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ENLIGT HEMSIDAN ”www.phrases.org.uk”(2016-02-25) myntade författaren Daniel Defoe frasen ’döden och skatter’ år 1726 och fler har sedan följt i hans fotspår. En av de kanske mest kända formuleringarna kom till i ett samtal mellan Benjamin Franklin och Jean-Baptiste Leroy (1789): ”I denna värld kan ingenting sägas vara säkert, utom döden och skatterna.” (fritt översatt från engelska). Vi har även funnit en person som använt det här uttrycket kopplat till underhåll, nämligen Kevin Marshall som diskuterar underhåll av hyreshus: ”...döden, skatter och underhåll.” (”www.flat-living.co.uk”, 2016-02-25). Underhåll i någon av alla dess former är någonting alla människor på jorden upplever nästan dagligen, medvetet eller omedvetet. Det finns egentligen bara ett sätt att tackla detta – med ett leende på läpparna. Man behöver dock inte vara slösaktig. På samma sätt som väldigt få vill betala mer i skatt än vad lagen kräver så vill sällan någon betala mer för underhåll än vad nöden kräver. Det är vad denna handbok handlar om. Den vänder sig till tillverkande företag som önskar minska sina underhållsrelaterade slöserier, och därför har behov av att se över sin verksamhet. Boken vänder sig i första hand till ledningsgrupper för underhåll, underhållschefer och underhållsutvecklare/ingenjörer. Dock, för att citera en av våra samarbetspartners: ”Det är ett slöseri om bara anställda inom underhållsavdelningen läser boken.” För att nå ett hållbart resultat är vi övertygade om att medvetenheten om slöserier och underhållsrelaterade slöserier behöver höjas bland samtliga anställda i en verksamhet. Detta är anledningen till att vi vill att du använder handboken. Vi uppmanar till att du läser exemplen och diskuterar frågorna med medarbetare inom hela underhållsavdelningen, och gärna tvärfunktionellt med produktion och övriga stödfunktioner. Vårt mål är att ge vägledning för hur tillverkande företag kan arbeta med underhållsrelaterade slöserier. Boken klargör vad sådana slöserier är, samt tips och idéer på hur man kan identifiera, klassificera och kvantifiera dem. Handboken presenterar även en arbetsprocess för att minska eller ta bort underhållsrelaterade slöserier så kostnadseffektivt som möjligt. Den innehåller också korta teoriavsnitt med exempel från praktiken och frågor som ledningsgrupper och anställda inom verksamheten kan diskutera. Genom att följa arbetsprocessen kan du och ditt företag få ökad medvetenhet och förståelse för underhållsrelaterade slöserier inom er egen verksamhet. Handboken fokuserar främst på de tidiga stegen i processen eftersom de är mest avgörande för ett lyckat resultat. Underhållsrelaterade slöserier är delvis unika för varje företag. Tyvärr finns inga genvägar eller standarder för att minska eller ta bort dem. Att endast läsa handboken kommer inte att ge något resultat. Den här boken bygger på att du och ditt företag aktivt finner er egen väg för att minska eller ta bort de underhållsrelaterade slöserier ni upptäcker i er verksamhet.

The growth of global competition has led to remarkable changes in the way manufacturing companies operate. These changes have affected maintenance and made its role even more crucial for business success. To remain competitive, manufacturing companies must continuously increase the effectiveness and efficiency of their production processes. Furthermore, the introduction of lean manufacturing has increased concerns regarding equipment availability and, therefore, the demand for effective maintenance. That maintenance is becoming more important for the manufacturing industry is evident in current discussions on national industrialization agendas. Digitalization, the industrial internet of things (IoT) and their connections to sustainable production are identified as key enablers for increasing the number of jobs in industry. Agendas such as “Industry 4.0” in Germany and “Smart Industry” in Sweden are promoting the connection of physical items such as sensors, devices and enterprise assets, both to each other and to the internet. Machines, systems, manufactured parts and humans will be closely interlinked to collaborative actions. Every physical object will formulate a cyber-physical system (CPS), and it will constantly be linked to its digital fingerprint and to intensive connection with the surrounding CPSs of its on-going processes.

