- •Selector controls
- •Override controls
- •Techniques for analyzing control strategies
- •Explicitly denoting controller actions
- •Determining the design purpose of override controls
- •Review of fundamental principles
- •Process safety and instrumentation
- •Explosive limits
- •Protective measures
- •Concepts of probability
- •Mathematical probability
- •Laws of probability
- •Applying probability laws to real systems
- •Practical measures of reliability
- •Failure rate and MTBF
- •Reliability
- •Probability of failure on demand (PFD)
- •High-reliability systems
- •Design and selection for reliability
- •Preventive maintenance
- •Redundant components
- •Overpressure protection devices
- •Rupture disks
- •Safety Instrumented Functions and Systems
- •SIS sensors
- •SIS controllers (logic solvers)
- •Safety Integrity Levels
- •SIS example: burner management systems
- •SIS example: water treatment oxygen purge system
- •SIS example: nuclear reactor scram controls
- •Review of fundamental principles
- •Instrumentation cyber-security
- •Stuxnet
- •A primer on uranium enrichment
- •Gas centrifuge vulnerabilities
- •The Natanz uranium enrichment facility
- •How Stuxnet worked
- •Stuxnet version 0.5
- •Stuxnet version 1.x
- •Motives
- •Technical challenge
- •Espionage
- •Sabotage
- •Terrorism
- •Lexicon of cyber-security terms
- •Design-based fortifications
- •Advanced authentication
- •Air gaps
- •Firewalls
- •Demilitarized Zones
- •Encryption
- •Control platform diversity
- •Policy-based fortifications
- •Foster awareness
- •Employ security personnel
- •Cautiously grant authorization
- •Maintain good documentation
- •Close unnecessary access pathways
- •Maintain operating system software
- •Routinely archive critical data
- •Create response plans
- •Limit mobile device access
- •Secure all toolkits
- •Close abandoned accounts
- •Review of fundamental principles
- •Problem-solving and diagnostic strategies
- •Learn principles, not procedures
- •Active reading
- •Marking versus outlining a text
- •General problem-solving techniques
- •Working backwards from a known solution
- •Using thought experiments
- •Explicitly annotating your thoughts
Chapter 34
Problem-solving and diagnostic strategies
The ability to solve complex problems is the most valuable technical skill an instrumentation professional can cultivate. A great many tasks associated with instrumentation work may be broken down into simple step-by-step instructions that any marginally qualified person may perform, but e ective problem-solving is di erent. Problem-solving requires creativity, attention to detail, and the ability to approach a problem from multiple mental perspectives.
“Problem-solving” often refers to the solution of abstract problems, such as “word” problems in a mathematics class. However, in the field of industrial instrumentation it most often finds application in the form of “troubleshooting:” the diagnosis and correction of problems in instrumented systems. Troubleshooting is really just a form of problem-solving, applied to real physical systems rather than abstract scenarios. As such, many of the techniques developed to solve abstract problems work well in diagnosing real system problems. As we will see in this chapter, problem-solving in general and troubleshooting in particular are closely related to scientific method, where hypotheses are proposed, tested, and modified in the quest to discern cause and e ect.
Like all skills, problem-solving may be improved with practice and persistence. The goal of this chapter is to outline several problem-solving tools and techniques.
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