Mirka Kans

An approach for determining the requirements of computerised maintenance management systems

Information technology (IT) could be an important tool for reaching efficiency and effectiveness within maintenance, provided that correct and relevant IT is applied. In this paper, a conceptual model for identifying maintenance management IT requirements is developed, with its practical application in a process for the IT requirements identification for maintenance management. The process is exemplified in two real-world cases. This paper suggests that the factors of goals, purpose and use should be considered on organisational and individual level in order to identify the IT demands. Correct level of IT applied, i.e. IT consisting of correct functionality required for planning, conducting and following up maintenance activities according to the state of maintenance and the strategy adapted, will contribute to successful maintenance management. Moreover, this paper promotes the use of a structured procedure for the identification of IT requirements for maintenance management.

The advancement of maintenance information technology : A literature review

Purpose – Maintenance management information technology (MMIT) systems have existed for some 40 years. The purpose of this paper is to investigate the advancement of these systems and compares the ...

A model to identify relevant data for problem tracing and maintenance cost-effective decisions : a case study

Purpose – The purpose of this paper is to help build up a relevant database for mapping technical and financial effectiveness of production in order to make cost‐effective maintenance decisions. Design/methodology/approach – A theoretical model is developed based on past research and experience adopting a holistic systems approach on the production. A case study, which includes databases of two maintenance‐used software programs, verifies the potential of applying the model. Findings – The main result achieved is a model for identifying relevant data required for accurate problem tracing and localisation within maintenance and production processes using a top down approach. The main conclusions are integration of IT and data resources within the enterprise is needed for developing a holistic view of the production process and a well‐formulated and documented procedure of data identification will ensure that the data can be traced back to root sources and in this way we can support the work of continuous cost‐effective improvement by eliminating root causes of problems at an early stage. Research limitations/implications – Further model verification by industrial case studies would be of interest. Practical implications – The holistic approach and the model presented are applicable especially in capital intensive industries, where maintenance budget is not negligible and the amount of data to process is large. By structuring the data need and data identification process relevant performance measures will be monitored and advanced maintenance concepts can be applied. Originality/value – By applying the proposed model in industry, the data identification process itself and not the data contents is necessary to be standardised and structured. It shifts the focus of the quality aspect from just data level to both data and data collection level. The performance measures will therefore not be chosen depending on what the IT applications can provide in first hand, but upon what is needed for cost‐effective mapping, analysis, following up and assessment of maintenance performance.

Analysing IT functionality gaps for maintenance management

Several studies have been carried out for describing the functionality and use of computerised maintenance management systems. A major drawback of these studies is that they do not reveal the actual support for maintenance management. To describe the full situation, the gaps between required support and actual support have to be determined. The gaps are of two kinds: 1) Between the functionality included in the IT system and the functionality required, and 2) Between the functionality included in the IT system and the functionality actually used. To reach a better understanding of the utilisation of IT in maintenance management, the existence of these gaps must be further explored. In this paper, we will study the existence of functionality gaps in maintenance management IT applications using data from a web-based questionnaire survey conducted in Swedish industry. Results show that the IT systems in general provide good support for maintenance management, thus low degree of functionality gaps. However, most commonly unused function was failure cause and consequence analysis and the most commonly unused information was maintenance improvement suggestions. When comparing the results with respect to type of IT system used, some significant differences was revealed, indicating that ERPsystems and production systems do not include all required information for maintenance management. Next step will be to further study the reasons behind the differences in gaps by conducting additional interviews.

Maintenance 4.0 in Railway Transportation Industry

Transportation systems are complex with respect to technology and operations with involvement in a wide range of human actors, organisations and technical solutions. For the operations and control of such complex environments, a viable solution is to apply intelligent computerised systems, such as computerised traffic control systems for coordinating airline transportation, or advanced monitoring and diagnostic systems in vehicles. Moreover, transportation assets cannot compromise the safety of the passengers by applying operation and maintenance activities. Indeed safety becomes a more difficult goal to achieve using traditional maintenance strategies and computerised solutions come into the picture as the only option to deal with complex systems interacting among them trying to balance the growth in technical complexity together with stable and acceptable dependability indexes. Industry 4.0 is a term that describes the fourth generation of industrial activity which is enabled by smart systems and Internet-based solutions. Two of the characteristic features of Industry 4.0 are computerization by utilising cyber-physical systems and intelligent factories that are based on the concept of “internet of things”. Maintenance is one of the application areas, referred to as maintenance 4.0, in form of self-learning and smart systems that predicts failure, makes diagnosis and triggers maintenance by making use of “internet of things”. This paper discusses the possibilities that lie within applying the maintenance 4.0 concept in the railway transportation industry and the positive effects on technology, organisation and operations from a systems perspective.