That said, despite the increasing demand for reliable production equipment, few manufacturing companies pursue the development of strategic maintenance. Moreover, traditional maintenance strategies, such as corrective maintenance, are no longer sufficient to satisfy industrial needs, such as reducing failures and degradations of manufacturing systems to the greatest possible extent. The concept of maintenance has evolved over the last few decades from a corrective approach (maintenance actions after a failure) to a preventive approach (maintenance actions to prevent the failure). Strategies and concepts such as condition based maintenance (CBM) have thus evolved to support this ideal outcome. CBM is a set of maintenance actions based on the real-time or near real-time assessment of equipment conditions, which is obtained from embedded sensors and/or external tests and measurements, taken by portable equipment and/or subjective condition monitoring. CBM is increasingly recognized as the most efficient strategy for performing maintenance in a wide variety of industries. However, the practical implementation of advanced maintenance technologies, such as CBM, is relatively limited in the manufacturing industry.

Based on the discussion above, the objective of this research is to provide frameworks and guidelines to support the development and implementation of condition based maintenance in manufacturing companies.  This thesis will begin with an overall analysis of maintenance management to identify factors needed to strategically manage production maintenance. It will continue with a focus on CBM to illustrate how CBM could be valued in manufacturing companies and what the influencing factors to implement CBM are. The data were collected through case studies, mainly at one major automotive manufacturing site in Sweden. The bulk of the data was collected during a pilot CBM implementation project. Following the findings from these efforts, a formulated maintenance strategy is developed and presented, and factors to evaluate CBM cost effectiveness are assessed. These factors indicate the benefits of CBM, mostly with regard to reducing the probability of experiencing maximal damage to production equipment and reducing production losses, particularly at high production volumes. Furthermore, a process of CBM implementation is presented. Some of the main elements in the process are the selection of the components to be monitored, the techniques and technologies for condition monitoring and their installation and, finally, the analysis of the results of condition monitoring. Furthermore, CBM of machine tools is presented and discussed in this thesis, focusing on the use of vibration monitoring technique to monitor the condition of machine tool spindle units.

The growth of global competition caused remarkable changes in the way manufacturing companies operate. These changes have affected maintenance and made its role even more crucial in business success. In order to stay competitive, manufacturing companies need to continuously increase the effectiveness and efficiency of their production processes. Further, by introducing lean manufacturing the concern about equipment availability is increased and so, the demand for effective maintenance. Despite the increasing demand on reliable production equipment, few manufacturing companies work with strategic maintenance development. Moreover, conventional maintenance strategies such as corrective maintenance are not sufficient today to fulfill the industrial needs on maximum reduction of failures and degradations of manufacturing systems. The concept of maintenance has evolved over the last few decades from a corrective attitude (maintenance intervention after a failure), to a predictive attitude (maintenance intervention fixed to prevent the fault). Strategies and concepts such as Condition Based Maintenance (CBM) have thus evolved to support this ideal situation. CBM is a set of maintenance actions based on real-time or near real-time assessment of equipment condition, which is obtained from embedded sensors and/or external tests and measurements taken by portable equipment and/or subjective condition monitoring. CBM is becoming recognized as the most efficient strategy for carrying out maintenance in a wide variety of industries. However, the practical implementation of advanced maintenance technologies, such as CBM, in manufacturing industry is more scarce.

Therefore, the objective with this research is to study on how to implement and develop an effective and efficient CBM strategy in manufacturing industry. This thesis will start with an analysis of the overall maintenance management to illustrate how to formulate a maintenance strategy, following with the focus on CBM; cost effectiveness of implementing CBM; an introductory review of applied CBM practices and CBM implementation process, all in manufacturing industry. The data was collected through case studies mainly at one major manufacturing site. The main part of the data was collected during a pilot project to implement CBM. As the result, a formulated maintenance strategy has been developed and presented. Factors to evaluate CBM cost effectiveness have been assessed. These factors indicate the benefits of CBM mostly in reducing probability of having maximal damage in production equipment and reducing production losses particularly in high production volumes. Further, a process of CBM implementation has been presented. Some of the main elements in the process are selection of the components to be monitored, techniques and technologies as well as installation of the technologies and finally how to analyze the results from the condition monitoring.

Machine tools cannot produce accurate parts if performance degradation due to wear in their subsystems (e.g., spindle units) is not identified and con-trolled. Appropriate maintenance actions delay possible deterioration and mini-mize machining system stoppage time that leads to lower productivity and higher production cost. Measuring and monitoring machine tool condition has become increasingly important because of the introduction of agile production and in-creased requirements for product accuracy. Condition Based Maintenance (CBM) techniques, such as vibration monitoring, are becoming a very attractive method for companies operating high-value machines and components. One of the most common problems of rotating equipment, such as machine tool spindle units, is the condition of bearings. Vibration analysis can diagnose bearing damage by measuring the overall vibration of a spindle or, more precisely, by high-frequency techniques such as enveloping. This paper focuses on the use of vibration analysis to monitor and analyse the condition of machine tool spindle units. The method is a case study at a manufacturing company in Sweden. CBM, using vibration moni-toring, is implemented on different types of machine tools. The results of the im-plementation, as well as a vibration analysis of a spindle unit and its cost effec-tiveness, are presented in the paper.

