Smart Maintenance Investments - ways to quantify effects and factors influencing the investment process

Abstract: Currently, industry is undergoing a digital transition, aiming at increased competitiveness. The transition towards digitalised manufacturing is expected to be a fourth industrial revolution, in which the new technology enables production systems to be decentralised and work autonomously. Maintenance organisations must take a key role in order to meet the requirements of digital manufacturing, approach failure-free production and achieve a new level of competitiveness. It is anticipated that maintenance organisations will transform towards Smart Maintenance, an organisational design of the maintenance function which fits into digitalised manufacturing. Transforming towards Smart Maintenance will require substantial organisational changes, as well as resource investments in technology and human capital. However, industrial practitioners are finding it a challenge to justify maintenance-related investments. In academia and industry, quantification is considered an important way of justifying investments; the emphasis in previous maintenance has been mainly on developing mathematical models. Less emphasis has been placed on empirical research into real-life industrial applications. The purpose of this thesis is to justify Smart Maintenance investments. The aims are to understand how the effects of maintenance can be quantified and to understand the maintenance-related investment process within industry. To fulfil these aims, this thesis adopts a mixed-methods research approach to qualitative and quantitative studies, as well as theoretical and empirical ones. The initial studies of this thesis conclude that there are multiple ways of quantifying the effects of maintenance. This thesis reviews 24 models, analyses 170 maintenance performance indicators (PIs) and presents a demonstration of discrete event simulation (DES) as a tool for quantifying the effects of maintenance. Factors other than quantification come into play for resource investments relating to maintenance. Based on empirics, this thesis describes 11 such additional factors. Equipped with methods for quantifying the effects of maintenance and understanding the factors influencing maintenance-related investment process, companies can work towards Smart Maintenance to approach failure-free production and achieve a new level of competitiveness.