Fault Finding Troubleshooting Flowcharts
Fault finding flowcharts and diagnostic troubleshooting flowcharts have been used for a long time to capture and convey the steps required to help identify and repair faults.
VisiRule lets you can turn these fault diagnosis flowcharts into self-service interactive troubleshooting guides so both qualified and unqualified people can diagnose faults and even make temporary repairs. By deploying fault finding troubleshooting flowcharts, you can empower your existing staff and field agents, and improve your customer service, in a controlled and recorded way.
VisiRule delivers fault finding problem resolution direct to the person who needs help on their own personal device using a dynamic sequence of interconnected questions.
Each answer helps determine the next question. Advanced calculations can be performed and complex logic evaluated. Pictures and videos can be incorporated to provide explanations and guidance.
Benefits of VisiRule Interactive Fault-Finding Flow Charts
reduce the time to problem resolution
reduce the accuracy of problem resolution
reduce the cost of providing informed product fault finding support
capture the faults logged and symptoms found
deliver informed guidance on mobile devices
provide links to the very latest product information
Self-Service Troubleshooting Flow Charts
Self-service troubleshooting is a powerful way of improving customer satisfaction. And it reduces the strain and workload on your own experts. Modern mobile technology provides an ideal platform for delivering self-help expert systems in a convenient and cost-effective way. With VisiRule, you can create fully automated decision trees for your help-desk agents and support staff, to ensure that customers always receive the correct response.
Intelligent Fault Finding: Detection & Resolution
Fault finding, or troubleshooting, can be best captured and represented diagrammatically. Using VisiRule Author, you simply draw the fault finding flow chart and it will generate an interactive question and answer session. This queries the nature of the symptoms present and directs users to a suitable diagnosis and associated recommended course of action.
Decision Tree Analytics
VisiRule can be used for the following:
Model data mining output to provide insight into the past and answer: “What has happened?”
Use forecasting rules to understand the future and answer: “What could happen?”
Capture advice on possible outcomes and answer: “What should we do?”
Diagnostic Flow Charts
You can map out the logic needed to diagnose faults using a diagnostic flow chart or flowchart. A fault finding troubleshooting flow chart provides an excellent way to model and share the process logic needed to help identify the root cause and most suitable resolution.
Interactive Troubleshooting Guides
Questions can have links to help files, manuals, KBs, images, pictures and other useful material. Users are only ever asked questions which are relevant and will contribute to an appropriate solution being found. Using the browser, they can go back and change their mind, and see what other questions and conclusions might be considered relevant. All of this makes for a rich, interactive walk-through of the troubleshooting process.
This works as both proactive and prescriptive maintenance.
Why Diagnostic Expert Systems?
Expert systems have been widely used over the years to help find faults in industrial and electrical equipment as well as deliver diagnostic advice in areas such as healthcare and customer support. Expert systems provide a systematic way to reason, extract, store and manage the expertise and know-how of senior personnel, engineers and management. This knowledge can then be used and shared with a wider range of less experienced or less specialist staff, and/or provided directly to consumers using simple interactive question and answer sessions.
Expert systems can interface to modern equipment and data feeds such as SCADA systems, PLCs and industrial controllers. Modern sensor technology and vibration data coupled with wireless or wired networks means that the intelligent remote monitoring and diagnosing of machinery is now viable. Intelligent diagnostic systems can shorten system downtime by helping identify worn parts and likely causes of failure BEFORE a part fails.
Valuable knowledge can be shared and retained, even when staff members retire or leave. Prolonging the life of old equipment and being able to provide accurate and effective maintenance support systems can be aided greatly by VisiRule.
Decision Graphs - More Powerful than Decision Trees
By allowing the merging of divergent branches within the diagnostic trees, VisiRule charts support paths which join up, so reducing the unnecessary duplication of sub-trees. This 'convergence' provides a far more compact representation than traditional decision trees which are prone to 'exponential explosion'.
VisiRule Troubleshooting Guide Features
VisiRule supports compound expressions of arbitrary complexity as well as simple expressions. VisiRule also supports delayed logic where you refer back explicitly to a previous answer to a previous question.
Explainable AI Reasoning
Explanations can be attached to each step of the diagnosis to help guide and aid the user, and also to provide a way of explaining how a conclusion was reached.
Pictures, Videos and Links
Explanations can be in the form of text, pictures, images, videos and links to relevant web pages. Each question in VisiRule has a slot for an explanation.
A record of each user session containing all the answers given, and any computations calculated, is made available along with the final conclusion reached for subsequent use. This can be emailed to the relevant department.
Your VisiRule chart can be used to generate an intelligent diagnostic chatbot which can guide users to a solution using a sequence of targeted questions.
VisiRule records each and every user sessions and uses these logs to produce intelligent visual analytics. Visual Analytics helps provide insight into popular paths and frequently occurring problems, and spot emergent patterns. Understanding the relationship between different clusters of answers and faults detected helps you understand better exactly how your charts are being used. By capturing user feedback, and seeing which routes are most popular, it is possible to produce self-service systems which actually improve over time.