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The Applicability of Statistical Process Control to Systems Involving People Processes and Business Rhythms
Author(s) -
Dever Jason,
Mazzuchi Thomas A.,
Sarkani Shahram,
Mihalcin Matthew J.,
Loewenthal Alex
Publication year - 2013
Publication title -
systems engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.474
H-Index - 50
eISSN - 1520-6858
pISSN - 1098-1241
DOI - 10.1002/sys.21262
Subject(s) - control chart , statistical process control , computer science , reliability engineering , process (computing) , reliability (semiconductor) , constraint (computer aided design) , industrial engineering , engineering , power (physics) , physics , quantum mechanics , operating system , mechanical engineering
The operation and maintenance (O&M) activities of systems can account for 75% of total lifecycle cost. To effectively manage cost, optimize system “on” time, and mitigate defects/failures during the O&M phase of a system's lifecycle, the application of systems monitoring and control is encouraged. Statistical process control ( SPC ) in general, the control chart specifically, is the most common monitoring approach. The control chart provides alerts with respect to the behavior of systems and processes, as well as changes in process variability. Data applied to control charts is assumed to adhere to a normal distribution, a constraint often satisfied in manufacturing and similar industries where the natural variation in the process or system follows the Gaussian distribution. Systems involving people processes and business rhythms can compromise the normality assumption, reducing the reliability of SPC . Through the application of SPC , this paper proposes a novel approach to monitoring operational systems in the systems engineering O&M phase for the express purpose of reducing high costs by mitigating system discrepancies and uncovering inefficiencies. This paper focuses on processes that require 100% system data sampling due to the operational nature of the system.