Root Cause Analysis Solver Engine

Root Cause Analysis Solver Engine (informally RCASE) is a proprietary algorithm developed from research originally at the Warwick Manufacturing Group (WMG) at Warwick University.^[1][2] RCASE development commenced in 2003 to provide an automated version of root cause analysis, the method of problem solving that tries to identify the root causes of faults or problems.^[3] RCASE is now owned by the spin-out company Warwick Analytics where it is being applied to automated predictive analytics software.

The algorithm has been built from the ground up to be particularly suitable for the following situations:

• 'dirty' data
• incomplete data
• big data
• small datasets
• complex problems for example multi-modal failure or with more than one solution

RCASE is considered to be an innovator in the field of Predictive analytics and falls within the category of classification algorithms. Because it was built to handle the data types above, it has been proven to have many advantages over other types of classification algorithms and machine learning algorithms such as decision trees, neural networks and regression techniques. It does not require hypotheses.^[4]

It has since been commercialised and made available for operating systems such as SAP,^[5]Teradata and Microsoft.^[6] RCASE originated from manufacturing and is widely used in applications such as Six Sigma, quality control and engineering, product design and warranty issues. However it is also used in other industries such as e-commerce, financial services and utilities where root cause analysis is required.^[7]

RCASE is non-statistical and thus does not require any hypotheses.^[8] If the key parameters causing the issue or fault in a process are not present in a dataset, it will still narrow the search space and advise where the root cause may lie. This is a different approach to statistical theories which try to find a best fit.^[9]

RCASE se basa en la teoría combinatoria optimizada y se ejecuta en un clúster de computación en malla o en una base de datos en memoria de alto rendimiento . El software se integrará con todos los sistemas MES y ERP . ^{[ 10 ]} El resultado es un sistema de seguridad que supervisa y previene la producción de productos defectuosos. El análisis arrojará marcadores que identifican la causa raíz exacta del fallo o una región paramétrica que indica una alta probabilidad de fallo (es decir, orientación basada en datos sobre dónde buscar a continuación para recopilar datos y resolver la causa raíz con precisión). ^{[ 11 ]}

El software se puede instalar en sistemas operativos Linux o Microsoft y desplegarse como On-Premises o Software-as-a-Service (“SaaS” o “nube”). ^{[ 12 ]}

• Mantenimiento predictivo

• Análisis de Warwick