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Smart Maintenance

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The Future of Industrial Maintenance

The annual cost of maintenance and production disturbances in the Swedish manufacturing industry is more than 100 Billion SEK and the Overall Equipment Effectiveness (OEE) is just above 50%. It is therefore easy to understand the recent increase in attention for the maintenance field, both in industry and academia. 

For example, predictive maintenance is considered one of the most important industrial use cases for enabling industrial digitalization, given the potential business value (impact) and the richness of available data. Similarly, maintenance is of high strategic importance for companies in terms of enabling failure-free and resilient production systems with high levels of automation. 

To meet these demands and develop the future of maintenance in your company, this learning area is about Smart Maintenance – maintenance in digitalized manufacturing!

Available modules
Learning outcome
Explain the concept of Smart Maintenance.
Distinguish between the four core dimensions of Smart Maintenance: data-driven decision-making, human capital resource, internal integration, and external integration.
Analyse contextual factors and expected effects of Smart Maintenance.
Assess the level of Smart Maintenance in a given factory.
Recommend actions and develop strategies to increase the level of Smart Maintenance in a given factory.
Explain the importance of effective integration for achieving smart maintenance.
Describe the expected benefits from adopting the asset management concept.
Analyze how the concept of servitization affects the management, procurement, and fulfillment of smart maintenance.
Assess the level of internal and external integration in a given operation.
Recommend actions and develop strategies for effective internal and external integration in a given operation.
Understand the principles and benefits of predictive maintenance.
Gain knowledge of different predictive maintenance techniques and tools.
Develop skills in data collection, analysis, and interpretation.
Learn how to identify FAILURE MODES and develop maintenance plans.
Gain proficiency in using predictive maintenance software and tools.
Understand the role of predictive maintenance in overall asset management and organizational strategy.
Develop communication and collaboration skills for working with maintenance teams and other stakeholders.
Partners
chalmers university of technology
KTH Royal Institute of Technology
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