【正文】 e cycle of the third operation was performed and is therefore of little importance). Five loads were hauled approximately 800 m between 10:20 and 11:30 in the first operation, and a second hauling operation hauled 36 loads a distance of approximately 100 m between 10:30 and 20:20.Therefore, 2 load and haul operations consisting of 4 activities (load, haul, dump, and return) each were identified from the preliminary review. The activitynaming convention adopted for this work is the activity name followed by the associated areas. For example, loading in area 3 is labeled Load 3, while hauling from load area 1 to dump area 2 is labeled Haul 12. The TIMs were applied to the data to identify the beginning and end times for each of the identified activities.The dump activities occur in fixed locations and with zero velocity, and therefore the ADTIM was used to identify the records key to those activities. The ADTIM areas to be applied to the data are shown in Fig. 5. The user can determine the central coordinates and radial distance of each ADTIM area from the plan view of the recorded data. Once the input data are provided,the ADTIM is executed and the results are placed on an ADTIM sheet. A portion of the ADTIM results for the Dump 2 activity are provided in Table 2.The results obtained should be pared with the preliminary review results to verify the ADTIM process and ensure that the total instances and time frame of the associated activities concur with the results of the preliminary review. A total of approximately 18,850 data records were collected and analyzed. The set of records where velocity equaled zero numbered approximately 13,900, a reduction of approximately 25%. Further reduction by ADTIM identified 90 key records that mark the start and end of activities. These 90 records represent less than % of the total records collected, and thus the collected data were reduced by more than %.The EXTIM was used to identify the records key to the load activities because the area in which the truck was loaded changed over time. The data file recorded on the loader was used with a critical distance of 20 m. This distance was selected based on previous experience with data from the same or similar operations.It is also necessary to review the EXTIM results to identify and eliminate any extraneous results. Such results can be produced by actions occuring outside of time frames identified during data evaluation and by trucks queuing at the loader at a distance less than the specified critical distance. Results outside an operational time frame are easily identified。 those produced by queuing can be identified as those preceding another result at approximate same time.EXTIM identified 150 records that marked the start and stop of the load activities. Further review and reduction by the user of the identified records resulted in 84 key records. This level of reduction from 18,850 to 84 records is very similar to that of the ADTIM and represents a greater than % reduction.FBTIM was used to identify the records key to the haul and return activities. The duration of the haul and return activities can be characterized as the time required for the truck to travel through or between FBTIM areas. For purposes of illustration, the FBTIM areas will be applied in both manners and are presented in Fig. 6. The truck traveled through boundary number 1 during thefirst operation and between boundaries 2 and 3 during the second operation.Further manual reduction of the data resulting from the TIMs may be necessary to produce a set of critical records. Overlapping areas can be defined for the FBTIM and produce results that are both accurate and useful. It is important to understand that the results produced may also overlap, and the appropriate overlapping results should be neglected.Data reduction by FBTIM reduced the number of records from 18,850 to 202. Further review and reduction by the user resulted in the identification of 164 key records that mark the start and stop of activities. These 164 records represent less than 1% of the total number of data records collected。 the data were reduced by more than 99%.Data AnalysisThe results produced can be used to calculate the collection of durations for each activity over the workday. These collections of durations can be used to provide insight into both the activity and the parent operation as a whole. They can also be used to develop bestfit statistical functions for use in puter simulation and modeling techniques. The Dump 2 activity results will be used to demonstrate data analysis, and a portion of these results are presented in Table 2.Graphical representations of data are more meaningful than collections of numbers in a table. A histogram of the durations can indicate the shape of the statistical distribution underlying the duration data and is presented in Fig. 7. The histogram shows that the majority of durations were between 6 and 12 min, with some observations much shorter in duration. Six minutes are not required to raise the dump body and dump the load, and it can be seen from Table 2 that the dump activity can be pleted in less than 1 min. This indicates that the truck is not the constrainingequipment in the Dump 2 activity and that the duration is often many times greater than necessary.The collection of activity durations can be further used to determine statistical functions that fit the sample data within statistical limits. The Stat?Fit program is a statistical analysis software package that accepts the sample data as input, estimates the parameters of several potentially fitting statistical functions, evaluates the appropriateness of the function through goodnessoffittests, and provides a remendation to the user regarding each function.Modeling and simulation techniques can be used to analyze construction operations, using stochastic definitions of activity durations as input. To determine the duration of e