Computer-aided school bus routing

Bus transportation is a large expense for many school districts. Reducing this cost is the objective of the Transportation Information Management System (TIMS), which all 133 school districts in North Carolina use. This personal computer-based decision support system (DSS) lets local school districts create efficient routes and schedules for their school buses.

TIMS has four modules: (1) geocoding, which digitizes the school district's street network maps; (2) transportation, which maintains all routing and scheduling information, including the location of each student; (3) optimization, which tries to identify the least costly bus routes and schedules and enables administrators to perform "what if?" analyses; and (4) boundary planning, which provides demographic data on students.

TIMS's data base contains information on the district's streets and roads, bus travel speed, student locations, bus stops, bus runs, and bus routes. The models are designed to determine how to reduce the time and distance of all bus runs based on the capacity of each bus. In tests in the Randolph County school district, TIMS reduced school bus mileage by 6 percent and was instrumental in reassigning or parking nine buses.

A widely used spin-off of the primary purpose of TIMS is the boundary planning module. This module allows administrators to plan school attendance districts based on student location information stored in the TIMS data base. It provides administrators with precise information about number of students, racial makeup of the student population, and distribution of students across grades for analyzing existing, new, or proposed attendance boundaries.

Smart workers for smart machines

A decade ago many workers worried that they would be replaced by robots and computerized manufacturing equipment. However, in some cases exactly the opposite has occurred— workers not only have not been replaced by machines but many have found that their jobs have been made more meaningful by the introduction of smart machines. This has come about because workers are being given more responsibility and authority to deal with problems or to make production-line decisions that were once reserved for supervisory personnel. Workers do more than just run machines; they spend large parts of their time collecting and processing data on quality control, inventory, and shipments. The result of this change is an information factory, where machines not only perform some operations, but they supply workers with information on processing operations.

As an example of this type of change, consider General Electric's Salisbury, North Carolina, factory. At this plant, which is highly automated, it was decided in 1984 to cut factory floor bottlenecks by giving workers the information and power to make decisions to keep the manufacturing process running. A machine operator with a problem, for example, now can talk directly to manufacturing engineers about solutions to the problem or can order parts for the machine without prior approval of management. Workers also serve on committees to hire new workers in the plant.

From 1985 through 1988, General Electric's pairing of smart workers with smart machines resulted in a tenfold decrease in delivery time, a reduction in employee turnover, a reduction by two-thirds in the number of hours per production unit, and an increase in General Electric's market share. Since 1988, concrete figures have not been available on the effect of these measures; however, plant management believes that the workers are continuing to assume more and more responsibility for running the plant. Each year, they have exceeded production goals and reduced production cost.