IT practices within maintenance from a systems perspective: Study of IT utilisation within firms in Sweden

Purpose – The aim with this paper is to describe current IT practices within maintenance in Swedish industry, and to outline the future possible developments.Design/methodology/approach – The study is performed as a web‐based questionnaire survey consisting of 71 participants. A systems perspective is applied for capturing the most relevant aspects of IT utilisation.Findings – The IT practices are characterised by high use of business‐specific IT solutions, low use of company‐wide IT solutions, low IT intensity and the client‐server architecture is dominating. The purchase decision and ownership of IT is to high extent tied to the maintenance function. Moreover, IT systems are apprehended as beneficial and connected to real needs. The findings imply a decentralised IT governance form and a mainly vertical (functional) IT support.Research limitations/implications – The socio‐technical approach suggested in this paper helps us to identify which areas to study, and also shows the tight interrelationship betw...

Service Management Models for Railway Infrastructure, an Ecosystem Perspective

Up until 2001 the operation and maintenance of Swedish railway, both the railway infrastructure and the rolling stock, was basically the responsibility of Statens Jarnvagar. At this year the operation and maintenance of the Swedish railway was deregulated and as a result the number of actors increased dramatically. Also, during the period from 1990 to 2012 there was an increase in the railway transports of 42 % in train-kilometres. This put great demands on the railway infrastructure operations and service, and indications were seen that the infrastructure was deteriorating leading to delivery quality problems. In order to solve the situation several governmental investigations were initiated. In a governmental report the situation of the railway maintenance is described as problematic due to several technical as well as organisational factors, of which the lack of competition is seen as the most important. Despite several investigations, the desired delivery quality is still not reached. This paper focuses on the Swedish railway infrastructure and describes the background and current state of the Swedish railway service management by utilising a business ecosystem perspective, which lets you capture the complexity and dynamics of the surroundings. By applying this perspective, looking outside the traditional framework of suppliers and customers, important areas in need of investigation or development can be singled out. As a part of the result, the Swedish railway infrastructure industry is modelled as an ecosystem, and directions for future development is pointed out.

Big Data in Asset Management: Knowledge Discovery in Asset Data by the Means of Data Mining

Assets are complex mixes of complex systems, built from components which, over time, may fail. The ability to quickly and efficiently determine the cause of failures and propose optimum maintenance decisions, while minimizing the need for human intervention is necessary. Thus, for complex assets, much information needs to be captured and mined to assess the overall condition of the whole system. Therefore the integration of asset information is required to get an accurate health assessment of the whole system, and determine the probability of a shutdown or slowdown. Moreover, the data collected are not only huge but often dispersed across independent systems that are difficult to access, fuse and mine due to disparate nature and granularity. If the data from these independent systems are combined into a common correlated data source, this new set of information could add value to the individual data sources by the means of data mining. This paper proposes a knowledge discovery process based on CRISP-DM for failure diagnosis using big data sets. The process is exemplified by applying it on railway infrastructure assets. The proposed framework implies a progress beyond the state of the art in the development of Big Data technologies in the fields of Knowledge Discovery algorithms from heterogeneous data sources, scalable data structures, real-time communications and visualizations techniques.

Impact of IT procurement on the quality of the maintenance process: Results from a study in Swedish industry

Purpose – IT investments in maintenance are of strategic importance, but it is hard to fit the IT systems to the business demands. One possible reason could be inadequate planning and execution of ...

Business Models for After Sales Services—Current State and Future Directions

The core strategic decisions describing what, where, how and whom to make business with are defined in the business model. The business models adapted by industry have evolved as a consequence of changes in the business environment, the production processes as well as in technology, and the modern, innovative business models focus on long term relationships, performance-based and value-driven customer offers, and knowledge intensive processes. Other aspects are the increased complexity of the offer itself and a holistic perspective on the full value chain. This paper reviews the literature with respect to business models, business strategy and business innovation for postproduction activities, i.e. operations and maintenance (O&M) services. The purpose is to describe the current state within the area and based on this give directions for future research and development. Four main aspects are found as being important for the successful development of O&M service models: the mix of products and services in customer offers (bundling), relevant setup and metrics for performance-based business models and contracts, Information and Communications Technology (ICT) as an enabler and a prerequisite for business model development, and the need for a holistic view on the value chain by utilising the asset management concept.