How can a new manufacturing process be planned before it begins? How much time will this new process take? And how efficient will the process be compared to its competitor’s? The answer lies with standard data. Because of these applications, it’s no surprise that standard data is the backbone of production design and industrial engineering. Keep reading to learn how standard data is used in process engineering to achieve a wide variety of production goals.
According to the late renowned industrial engineer Marvin Mundel, “Rather than determine the standard of time for each job on the basis of an individual study, standard times from a number of related jobs may be organized into a database from which the standard times for related jobs may be constructed or synthesized.” Mundel is describing the importance of using standard data for elements and tasks in order to more efficiently create production standards and standardize process methods. As long as the data is standardized, we can apply data from common elements and tasks to design and evaluate new processes. Rather than studying and observing the same tasks repeatedly, we can use predetermined time standards based on past observation of similar jobs. By creating and utilizing standard data, repeated observation of simple elements becomes unnecessary, saving us time and energy.
Standard data is especially important in the pre-planning design phase, where we often use preexisting time studies to visualize and study future processes. We first create a method by outlining the exact steps of a future process using standardized, measurable steps called elements. Standard data is then used to determine the labor cost of this future process, compare variations in method, evaluate design proposals and measure differences in expected productivity. Standard data is also useful in any industry that requires estimating. Labor cost estimates become more accurate when standard data of prior observed tasks is used.
Standard data can be developed for any organization. Observation and data collection, although initially laborious, will pay for itself tenfold when used to standardize processes that are repeated over time. Past time studies, MODAPTS predetermined time standards and industry standard databases are a few very important sources of standard data. There are many advantages of using standard data which include setting production standards in advance, increased productivity in process planning, accuracy in estimating and consistency in evaluating production standards.