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How Can SMEs Benefit from Big Data? Challenges and a Path Forward
This paper identifies barriers to SME uptake of big data analytics and recognises their complex challenge to all stakeholders, including national and international policy makers, IT, business management and data science communities.
Industrial Process Monitoring in the Big Data/Industry 4.0 Era: from Detection, to Diagnosis, to Prognosis
We provide a critical outlook of the evolution of Industrial Process Monitoring (IPM) since its introduction almost 100 years ago. Several evolution trends that have been structuring IPM developments
A systematic comparison of PCA-based statistical process monitoring methods for high-dimensional, time-dependent processes
These fundamental methods will be systematically compared on high-dimensional, time-dependent processes to provide practitioners with guidelines for appropriate monitoring strategies and a sense of how they can be expected to perform.
Multiscale statistical process control with multiresolution data
The approach proved to be able to provide a clearer definition of the regions where significant events occur and a more sensitive response when the process is brought back to normal operation, when it is compared with previous approaches based on single resolution data.
Aroma ageing trends in GC/MS profiles of liqueur wines.