The term "automated guided vehicle" (AGV) is a general one that encompasses all transport systems capable of functioning without driver operation. The term "driverless" is often used in the context of automated guided vehicles to describe industrial trucks, used primarily in manufacturing and distribution settings, that would conventionally have been driver-operated.

Since their introduction in 1955, automated guided vehicles have found widespread industrial applications. AGVs are now found in all types of industries, with the only restrictions on their use mainly resulting from the dimensions of the goods to be transported or spatial considerations. Many applications of AGVs are technically feasible, but the purchase and implementation of such systems is usually based on economic considerations.

The use of AGVs can be divided into four main areas of application: 1) supply and disposal at storage and production areas, 2) production-integrated application of AGV trucks as assembly platforms, 3) retrieval, especially in wholesale trade, and 4) supply and disposal in special areas, such as hospitals and offices. In all of these settings, AGVs have been found to reduce the damage to inventory, make production scheduling more flexible, and reduce staffing needs. But, as with any other major capital decision, implementation of these systems must be undertaken cautiously.


AGV usage is growing. One reason is that as manufacturers strive to become more competitive, they are adopting flexible manufacturing systems (FMS). These systems integrate automated material handling systems, robots, numerically controlled machine tools, and automated inspection stations. FMSs offer a high capital utilization and reduced direct labor costs in addition to lower work-in-process inventory and shorter lead times. Because the systems are flexible, they are more responsive to changes in production requirements. These systems offer high product quality and increased productivity.

Flexible manufacturing systems can benefit from the linkage with AGVs. While robots are often highlighted as saving billions in production costs, at some plants—including steel and other metals plants—automated material-handling systems have made the biggest inroads. Today, there are hundreds of instances of computer-controlled systems designed to handle and transport materials, many of which have replaced conventional human-driven platform trucks. Although only a single component of a flexible manufacturing system, automated material handling systems have advantages of their own. These include a reduction in damage to in-process materials, simplified inventory tracking and production scheduling, increased safety, and the need for fewer personnel than in conventional systems.


United States Steel-Posco, I/N Tek and I/N Kote, Allegheny Ludlum, Logan Aluminum, Alcoa, and Kennecott Copper all use automated guided vehicles to move steel, aluminum, and copper coils within their mills. Although the choice of a transport system is often viewed as a technical issue, like every capital decision it demands a comparative economic study. In his book Automated Guided Vehicles, Thomas Müller reminds us that when selecting an investment calculation procedure one should bear in mind that transport systems provide assistance only in achieving the actual production performance of the organization (i.e., the application of a transport system has no actual market value).

Writing in Industrial Management Principles of Automated Data Processing, B. Hartmann suggests following a simple investment formula to compare the costs of AGV systems, which is the cash value of savings from the AGV divided by the cash value of extra costs (compared to the old system) plus the difference in initial outlay (which sets the cash value difference of the extra costs and the cash value difference of the initial outlay against the savings). Obviously, the larger the comparison factor, the more favorable the investment. In performing this calculation, a business must consider both the fixed and variable costs. Fixed costs are incurred independently of the degree of loading, while variable costs depend on the degree of loading the AGVs.


Müller has stated that it is difficult to improve the material flow in existing organizations, since in most cases there are relatively few opportunities to reorganize existing installations or to recover the costs involved. Once the decision to restructure material flow using AGVs has been made, however, certain criteria need to be examined to achieve the full advantages of an automated, yet flexible system.

The first criteria is the physical material flow. By examining the type of goods transported (or load units), the order of transport operations, the quantity framework of the material flow, and the distances of connections within the network, the organization can begin to outline the type of transportation best suited for its material handling requirements. Once the type of transportation is identified, the space and floor conditions need to be addressed. The width of the transport lanes or gangways, any gradients that have to be negotiated, and the type of floor installation required for specific types of trucks all need to be considered carefully. Finally, the choice of AGV can be made. Again, close consideration must be given to transport function, the material flow densities, and the overall process organization.

Computer simulations are often used in planning complex transportation systems. Facilities may require pathways, wire-guidance systems, automatic cranes, and additional computer software and hardware to run the entire AGV system. Some AGV systems even use laser scanners as guidance systems. AGV systems can reduce manual handling damage, and the vehicles are always available, alleviating problems associated with scheduling employees on nights, weekends, and holidays.


Hartmann, B. Industrial Management Principles of Automated Data Processing. Verlag, 1961.

Müller, Thomas. Automated Guided Vehicles. IFS Publications, 1983.

Schriefer, John. "Automated Coil Handling to Improve Efficiency and Quality." New Steel. August 1995.

Sidhartha R. Das, and Basheer M. Kumawala. "Flexible Manufacturing Systems: A Production Management Perspective." Production and Inventory Management. Second Quarter 1989.

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