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At a basic level, machine learning (ML) is the science of getting computers to act without being explicitly programmed. In other words, with a certain degree of autonomy. In the past decade, ML has given us self-driving cars, practical speech recognition, effective web search, and significantly improved understanding of the human genome and pharmaceuticals. ML is a subfield of computer science that evolved from the study of pattern recognition and computational learning theory in AI. ML research and development has led to the creation and study of algorithms that can learn from and make predictions on data. ML primarily focuses on prediction, based on known information learned from training data, a set of data used to discover potentially predictive relationships. Today, advanced analytics and more specifically, predictive analytics based on ML is providing a next generation tool for manufacturers to improve and optimize their production systems.
Machine learning technologies and applications have particular significance for manufacturing. As manufacturers make the transition to the smart connected factory and extend Industrial Internet of Things (IIoT) ecosystems across factories, supply chains, and service of products in field, efficient and flexible data analysis will be critical to the operations of production systems and plant assets. Advanced analytics powered by ML algorithms will access and analyze large volumes of production records and information to drive real and actionable continuous process improvement and complete the as-built to as-designed feedback loop. ML applications targeted on manufacturing processes will be able to learn through pattern matching algorithms that can process large volumes of completed records, quality assurance and non-conformance information which today represents Big Data generated by production execution systems. Next, predictive analysis will be performed to determine what the outcome or consequences of the analysis will have on processes going forward. The next step will be take some sort of action to mitigate or adapt the processes to effect an improvement, i,e., a prescriptive change. Today, there are ML-based applications being offered by software providers in this space that can perform this type of advanced analytics for manufacturing processes and an IIoT connected ecosystem.
There are other areas that ML can help companies. As manufacturers introduce next-generation materials to product design and build, understanding the manufacturing processes, and discovering and adapting to new material characteristics and properties will be essential. ML will be able to make sense out of the large volumes of production data and the many variables involved to help streamline production processes and improve product designs.
Machine learning technologies and applications have particular significance for manufacturing. As manufacturers make the transition to the smart connected factory and extend Industrial Internet of Things (IIoT) ecosystems across factories, supply chains, and service of products in field, efficient and flexible data analysis will be critical to the operations of production systems and plant assets. Advanced analytics powered by ML algorithms will access and analyze large volumes of production records and information to drive real and actionable continuous process improvement and complete the as-built to as-designed feedback loop. ML applications targeted on manufacturing processes will be able to learn through pattern matching algorithms that can process large volumes of completed records, quality assurance and non-conformance information which today represents Big Data generated by production execution systems. Next, predictive analysis will be performed to determine what the outcome or consequences of the analysis will have on processes going forward. The next step will be take some sort of action to mitigate or adapt the processes to effect an improvement, i,e., a prescriptive change. Today, there are ML-based applications being offered by software providers in this space that can perform this type of advanced analytics for manufacturing processes and an IIoT connected ecosystem.
There are other areas that ML can help companies. As manufacturers introduce next-generation materials to product design and build, understanding the manufacturing processes, and discovering and adapting to new material characteristics and properties will be essential. ML will be able to make sense out of the large volumes of production data and the many variables involved to help streamline production processes and improve product designs.