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In an era where real-time asset data is crucial for a more efficient and safer production environment, many companies still struggle with how and which techniques to use for collecting this data. Manual measurements, standard sensors, or AI-driven smart monitoring? The possibilities are numerous, but large-scale implementation often proves complex and economically unfeasible.
Across industries, maintenance remains a critical challenge. Many organizations face low uptime, frequent breakdowns, and rising maintenance costs. Despite investments in new technologies and improvement initiatives, achieving consistent performance remains a complex task. As a result, maintenance is often perceived as a cost center rather than a strategic asset.
From the Digital Factory Alliance (DFA) and the SM4RTENANCE consortium we are delighted to invite you to join us in our last SM4RTENANCE Deep Dive, part of a set of key events that actively have explored business and technical applications of Data Spaces in the manufacturing industry.
Attendees will gain insights into the transformative impact of data-driven processes on manufacturing operations.
In today's digital landscape, businesses heavily invest in advanced Enterprise Resource Planning (ERP) and Computerized Maintenance Management Systems (CMMS) to streamline operations. These systems are designed to integrate and automate various business processes, from financial management to supply chain logistics and asset tracking. However, many companies still struggle with fundamental questions regarding field inventory management: What exactly is in stock? Where is it located? Does our digital record match the physical reality?
The European Commission, in collaboration with SYSTEM FACTORY, the french defence cluster of Toulon Région Sud part of the European Network of Defence Regions (ENDR), proudly presents the international conference on "Maintenance in Defence Domains," to be held on April 1 and 2, 2025, in Toulon, France.
Discover the benchmark results and the introduction training for Sustainable Asset Management on 27 March 2025, designed to reduce energy consumption and emissions in industrial companies.
Predictive maintenance has already become a reality for many industrial companies. Approximately 15-20% have fully implemented or are in the process of implementing predictive maintenance technologies, with their current challenge being to maximize the added value, secure board-level buy-in, and ensure continuous investment in further rollouts. Meanwhile, an additional 60-65% are running pilots or planning their implementation strategies.
This use case focuses on generating value on how machines are actually being used, and can be used to improve the operating parameters, tooling, and processes for machine users.
