Decision model software maintenance

That decision responds to, in effect, the active decision model. But has that model been examined in the current operating context? Can it be improved? What were the observed conditions of engines prior to scheduled overhaul at hours?

Were they all on the verge of failing? Probably not. What were the observed Failure Modes? How many engines failed in service prior to scheduled overhaul? What sensor or monitored data patterns preceded the failure or preventive overhaul? Continuous improvement, nevertheless, is one of the foremost requirements of modern maintenance practice mandated by such programs and standards as PAS 55 or ISO Could a maintenance organization gradually supplant a particular legacy age based model in favor if a more aggressive policy based on both age and condition monitoring data?

How could this be done systematically based on the evidence? Such an endeavor would do more than simply collecting and observing sensor and oil analysis data. A rule or procedure needs to be formulated to transform that data into a decision that is verifiable.

The decision model must be shown to render decisions that optimally satisfy one or more desired availability, profitability, or reliability objectives. Decision Modeling enables the right mix of analytics, AI, rules, machine learning, optimization, decision support and decision automation in a single model. As the world moves beyond rigid programming logic to data-driven decision-making, decision modeling with DMN is critical to the future of your business.

Simplify business rules analysis and maintenance, sustain business engagement, improve traceability and impact analysis and extend rule coverage and re-use. Deploy a working decision automation pilot in just weeks. Developing systems that truly support data-driven decisions by focusing on the decision to be made not the data available. Realize value from Machine Learning by developing a shared business understanding and deployment context for multi-functional data science teams and their business partners.

The same model can be used to monitor the decay of a software system quality and thus avoid the need to renew it using the most costly renewal processes. Key words: Legacy system, renewal process, reverse engineering, reengineering, maintenance, software qualities 1.

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