OVERVIEW:
There are times when it is not practical to set standards
with any direct measurement procedure. For example, if your operation has a
high volume of different SKU’s, low production runs, or rapid changeover, then
developing a standard data system is the appropriate way to generate work
standards. As Marvin Mundel stated, “Rather than determine the standard time
for each job on the basis of an individual study, standard times from a number
of related jobs may be organized into a data base from which the standard times
for related jobs may be constructed or synthesized.”
This two-day course provides an in-depth understanding of standard
data systems and the analytics involved in developing them within your
organization. Multiple case studies show how to apply statistical tools to
existing data in order to create accurate and reliable standard data systems.
Advantages of standard data include increased productivity
in setting standards, a capability to set standards before production,
increased consistency in standards, and a standardized way to provide
information to other systems such as product cost estimating, computer assisted
process planning, and MRP systems.
WHAT YOU WILL LEARN:
Upon completion of this course, you will be able to:
- Define standard data systems
- Determine advantages and disadvantages of
standard data systems
- Apply analytical tools to develop standard data
models
- Develop standard data model
- Evaluate standard data models
COURSE CONTENT:
- Introduction to Standard Data
- Microscopic
- Macroscopic
- Advantages
- Disadvantages
- Structure
- Regression and Correlation within Standard Data
- Developing Models
- Evaluating Models
- Applying Standard Data
Participants will need to bring a computer running Excel® to
the class. Case studies will require the use of the data analysis tool pack
found in Excel®
CLASS CANCELLATION:
IISE reserves the right to cancel a class up to 15 business
days prior to the scheduled start date.