Vibration analysis and the Shock Pulse Method (SPM) are two of the most popular condition monitoring techniques used in Condition-Based Maintenance (CBM) policy, especially for rotating equipment. To illustrate the extent to which advanced CBM techniques (in this case, vibration analysis and SPM) are applicable and cost effective in a manufacturing company, a pilot project was followed in real time. The pilot project was performed at a large manufacturing site in Sweden. The purpose of the project was to implement online condition monitoring of five critical gas circulation fans in the hardening process of the manufacturing company. This paper presents some of the main findings of the online condition monitoring of the fans for a period of three years. Consequently, based on the empirical data, the company was able to gain great profit due to preventing production losses by preventing breakdowns of the fans.

Vibration analysis and the Shock Pulse Method (SPM) are two of the most popular condition monitoring techniques used in Condition-Based Maintenance (CBM) policy, especially for rotating equipment. To illustrate the extent to which advanced CBM techniques (in this case, vibration analysis and SPM) are applicable and cost effective in a manufacturing company, a pilot pro-ject was followed in real time. The pilot project was performed at a large manu-facturing site in Sweden. The purpose of the project was to implement online condition monitoring of five critical gas circulation fans in the hardening pro-cess of the manufacturing company. This paper presents some of the main findings of the online condition monitor-ing of the fans for a period of two years. Consequently, based on the empirical data, the company was able to gain great profit due to preventing production losses by preventing breakdowns of the fans.

Machining systems (i.e., machine tools, cutting processes and their interaction) cannot produce accurate parts if performance degradation due to wear in their subsystems (e.g., feed-drive systems and spindle units) is not identified, monitored and controlled. Appropriate maintenance actions delay the possible deterioration and minimize/avoids the machining system stoppage time that leads to lower productivity and higher production cost. Moreover, measuring and monitoring machine tool condition has become increasingly important due to the introduction of agile production, increased accuracy requirements for products and customers' requirements for quality assurance. Condition Based Maintenance (CBM) practices, such as vibration monitoring of machine tool spindle units, are therefore becoming a very attractive, but still challenging, method for companies operating high-value machines and components. CBM is being used to plan for maintenance action based on the condition of the machines and to prevent failures by solving the problems in advance as well as controlling the accuracy of the machining operations. By increasing the knowledge in this area, companies can save money through fewer acute breakdowns, reduction in inventory cost, reduction in repair times, and an increase in the robustness of the manufacturing processes leading to more predictable manufacturing. Hence, the CBM of machine tools ensures the basic conditions to deliver the right ability or capability of the right machine at the right time. One of the most common problems of rotating equipment such as spindles is the bearing condition (due to wear of the bearings). Failure of the bearings can cause major damage in a spindle. Vibration analysis is able to diagnose bearing failures by measuring the overall vibration of a spindle or, more precisely, by frequency analysis. Several factors should be taken into consideration to perform vibration monitoring on a machine tool's spindle. Some of these factors are as follows: the sensor type/sensitivity, number of sensors to be installed on the spindle in different directions, positioning of the vibration accelerometers, frequency range to be measured, resonance frequency, spindle rotational speed during the measurements, measurement condition, including the no-load condition with tool clamped or without a tool, measuring tools and technologies, automatic or manual run of measurement, measurement routine, warning limits, and data handling and analysis, among other factors. The aim of this paper is thus to address CBM and particularly the implementation in the manufacturing industries focusing on the use of vibration monitoring techniques to monitor the condition of the machine tools' spindle units. To conduct this study, a pilot project was followed in real time. The pilot project was performed at a manufacturing company in Sweden. The company's product is gearboxes for the automotive industry, with a production volume of approximately 135,000 units per year. CBM, by online and off-line condition monitoring, using vibration monitoring, has been implemented on different types of machine tools, including horizontal and vertical turning machines, multi-task milling machines and grinding machines.

This paper presents a proposed guide for analysis of the costs and benefits of implementing Condition Based Maintenance (CBM) in manufacturing industry. The guide will be exemplified with results from a case study performed in a real CBM implementation in hardening and machining processes in a large manufacturing facility. The result indicates factors that ought to be taken into consideration in order to evaluate both the cost of implementing CBM and its benefits. These factors indicate the benefits of CBM mostly by reducing the losses due to damage in the production equipment, including capital loss, production loss, quality loss, environmental loss, safety loss etc. By analyzing the empirical data, the most potential savings by implementing CBM are presented as; reducing the probability of having maximal damage in the production equipment and, reducing production losses particularly in high production volumes.

