UdZPraxis 2-2018

54 UdZ Praxis | Gastbeitrag Core ingredients: Reliability Centered Maintenance (RCM) and data management RCM was introduced in the late 1970s in the aircraft sector and has spread to various indus- tries since then. The basic idea behind RCM is to focus on the Life Cycle Cost (LCC) of the asset and indirect default costs, such as e.g. quality, production loss or safety regards. The challen- ge in the implementation of this maintenance concept is to gain sufficient knowledge of the assets, which is a very difficult task for com- plex assets or plants, new assets, and in terms of knowledge exchange across various depart- ments. In the past the only way to cost efficient- ly generate sufficient data for RCM was mostly done with workshops and the help of experts. Even in the future, experiential knowledge of the maintenance engineering team will be more important than ever, but like all human behavior, the knowledge of experts always tends towards biases. The first expert is more focused on electrical components, so a lot of money is invested in electrical systems; the other one is an expert in lubrication, and thus the focus is placed there. The biggest advantage of a data management system is that it does not have a passion for a specific asset or engineering topic, so the data is always presented in the same way. The ability of data storage solutions has increased tremendously over the past years, the industrial internet of things generates an unthinkable amount of data, and with the possibilities of machine learning / data analytics the data can be transformed into business decisions. Company-specific data management is complex and varies greatly, so the printed logos only show examples of product groups and do not suggest or promote any system. In figure 1 a common approach to maintenance data management is shown. For the purpose of this paper we abstract the process into three steps: raw data gathering and handling, data analysis and decision ana- lysis. In what follows we will explain every step in detail and specify the right method of implementing and improving RCMwith an intelligent data management system. Figure 1: Common approach for data management and analysis Figure 2: Example for a risk centeredmaintenanceworksheet