Industrial Engineering Knowledge Center: Industrial Engineering Statistics - IE Six Sigma Studies of Processes

Wednesday, April 13, 2022

Module of Industrial Engineering ONLINE Course

Modules

Industrial Engineering 4.0

Industrial Engineering Case Studies

Industrial Engineering Statistics

F.W. Taylor himself advocated maintaining of records and data for decision making. The other industrial engineering pioneers also promoted record keeping and data analysis. As sampling based decision making became more robust, industrial engineers promoted it as a productivity improvement initiative and imperative. One of the prominent areas of application is statistical quality control. Now six sigma, a statistics based technique is being promoted by the IE profession.

Six Sigma Method and Industrial Engineering - Robust Productive Process Design - IE Six Sigma Projects.

Industrial engineers have to make their process redesigns robust and the six sigma exercise will facilitate that task. Industrial engineers can measure the output possible from a current process subject to six sigma exercise and then subject the redesigned process to six sigma exercise. It is logical that the process which gives better output in terms quality, productivity and cost will be selected. A multi-objective criterion can be used to make the choice.

Robust product design and process planning in using process capability analysis

Journal of Intelligent Manufacturing volume 26, pages459–470 (2015)

https://link.springer.com/article/10.1007/s10845-013-0802-6

Module Lessons

Lesson 401

Statistics and Industrial Engineering

http://nraoiekc.blogspot.com/2012/07/statistics-and-industrial-engineering.html

402

Statistical Quality Control – Industrial Engineering

https://nraomtr.blogspot.com/2011/12/statistical-quality-control-industrial.html

403
Basics of Statistics

https://eng.libretexts.org/Bookshelves/Industrial_and_Systems_Engineering/Book%3A_Chemical_Process_Dynamics_and_Controls_(Woolf)/13%3A_Statistics_and_Probability_Background/13.01%3A_Basic_statistics-_mean%2C_median%2C_average%2C_standard_deviation%2C_z-scores%2C_and_p-value

404

Statistical Process Control
http://www.itl.nist.gov/div898/handbook/pmc/section1/pmc12.htm
http://www.itl.nist.gov/div898/handbook/pmc/section3/pmc3.htm

Evaluation Improvement of Production Productivity Performance using Statistical Process Control, Overall Equipment Efficiency, and Autonomous Maintenance,
Amir Azizi
Procedia Manufacturing
Volume 2, 2015, Pages 186-190
open access
http://www.sciencedirect.com/science/article/pii/S2351978915000335

405

Statistical Quality Control
http://www.itl.nist.gov/div898/handbook/pmc/section2/pmc2.htm

406

Calculation of Sample Sizes in Work Measurement and Work Sampling

http://www.measuringu.com/sample_continuous.htm
http://www.prenhall.com/divisions/bp/app/russellcd/PROTECT/CHAPTERS/CHAP08/HEAD06.HTM (WorK measurement full chapter - Includes sample size calculation for time study and work sampling)

407

Test of Hypothesis

Test of hypothesis is to be used by industrial engineers to confirm or validate that their redesign or a process has resulted in the increase of productivity. This becomes useful when there is variation in the output from various workstations or persons. We can also visualize activities in different places. In such case we test the hypothesis that productivity has improved in the workstations where redesign is is implemented.