Six Sigma is a well-known engineering and manufacturing process created by Motorola in 1986. The Six Sigma system attempts to eliminate product defects by identifying the cause of the deviations. Properly executed, Six Sigma yields 3.4 defects per million products. This has become the gold standard of engineering efficiency, leading to a number of copycat programs.

Lean Six Sigma

Lean Six Sigma is similar to Six Sigma, developed and certified by Motorola as well. "Lean" differs in that it also examines work processes and deficiencies in work flow, rather than just defects in products. For example, Lean attempts to identify overproduction, unnecessary processing, poor logistics, production delays and even products that do not meet the customer needs. Lean essentially helps to fill in the gaps that Six Sigma does not resolve.


Capability Maturity Model Integration (CMMI) was developed by software engineers at Carnegie Mellon University. The process is similar to Six Sigma but mostly focuses on software improvement. Because software can be indefinitely altered and upgraded, CMMI became necessary as an alternative to Six Sigma. It is a way for different company units to integrate their development processes with the same goals by creating guidelines and a point of reference for improvement.

Statistical Process Control (SPC)

Statistical Process Control (SPC) is a method of quality control based entirely on statistical analysis. It is used primarily for process capability performance and process monitoring. In other words, it determines how well systems are working. One popular subset of SPC is Pareto Analysis. Pareto statistics organize production data by time, process and defect number. It can help you identify where problems arise and optimize efficiency.

Engineering Process Control (EPC)

Engineering Process Control is similar to Statistical Process Control in that it uses charts and data to identify problems, but focuses on prediction and concurrent adjustment of the engineering process. EPC involves charting a process in real time and then changing it if efficiency metrics are different than expected. This is done by constructing graphs and intensely monitoring the progress of the targeted process.