DIFFICULTIES IN FLEET MANAGEMENT: INTANGIBLE FACTORS, INFORMATION OVERLOAD, AND DATA INTEGRITY

摘要

This research with the Minnesota Department of Transportation (Mn/DOT) focuses on optimizing fleet maintenance and operation. A nationwide benchmarking study of performance measures used by transportation departments led to a life cycle costing model for snowplows and other assets. Currently, feasibility of automating data acquisition from fleet assets is under investigation. Throughout these projects, difficulties arise from intangible factors, too much data, and bad data. Intangible factors play a substantial role in asset utilization and data reporting; these frequently deal with how a person feels about a particular asset or characteristic. Mn/DOT collects a huge amount of data, which leads to information overload. Because some data are manually collected and some personnel view data collection as a useless chore, much data are erroneous or incomplete, making analysis more difficult. This paper details these issues and offers strategies for coping, which can then be used for fleet management and any system.