ − 1505.08 ( 2 )⁄ + 8266.77 1 + 3007.77 6 Rollers = 3.29 ( ⁄ ) + 0.72 + 408.59 log( ) Drills = 10.75 log( ) − 961.32 Asphalt Distributors = 13.20 ( ) + 3704.04 ( 2 )⁄⁄ Man Lifts = 8.82 log( ) + 45.51 Large Trucks with Special Body = 0.32 − 229.44 ( )2 + 1151.60 log( ) − 53.64 + 20.15 log( ) + 3696.48 5 + 3006.28 8 + 6582.92 11 Table 4. Summary of equipment operating cost estimation models.

41 Equipment Utilization Management Framework Optimal fleet size and utilization level in a region minimize the total fleet management costs while meeting available budget, maximum utilization thresholds, and demand con- straints. A mathematical program is required to account for these constraints, find the optimal fleet size and utilization level in each region, and determine how to achieve these opti- mal sizes and levels by purchasing, salvaging, and relocating equipment assets while minimizing total fleet management costs. This chapter describes the details of such a program. The fleet utilization management program determines optimal (a) fleet size in each region in a year, (b) the number of equipment units to be purchased in each region in a year, (c) the number of equipment units to be salvaged in each region in a year, (d) the number of equipment units to be relocated from a region to another, and (e) average utiliza- tion level required to meet the demand for an equipment unit in each region in a year. Utilization optimization of each equipment type is performed separately. The program finds the lowest total fleet utilization management costs, including capital, operating, and maintenance costs. The objective function of the mathematical program formulates three cost items: 1. The costs of keeping an asset in service using the predic- tive annual operating cost functions obtained from esti- mation models. These costs consider the effect of fleet size and utilization metrics (e.g., mileage) on equipment operating costs in each region for the various inputs (e.g., annual downtime hours, in-service age, and equip- ment class). 2. The cost of adding new equipment to the fleet in a region in the following year (by multiplying the purchase cost by the number of equipment units purchased). 3. The relocation cost considering the distances between regions and the transportation cost rates. The users have the capability of defining regions and providing either distances, transportation cost per mile, or actual transportation costs between them. Also, the cost function does not consider salvaging equipment to avoid salvaging too many equipment assets to make income. The program updates the fleet size in each region in the following year considering the number of purchased equipment units, “brought-in” or “sent-out” equipment from/to other regions, and salvaged equipment, and ensures that: 1. The number of equipment units leaving each region to other regions in the following year does not exceed the number currently available in that region; 2. The demand will be met by having sufficient fleet size in the following year (i.e., the product of fleet size and average utilization of each equipment type in each region in the following year shall be equal to or greater than the total demand); 3. No equipment unit will be utilized in excess of its maxi- mum allowed utilization level; and 4. The number of purchased, salvaged, and relocated equip- ment units will not be less than zero for the following year. The results of the equipment utilization management framework are used at three levels: analysis area-, region-, and unit-level. More details follow. 6.1 Area-Level Utilization Management The fleet utilization management program allows users to determine the optimal fleet size, utilization level, and number of equipment units to be purchased, salvaged, and relocated. The optimal area-level utilization values are expected to vary within the analysis area from one region to another, but they can be used to provide a high-level reference point for optimal usage. The area-level values are determined by post-processing the outcome of the region-level analyses (by averaging the optimal region-level utilization levels), and C H A P T E R 6

42 a weighted average (based on the fleet size in each region) is calculated. The optimal area-level fleet size is the summation of region-level fleet sizes. The number of equipment units to be purchased, salvaged, and relocated are determined similarly. 6.2 Region-Level Utilization Management The UPM software determines the optimal fleet size and utilization level in each region (and how to achieve them). The software also determines if the equipment units in a region, in general, are over- or underutilized. The software reports overutilization and underutilization if the average utilization is at least 20% more or less than the optimal utili- zation level, respectively; these thresholds are inputs that can be changed in the software. Generally, the program will direct a region having underutilized equipment to send out its fleet to regions that have overutilized equipment to balance the utilization throughout the analysis area. 6.3 Unit-Level Utilization Management The UPM software compares the actual annual mileage of individual equipment units to the optimal analysis area- level and region-level utilization thresholds. As a result, a state DOT, for example, can detect individual under- or overutilized equipment units and make plans to adjust their utilization. The software also reports specific unit ID for equipment that should be relocated or salvaged. Equipment with the lowest utilization levels is sent to other regions if a region has to send out any equipment. The software reports equipment with highest in-service age if a region needs to salvage equipment. However, state DOTs need to consider operational conditions of equipment in making relocation and salvage decisions, as the UPM assumes that the operational conditions are a function of equipment age for salvage decisions and does not consider poor opera- tional conditions.

