IIC Journal of Innovation 8th Edition | Page 9

Causal Analytics in IIoT – AI That Knows What Causes What, and When will be ready to retire within 5 years 5 . The US Department of Labor also estimates that the average age of industry employees is now over 50 and up to half of the current energy industry workforce will retire within 5-10 years. 6 for telecommunication devices that states “the effect of a telecommunications network is proportional to the square of the number of connected users of the system (n 2 )”. Metcalfe’s law, now also used in economics and business management, provides some quantification of the impact of the increasing complexity of equipment to troubleshoot potential causal relationships between operational events. Manual RCA requires the combination of a rigorous methodology, fault analysis technology and experience to evaluate the possible causes of business events such as equipment failure, quality problems or safety incidents. Much of the expertise needed will be lost with the retiring workforce. A data-driven, algorithmic approach provides a viable replacement for the experience of people to determine causal relationships between business events. Inaccuracy of Root Cause Analysis Root Cause Analysis gained popularity in industrial and other sectors such as healthcare. One of the main challenges that emerged centers around the fact that it requires facilitation and analysis by people who can process only limited amounts of information. People are also susceptible to opinions and organizational influences such as politics. Peerally 9 et al describe the problem with Root Cause Analysis with these 8 main challenges:  The unhealthy quest for “the” root cause  Questionable quality of RCA investigations  Political hijack Complexity of Industrial Equipment As industrial equipment becomes 7 increasingly sophisticated and more complex, the ability to perform diagnostics becomes increasingly more difficult. As equipment becomes more complex and sophisticated, the number or combinations and permutations of potential causal factors for certain events increases exponentially. It follows a similar pattern to Metcalfe’s law 8 5 U.S. Department of Energy, Quadrennial Energy Review (QER) Task Force report second installment titled “Transforming the Nation’s Electricity System.” Chapter V: Electricity Workforce of the 21st-Century: Changing Needs and New Opportunities. January 2017. Retrieved from https://energy.gov/epsa/initiatives/quadrennial-energy-review-qer 6 U.S. Department of Labor Employment and Training Administration “Industry Profile – Energy.” Retrieved from https://www.doleta.gov/brg/indprof/energy_profile.cfm 7 Challenges To Complex Equipment Manufacturers: Managing Complexity, Delivering Flexibility, and Providing Optimal Service http://www.oracle.com/us/solutions/046249.pdf 8 Metcalfe's law https://en.wikipedia.org/wiki/Metcalfe%27s_law 9 The problem with root cause analysis http://qualitysafety.bmj.com/content/26/5/417 IIC Journal of Innovation - 5 -