Purpose-The purpose of this paper is to identify and categorize problems in knowledge management of industrial maintenance, and support successful maintenance through adapting the SHEL model. The SHEL model has been used widely in airplane accident investigations and in aviation maintenance, but not in industrial maintenance. Design/methodology/approach-The data was collected by two separate surveys with open-ended questions from maintenance customers and service providers in Finland. The collected data was coded according to SHEL model-derived themes and analysed thematically with NVivo. Findings-We found that the adapted SHELO model works well in the industrial maintenance context. The results show that the most important knowledge management problems in the area are caused by interactions between Liveware and Software (information unavailability), Liveware and Liveware (information sharing), Liveware and Organisation (communication), and Software and Software (information integrity). Research limitations/implications-The data was collected only from Finnish companies and from the perspective of knowledge management. In practice there are also other kinds of issues in industrial maintenance. This can be a topic for future research. Practical implications-The paper presents a new systematic method to analyse and sort knowledge management problems in industrial maintenance. Both maintenance service customers and suppliers can improve their maintenance processes by using the dimensions of the SHELO model. Originality/value-The SHEL model has not been used in industrial maintenance before. In addition, the new SHELO model takes also interactions without direct human influence into account. Previous research has listed conditions for successful maintenance extensively, but this kind of prioritization tools are needed to support decision making in practice.
Abstract:Big Data and Internet of Things will increase the amount of data on asset management exceedingly. Data sharing with an increased number of partners in the area of asset management is important when developing business opportunities and new ecosystems. An asset management ecosystem is a complex set of relationships between parties taking part in asset management actions. In this paper, the current barriers and benefits of data sharing are identified based on the results of an interview study. The main benefits are transparency, access to data and reuse of data. New services can be created by taking advantage of data sharing. The main barriers to sharing data are an unclear view of the data sharing process and difficulties to recognize the benefits of data sharing. For overcoming the barriers in data sharing, this paper applies the ecosystem perspective on asset management information. The approach is explained by using the Swedish railway industry as an example.
This paper discusses the need for maintenance related training in higher education and investigates the maintenance related education offered by engineering programs in Finland and Sweden. Main study objects are Finnish and Swedish Mechanical and Industrial engineering programs on both bachelor and master level. The study covers, for the selected programs, full programs in maintenance, single courses and parts of courses in which maintenance plays a role. In Finland there are in total 42 universities and applied science schools offering 115 programs within Mechanical or Industrial engineering. Of those, 17 programs contain some sort of maintenance related training. The corresponding figures for Sweden are 23 universities and applied science schools offering 87 programs within Mechanical or Industrial engineering, and 10 of these programs contains maintenance related education. For reviewing the educational contents, data was collected from course syllabuses; for each course the content and expected learning outcomes were analysed and categorised. The maintenance related education in the studied programs is in general low; less than 15% offer maintenance courses. The content in the maintenance related courses differs greatly: concept of maintenance, information systems in maintenance, reliability, life-cycle management, condition monitoring and management of maintenance are covered. For increasing the maintenance topics in higher education, the development of appropriate study material and joint online courses are suggested.
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