Natural Language Processing applications in manufacturing: a systematic literature review

Among the manufacturing sector several applications of Natural Language Processing (NLP) are emerging. NLP is a branch of Artificial Intelligence (AI) aimed at understanding, interpreting, and manipulating human language through computer-based data processing. This application is quite powerful and prospective in manufacturing context, considering the ever-increasing amount of data available within the organizations, often unstructured, non-standardized, and free text. Therefore, human analysis to extract information and useful knowledge results in a long and tedious task with limited added value. The automation of these activities moves workers to more meaningful and value-added activities; it improves efficiency in searching for and extracting information, with benefits for decision-making processes. The paper presents a systematic literature review concerning NLP applications in manufacturing, conducted using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement methodology. Basing on the documents retrieved, a comparative analysis of the literature is presented. The analysis is carried out following two different rationales: an objective analysis, which highlights and compares the different purposes with which NLP is applied in the manufacturing field, such as knowledge base, ontology, predictive maintenance, human machine interaction and decision support system. The second analysis investigates NLP applications by exploring different production process phases involved in manufacturing activities. The research identified mature NLP applications, transversally implemented in several production process phases, with specific objectives. The paper provides a comprehensive and in-depth overview on the topic. Finally, possible future directions of development of NLP in manufacturing were defined. © 2022, AIDI - Italian Association of Industrial Operations Professors. All rights reserved.