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This paper presents a concept for digitalised maintenance (DM), maps the conceptualised DM to maintenance problems in industries and highlights challenges that might be faced when realizing this concept.

First, maintenance problems that are faced by the industry are presented, followed by a conceptualisation of DM. Next, a typical operational scenario is used as an exemplification to show system dynamics. The characteristics of this conceptualised DM are then mapped to the identified maintenance problems of industry. Then, interesting initiatives in this domain are highlighted, and finally, the challenges to realize this approach are discussed.

This paper identified a set of problems related to maintenance in industry. In order to solve current industrial problems, exploit emerging digital technologies and elevate future industries, it will be necessary to develop new maintenance approaches. The mapping between the criteria of DM and maintenance problems shows the potential of this concept and gives a reason to examine it empirically in future work.

This paper aims to help maintenance professionals from both academia and industry to understand and reflect on the problems related to maintenance, as well as to comprehend the requirements of a digitalised maintenance and challenges that may arise.

The purpose of this paper is to develop the steps required for establishing and running cost‐effective condition‐based maintenance (CBM) exemplified for vibration‐based maintenance (VBM) and compared with real implementations in case companies.

The study is based on published knowledge and experience within condition monitoring (CM) and CBM, and three case studies.

The study has shown that all three case companies are in a big need for systematic procedures for doing right things right, in the right time cost‐effectively (establishing and running a cost‐effective CBM).

The paper focuses on development of cost‐effective CBM exemplified for VBM. Also, the case companies belong to three branches: paper and pulp mills, energy producer and engineering manufacturing. The case companies have different levels in applying CBM/VBM, experience and knowledge in CM and CBM.

Systematic procedures for establishing CBM/VBM policy are developed, motivated and discussed in a way which enables the user to establish and run CBM/VBM policy cost‐effectively.

The steps of establishment of CBM/VBM provide a unique model for companies to establish and run cost‐effective maintenance its originality.

The purpose of this paper is to examine the role of maintenance in improving company's competitiveness and profitability. In the first part the paper aims to discuss the potential improvement areas from the company perspective. Second part of this paper examines maintenance impact on company's business.

An empirical case study was utilized aiming to provide an understanding of the role of maintenance in improving company's business. The empirical data for this study were collected from a Slovenian textile company. A gap analysis was used in order to address the research problem and to identify potential improvement areas.

Based on the gap analysis, the results suggest that from respondents’ points of view, maintenance practices related to condition-based maintenance approach represent the highest opportunity for improvement. The most notable empirical results of the case study showed that around 3 per cent of additional profit could be generated at weaving machine, especially if all unplanned stoppages and loss of quality due to decrease in the productivity would be prevented.

This paper demonstrates to managers the potential benefits of maintenance policy in terms of productivity, quality and profitability. In this regard, this paper builds on a premise that company can gain higher performance benefits using more effective maintenance policy.

The proposed conceptual model contributes to the existing literature by showing the interactions between maintenance and company's competitiveness and profitability. Empirical findings of this study therefore, acknowledge maintenance's potential of increasing the overall profit. In addition this study advances prior studies by utilizing a gap analysis which is rare in this type of research.

To develop and test a model and software‐based support system for better understanding of the interactions between man‐machine‐maintenance‐economy (MMME), and enable cost‐effective decisions.

The study is based on published knowledge and experience within maintenance, maintenance organization and production, and a case study.

Development of a model describing interactions between man‐machine‐maintenance‐economy interactions and MMME software module. MMME test shows its ability to identify, quantify, assess and follow up losses in production time which is necessary when planning effective maintenance actions.

In the paper the focus is to quantify production time losses in order to identify the root causes of the problem. The case study is performed at a manufacturing plant for truck engines.

A systematic approach of how to quantify and evaluate losses in production time in order to identify problems and problem areas within the production. This approach is discussed and motivated with the aim of achieving more cost‐effective decisions in maintenance.

The model and software application developed enables a structured way of analyzing production time losses in order to find cost‐effective solutions to the problems. The model is very flexible enabling it to be customized for a wide spectrum of branches.

Rolling element bearing failures in paper mill machines are considered in relation to their critical role in the machine function. The use of expensive, sophisticated and highly automated equipment and machines and the intention to achieve higher quality products, longer machine life, higher machinery effectiveness and safer operating processes were the main driving force motivating efforts to improve the maintenance concept during the last 50 years. In this paper, a conceptual model that integrates the available condition information, the deterministic models used in condition monitoring based upon mechanical theory and the probabilistic models used in the area of operational research is developed and its applicability is discussed. This model covers fault detection of a mechanical component such as a rolling element bearing, prediction of its vibration level in the near future, assessment of the probability of failure of a component over a finite period of time of interest.

Relevant and reliable data from the surroundings in addition to the vibration measurements are required to achieve effective diagnosis and prognosis when a vibration‐based maintenance (VBM) policy is used. The main conclusion is that the variation in the machine load and speeds influences the amplitudes of rolling element bearing defect frequencies. Therefore, changes in the machine speed and load should be considered when interpreting vibration spectra. This will improve the effectiveness and accuracy of fault diagnosis and prediction of the time to maintenance action. The paper classifies stoppage times and highlights the reasons behind them. Also, it discusses the consequential economic losses incurred by unplanned stoppages. During the period covered by this study (58 days), the total stoppage time was about 76.6 days and caused appreciable economic losses of about 2.3 million SEK.

The problem addressed in this paper is how to utilise the concept of TQMain to develop an integrated vibration‐based maintenance (VBM) for detecting deviations in the machine condition and product quality (technical specifications) before the machine starts manufacturing defective items. Concepts of TQMain and integrated VBM are discussed. A technical analysis is conducted to identify quality problem cause roots when manufacturing crankshafts in Volvo Motor, Sko¨vde, Sweden. A factorial experiment is conducted to assess the effect and significance of the suspected causes. Vibration measurements from seven points are collected. The major conclusion of this study is: when using an effective, e.g. on the basis of TQMain concept, integrated VBM, deviations in product quality can be detected at an earlier stage than when using usual quality control diagrams. Manufacturing defective items can be reduced dramatically (or prevented), which will eliminate bad quality‐related losses.

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.

The reputation of an organisation is often built through hard work on improving quality, reliability, delivery time and price. In this paper a graphical method for the selection of a cost‐effective monitoring technique is suggested. This graphical method is also used to select the most cost‐effective replacement vibration level, when a vibration‐based maintenance is implemented, i.e. when the available data are mainly condition‐based replacement. This method is based on the concept of the total time on test, TTT‐plot. The use of this method is explained by three examples.

In manufacturing systems intelligent techniques are being used to integrate and interpret data from multiple sensors to predict tool wear and tool life. Less attention is devoted to developments of integrated condition monitoring systems, which enable the user to evaluate a multi‐variant system based on the data collected from, e.g. maintenance, quality, production, etc. In this paper we discussed different approaches of how to keep availability, quality and productivity at high levels. Also, we proposed a new approach for an expert system concept, which is characterised by using a total quality maintenance (TQMain) concept; having a common database, and a continuously improved knowledge base with an intelligent inference engine. It can enhance data reliability, decision making certainty, remove the redundancy in monitoring systems, and allow the user to detect and eliminate reasons behind variations through effective diagnosis and prognosis. This will enhance the performance‐efficiency, availability and quality rate, i.e. overall equipment effectiveness of the manufacturing systems.