43 Equipment Utilization Management Process Figure 1 shows the general process for fleet UPM. This process heavily depends on equipment input data, and users need to provide accurate data regarding fleet equipment current utilization, costs, and other characteristics. The data need to exactly follow a predefined format so that it can be used by the UPM software for equipment utilization estima- tion and management. The process consists of eight steps; these are described below. Step 1: Define the Analysis Area Before managing the utilization plans, users need to define the desired analysis area (e.g., State of California or City of Raleigh). Step 2: Update the Distance Matrix It is very likely that equipment needs to be relocated among different regions of an analysis area to optimize the utilization and meet the demand. The equipment reloca- tion cost highly depends on the distance and unit transpor- tation cost per mile between regions. The users need to fill out two Excel files for distance and transportation cost per mile between every two regions in an analysis area and load them in the software. The software calculates total trans- portation cost by multiplying the distance, transportation cost, and the number of equipment assets. If transporta- tion cost per asset between two regions is known, the user can enter a value of one in the distance matrix and the cost value in the other matrix. Also, the name of regions must match those shown in the equipment utilization input file. Step 3: Import the Data In this step, users need to import equipment-level utili- zation data into the UPM software. Each row of data deals with an individual equipment unit and includes data on its unit ID, NAFA code, equipment group, equipment class, user-defined classification code, user-defined equipment description, report year, region, in-service age, purchase cost, annual fuel cost, annual maintenance cost, annual unscheduled repair cost, annual downtime hours, annual engine hours, annual mileage, and frequency of usage. The fleet size (i.e., the number of units within the same class in the same region) is also required. Users can input data in UPM either manually or automatically. A template Excel sheet is provided to facilitate preparing the input data. Figure 2 shows the required layout (i.e., specific columns with their names and order). The entry data MUST exactly follow the format shown in Figure 2 for the software to work properly (the UPM aggregates the data and creates region-level data). The required information on each equipment unit must be presented in one row in the following order: A. Unit ID: Identifies the specific unit ID that does not change over time. The input should be a number or a set of characters. B. NAFA class code: Identifies each fleet equipment type and class. The input should be an integer based on the NAFA equipment classification system. C. Equipment group: Identifies the group type of each equipment unit (e.g., sedan, trailer, or truck). This is an informative column and can have any character. D. Equipment class: Identifies equipment classification based on the GVW and functionality. This is an infor- mative column and can have any character. E. User-defined classification code: Identifies each fleet equipment type based on a user-defined classification. This input is optional and can be in numeric or text formats. F. User-defined equipment description: Provides a user- defined description of each equipment unit. This input is optional and can be in numeric or text format. G. Report year: Indicates the year of the provided infor- mation. The input should be an integer. H. Region: Shows the region where the equipment is located in the report year. Each word in the region name should start with a capital letter (e.g., Los Angeles, Whitman, Walla Walla). C H A P T E R 7

44 Figure 1. Utilization measurement and management process. Figure 2. Input data layout.

45 I. In-service age: Shows the years an equipment unit is being operated. The input should be a real number. J. Purchase cost: Shows the purchase cost at the time of buying the equipment. The input should be a real number. K. Fleet size: Indicates the number of available equipment assets with the same NAFA class code in the fleet in a region in the report year. The input should be an integer. L. Annual fuel cost: Represents the fuel cost of an equip- ment unit in the report year. The input should be a real number. M. Annual scheduled maintenance cost: Shows the total scheduled maintenance cost for an equipment unit in the report year. The input should be a real number. N. Annual unscheduled repair cost: Represents the total unscheduled repair cost for an equipment unit in the report year. The input should be a real number. O. Annual downtime hours: Shows the inoperative hours of an equipment unit in the report year. The input should be a real number. P. Annual engine hours: Represents the engine hours of an equipment unit in the report year. The input should be a real number. Q. Annual mileage: Represents the miles driven of an equipment unit in the report year. The input should be a real number. R. Frequency of usage: Represents the number of days in a year an equipment unit is used. The input should be a real number. Step 4: Estimate the Utilization The UPM software estimates the utilization of each equipment type and class. Users need to enter the NAFA class code of the desired equipment (it should be among the codes provided in Table 1). In addition, users need to enter the analysis year that utilization is being estimated for. After defining the equipment class and analysis year, the software estimates the utilization based on the models shown in Table 3. The software extracts values for the different variables from the imported data and estimates the annual mileage, annual engine hours, or frequency of usage for the desired equipment class and analysis year. Step 5: Analyze Utilization Metric Sensitivity to its Contributing Factors After estimating the desired utilization metric, users can perform sensitivity analyses on any of the variables that contribute to the equipment utilization. This will allow the users to understand the association between each variable and the proper utilization metric that helps design more effective fleet utilization management scenarios. For instance, users can see the relationship between changing fleet size in a region and the annual mileage. Step 6: Input Optimization Parameters Users need to enter equipment NAFA class code and analysis year. The optimization framework requires data on the annual demand, purchase cost, maximum allowed utili zation, and transportation cost per mile per equip- ment to run the mathematical program (these parameters are region-based average values, and the software provides default values for them that can be changed by the user). The default value for demand in a year is the average annual mileage or annual engine hours in the current year. This means that the demand level does not change if there is no good estimation for it. The default value for the purchase cost is found the same way. The maximum utilization threshold is equal to the average of the top 15 percent observed utilization in the previous year. The software provides a value of $1.00 as the default value for the transportation cost. How ever, users are encouraged to enter appropriate values for these parameters and only use the default values in the absence of more appropriate estimations. Step 7: Manage Fleet Utilization In this step, the software solves the optimization problem and estimates the optimal utilization level, fleet size, and number of purchased/salvaged/relocated equipment units in each region based on the input data; users can record the outcome in an Excel file. The software provides a total fleet management cost for do-nothing and optimal sce- narios. However, the do-nothing scenarios may lead to infeasibility (i.e., the demand may not be met or the maxi- mum utilization threshold may be violated). The software marks infeasible solutions in red. For a do-nothing infea- sible scenario, a total cost may be less than the optimal cost. Step 8: Analyze User-Defined Scenarios Users can define scenarios and study their effects on fleet utilization management. After selecting the equip- ment class and analysis year, users can load the predefined scenarios (in an Excel file) in the software. The software provides fleet utilization management costs for that scenario and specifies its feasibility. The user can generate reports on defined scenarios and compare a set of scenarios.