Predictive Maintenance (PdM) using Artificial Intelligence (AI) and Machine Learning (ML) is the top-ranked use case in terms of business value of industrial digitalization. Not surprising since the annual maintenance cost in Swedish manufacturing industry is over 100 billion SEK and 60% of all maintenance activities are reactive. The PACA project aims to develop PdM algorithms, based on advanced cluster analysis, to increase the precision and make them understandable for decision makers.
Three real-world cases provide data from multiple streams (sensors and computer systems) and multiple machines. The data will be jointly analyzed to identify interesting patterns and compare across machines and their historical records. This will build understanding of how different patterns correlate to certain wear-down behavior, later used to design an algorithm for prediction of future machine states/failures.
Expected effects include: increased productivity, robustness, resource efficiency and competence in Smart Maintenance and advanced data analysis. The cross-disciplinary consortium consists of major manufacturing companies, service and IT providers, and universities with expertise in Smart Maintenance and advanced data science.
To create an inventory of AI techniques for maintenance services, apply AI techniques to three industrial cases, and evaluate their economic and environmental implications.
The aim is to develop new models for visualizing and predicting delivery schedule variations in supply chains.
The objective is to bring together expertise from AI and LCE to Product/Service Systems for Swedish manufacturing firms in a multidisciplinary research effort to utilise latest techniques efficiently for Swedish production industry. The goal is to make a plan of developing demonstrators in production and maintenance using artificial intelligence techniques, digital technologies and lifecycle engineering methods
The SAPPA project is about innovative cloud-based predictive and preventive maintenance systems, improving availability of products and production systems.
e-FACTORY will enable companies to utilize digital tools as a means to obtain a number of different production values, e.g. increased capacity, improved quality, improved traceability, etc