The posting on June 27, 2011
introduces Statistical Engineering, and the article by Anderson-Cook et al (2012) discusses the definition of Statistical Engineering proposed by Hoerl and Snee (2010). That is, the study of how to use known statistical principles and tools to solve high-impact problems for the benefit of mankind. The posting on June 27
gives two examples of Statistical Engineering. They are Lean Six Sigma (LSS) and the Hoerl-Snee process improvement strategy discussed at length in this blog starting with the posting of March 18, 2008. The Theory of Constraints (TOC) is another example of Statistical Engineering, and this is mentioned by the author of this blog in the article by Anderson-Cook et al (2012).
Dettmer (1997) distinguishes between Goldratt's Theory of Constraints (TOC) and a Process Improvement Strategy. He states that the TOC is a System Improvement Philosophy rather than a Process Improvement strategy. Goldratt's viewpoint is that organizations achieve their goals as systems not as processes. The interaction among component processes determines how well the system performs. Goldratt views the system as a chain or a network of chains. The network of chains has a weakest link that limits system performance. The weakest link is the system constraint. One has to improve the weakest link or constraint in order to improve the system. On page 8, Stein (1997) states the following important principle employed by the TOC. "In any chain of events there can only be one weakest link, and if improvement is to occur only the weakest link needs to be strengthened."
Stein (1997) specifies that the first step in applying the Theory of Constraints is to select a method of measurement for system performance. This measurement method must be agreeable to management and all involved parties. A measurement commonly used in TOC publications is Throughput. One example given by Stein for throughput is the rate at which the system generates money through sales. Creasy (2009) calls this performance measurement the Capstone Metric.
Why connect TOC with Statistical Engineering? Creasy (2009) and Nave (2002) recommend using the Theory of Constraints (TOC) with LSS to generate more effective system improvements. Also, Stein states on page 9: "Not only the physical resources but also the individual functions of a corporation are subject to the laws governing probability and statistical fluctuation."
1. Anderson-Cook, C.M., Lu, L., Clark, G., DeHart, S.P., Hoerl, R., Jones, B., MacKay, R.J., Montgomery, D.C., Parker, P.A., Simpson, J., Snee, R., Steiner, S., Van Mullekom, J., Vining, G.G., Wilson, A.G. (2012). “Statistical Engineering – Forming the Foundations”, Quality Engineering,
24(2), pages 110-132.
2. Creasy, T. (2009) "Pyramid Power", Quality Progress
3. Dettmer, H. William (1997). Goldratt's Theory of Constraints: A Systems Approach to Continuous Improvement,
ASQC Quality Press, Milwaukee, Wisconsin.
4. Nave, D. (2002). "How to Compare Six Sigma, Lean and the Theory of Constraint." Quality Progress 35(3): 73-78.
5. Stein, R. E. (1997) The Theory of Constraints: Second Edition
. New York, Marcel Dekker, Inc.