Development of Indicators for Maintenance Management within Integrated Planning

Abstract

The increased level of complexity in production and global competition demands a reliable plant capacity. To achieve this, it is of vital importance to integrate maintenance with production planning. This PhD research develops new concepts denoted as integrated planning (IPL). In particular, sound key performance indicators (KPIs) are developed for maintenance planning. The KPIs will communicate between maintenance planning and production planning through an interaction mechanism to the environmental system which is production planning. In this thesis the overall scientific objective is develop theory and methods in IPL that balance maintenance management with other priorities related to physical assets. The main objective has been decomposed into five research objectives:

1. identify and evaluate existing models for maintenance planning strategies;

2. develop a framework for IPL;

3. evaluate and structure existing maintenance KPIs for IPL;

4. further develop KPIs applied for IPL; and,

5. demonstrate and evaluate the KPIs in the IPL framework.

The contributions to science are:

- identification and evaluation of the Deming cycle and static indirect maintenance grouping to be sound strategies in maintenance planning and suitable for further development towards IPL;

- semi-static maintenance strategy applied as a maintenance optimisation strategy in IPL;

- a framework for IPL;

- a framework for structuring KPIs;

evaluation of overall equipment effectiveness (OEE) and maintenance backlog as two appropriate indicators for IPL;

- evaluation of the hidden factory and the need for developing the profit loss indicator (PLI);

- development of the KPIs maintenance backlog and PLI; and,

- demonstration of KPIs in different industrial contexts.

The contributions to practice apply to several sectors and industry branches. Through their industrial challenges it was possible to demonstrate KPI frameworks and PLI. This should in future contribute to reduced minor stoppages, downtime, defects, and revenue losses.

My proposal for further research in this field is modelling and development of the existing theory in IPL. There is also a need for conducting more testing in industrial cases in an attempt to bridge the gap between theory and practice. The 5C model for cyber-physical systems seems promising as a further direction after implementing PLI.