Intelligent Asset Management: A crash course on ISO55000 series
Intelligent asset management enhances the efficiency and effectiveness of industrial systems, aligning with organizational goals, and supporting the transition to a circular economy by prioritizing the lifecycle management of assets. This course is to serve as a comprehensive and condensed program that enables participants to gain knowledge in asset management principles, standards, and best practices.
Facts
Target audience:
The target group includes individuals working in various industries such as railway, mining, transportation, construction, manufacturing, logistics, energy, and other organisations that are or planning to implement asset management systems. This course can be suitable for professionals ranging from asset managers, maintenance and reliability professionals, operation managers, engineers, project managers, and asset management consultants.
Prerequisites:
Upper secondary school, bachelor, or equivalent.
Scope:
40 study hours
Location:
Fully digital
Language:
English
Price:
4 200 SEK
Registration:
Register your interest further down on this page.
Course content
The course includes:
Introduction to assets, asset management
Understanding the needs and expectations of stakeholders
Introduction to asset management system
Asset management programme
Leadership and commitment
Planning asset management
Risk management
Sustainable development
Decision and decision-making
Lifecycle management LCC,LCP
Availability, Reliability, Maintainability, Maintenance Support
Safety and security
Maintenance and maintenance programme
Asset management and maintenance
Tools for asset management – Analytics, AI, digitalisation
Performance measurement and KPIs
Support to asset management
Competence development
Auditing asset management process
Continuous improvement, Kanban etc.
Examples of relevant tools for asset management
Course structure
The course will be a mix of lectures and guest speakers, video recordings, reading, assignments, interactive discussions and collaborative projects.
Self-study (30–35 hours) and meetings (5–10 hours).
To pass the course
To pass the course you need to submit final assignment (Report) and quizzes.
Teachers
Ramin Karim, Professor Division of Operation and maintenance Engineering, Department of Civil, Environmental and Natural Resources Engineering
Jaya Kumari, PhD student Division of Operation and maintenance Engineering, Department of Civil, Environmental and Natural Resources Engineering
Expression of interest
Registering your interest is not binding. The course starts when enough people have registered their interest.
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