An important aspect of business efficiency is the cycle time, defined as the total time that it takes to complete a recurring task—usually one essential to the business's output. An example would be the time spent by an assembly machine to install a single electronic component on a circuit board, a task that may be repeated thousands or millions of times. Cycle times may also be observed for longer, multistage processes, such as the time it takes to bring a new product to the market. Traditionally associated with manufacturing processes, the concept is useful in nearly all lines of business. Cycle time may be used to determine such statistics as
Cycle time includes machine or operation time and idle time before the new
cycle starts. In other words,
Suppose that the fabrication of a certain part requires the execution of six different operations or tasks as follows:
For simplicity, let's assume that the idle time is negligible, which is not always the ideal case.
To compute the cycle time for this situation, the number and the nature of workstations need to be defined. For example, all tasks may be done on a single machine or a machining center. On the other hand, each task may be performed on a separate machine or in a different workstation. In other words, the determination of cycle time requires the definition of the manufacturing system that will be used to produce the part.
Let's consider these two situations. If all tasks will be done on a single machine or workstation, then the total time required to produce the part is simply the sum of all cycle time, and the cycle time is determined to be 6.0 minutes. The processing of tasks in this case is said to be sequential.
If we assume that each task will be performed or executed on a different machine, then the cycle time will be the longest time among all tasks, which is 1.5 minutes. In this case, the different tasks are performed in parallel.
Once the cycle time has been determined, it is possible to determine the
daily production output as follows:
As an example, assume that there are two daily shifts. Each shift is eight
hours long, and the daily operating time is 16 hours or 960 minutes. For
the sequential processing case, the daily production output will be
If the tasks are performed in parallel, the daily production output will
Optimum cycle times can be determined using the line balancing techniques. Line balancing problems are mostly concerned with assembly lines or production lines where decisions are needed regarding the optimum number of work stations necessary for a certain assembly or production line. Line balancing problems are also concerned with the determination of optimum cycle times for a given assembly or production line. In order to appropriately solve a line balancing problem, the following information may be needed: production quantity for each product item, operations performed on each item, sequence of operations, and operation times.
Many businesses use cycle time as a benchmark of their productivity. As such, in the long run most companies wish to decrease their cycle times to improve productivity and thereby reduce costs. However, a number of additional benefits can arise from reducing cycle times, including
Indeed, some companies find that these side benefits of analyzing and reducing cycle times can outweigh the more obvious and direct efficiency gains.
However, when altering cycle times, organizations must also be wary of the risk that they will offset the balance throughout their supply and distribution channels. To take a simple example, if a manufacturer begins to bring new products to the market dramatically faster than in the past, it may need to alter its marketing programs and buyer support system in order to facilitate the faster delivery.
Ellis, Lynn. Evaluation of R&D Processes: Effectiveness through Measurements. Boston: Artech House, 1997.
Meyer, Christopher. Fast Cycle Time: How to Align Purpose, Strategy, and Structure for Speed. New York: Free Press, 1993. Schilling, Melissa A., and Charles W.L. Hill. "Managing the New Product Development Process: Strategic Imperatives." Academy of Management Executive, August 1998.
Schwartz, Karen D. "Benchmarking for Dollars." Datamation, February 1998.