Effective Maintenance: A Configuration Approach

This thesis addressed the industrial need for effective and efficient maintenance of assets using an approach that leverages historical data and mass customization concepts. The primary objective of this research was to improve maintenance preparation and execution by emphasizing the importance of clear, visual, and easily understandable information for decision-making. The research also aimed at eliminating low-value activities, reusing valueadding activities, and learning from past equipment failures and maintenance practices to drive improvements.

The study incorporated the principles of modularization, which involved decomposing maintenance activities into independent modules that represented specific tasks, such as repairs or replacements. This collection of well-defined and value-adding modules meets the maintenance needs of companies by allowing for customization and configuration.

The research methodology involved studying a maintenance-performing company and exploring the role and value of data in maintenance preparation. It investigated the potential for reusing historical data and structuring and organizing it using the modularization approach. Furthermore, the research examined the purposeful development of configurators. Models and methods were developed to structure, organize, and synthesize historical data for decisionmaking; modularize maintenance activities and instructions based on historical data; and evaluate configurator projects in alignment with development objectives and requirements.

The key findings of this research revealed that valuable insights for maintenance preparation could be derived from data on equipment failures and maintenance activities. Moreover, historical data could be effectively utilized for the modularization of maintenance, resulting in a significant reduction in non-value-adding variety and an enhancement of value-adding variety. Furthermore, the incorporation of effective performance assessments in configurator development projects could steer these projects toward achieving their targets. By effectively configurating maintenance activities, significant improvements were achieved, including error rate reductions from above 4% to below 1% and a time reduction of 75%–92% compared to traditional methods.

This thesis underscores the value of modularization and architectural principles, traditionally applied in product domains, within the context of maintenance. The research demonstrates the value of data-driven approaches, modularization principles, and information accessibility in enhancing maintenance preparation. By leveraging historical data, implementing modularization, and utilizing configurators, companies can tackle industry challenges more effectively.