This paper presents a guide for implementation of Condition Based Maintenance (CBM) in a manufacturing industry, considering the technical constituents and organizational aspects when implementing CBM. The empirical base for the study is a case study from a major manufacturing site in Sweden. The data was collected during a pilot project to implement CBM at the case company. The purpose of the pilot study at the company was to implement online condition monitoring on some of the critical components in the hardening process. Hereby, two of the main online condition monitoring techniques namely vibration analysis and Shock Pulse Method (SPM) have been implemented and tested on electric motors to monitor bearing conditions. The paper presents the process of implementation and the elements included in this process. Some of the main elements in the implementation process are selection of the components to be monitored, techniques and technologies as well as installation of the technologies and finally how to analyze the results from the condition monitoring. The data from online condition monitoring on the electric motors, driving the furnace fans, are recorded and presented in the paper including breakdown data on two objects. This information is leading to useful and reliable knowledge for maintenance work to be cost effective and be able to increase the overall equipment availability (OEA). In addition to this, the result indicates to what extent advanced CBM practices are applicable in the hardening environment in the manufacturing company and it provides guidance for further research and development in this area. The paper concludes with a discussion on possible future trends and research areas, needed to increase the effective and efficient use of CBM.

This article demonstrates the feasibility of the convolutional neural network (CNN) and pulse transit time (PTT)-based approach in estimating the systolic blood pressure (SBP) and diastolic blood pressure (DBP). Electrocardiogram (ECG) and photoplethysmography (PPG) signals were employed to calculate the PTT, which is the time delay between the R-wave peak Rof ECG, and specific points of the PPG waveforms. Then, the Blood pressure (BP), which is inversely related to PTT was estimated. A total of 22 patients with available ECG, PPG and SBP data were selected from the Medical Information Mart for Intensive Care (MIMIC III) dataset to validate the proposed model. A window of five minutes of recoding was chosen for each patient. Duration of each cardiac cycle was around 0.6 s, centred at R-peaks and sampled at 125 Hz. A CNN-based model was developed with four convolutional layers. The results showed that the average root mean square error (RMSE) of 5.42 mmHg and 7.81 mmHg were achieved for SBP and DBP, respectively.

This paper is written based on the need for Computerized Maintenance Management System’s (CMMS) decision analysis capability to achieve world class status in maintenance management. Investigations indicate that decision analysis capability is often missing in existing CMMSs and collected data in the systems are not completely utilized. How to utilize the gathered data to provide guidelines for maintenance engineers and managers to make proper maintenance decisions has always been a crucial question. In order to provide decision support capability, the aim of this paper is to provide and examine three different decision making techniques which can be linked to CMMS and add value to collected data. This research has been conducted within a global project in a large manufacturing site in Sweden to provide a new maintenance management system for the company. The data from the main studies were collected through document analysis complemented by discussions with maintenance engineers and managers at the case company to verify the data. Methods including a Multiple Criteria Decision Making (MCDM) technique called TOPSIS, k-means clustering technique, and one decision making model borrowed from the literature were used. The results indicate the most appropriate maintenance decision for each of the selected machines/parts according to factors such as frequency of breakdowns, downtime, and cost of repairing. The paper concludes with a comparison of results obtained from the different decision making techniques and also a discussion on possible improvements needed to increase the capability of the maintenance decision making models.

In recent decades, by introducing lean manufacturing the vulnerability to system disturbances has increased and so, the demand for dependable production equipment. The need for having high production equipment availability causes companies to need a more effective and efficient maintenance strategy in order to stay competitive. Despite the increasing demand on reliable production equipment, few manufacturing companies work with strategic maintenance development and a large part of the manufacturing industry lack clear maintenance strategies. It is therefore difficult to develop the maintenance work in accordance with the strategic goals of the manufacturing companies. The main objective of this paper is to define a process for formulating maintenance strategy in order to facilitate further development in a strategic way. The problem has been studied by literature review and through case study at one major manufacturing site in Sweden to investigate the company’s view on strategic maintenance development. Hence, a formulated maintenance strategy has been provided and presented. The company’s overall goals considered and translated to the strategic objective of maintenance. Moreover, balanced score card is used as a tool to make a framework of the maintenance strategy. As a result of this study, the company could easily formulate a maintenance strategy by using a simple process based on the tools that they have already used. In addition to this, the result indicated how maintenance strategy can contribute to the company’s business goals.

In recent decades, by introducing lean manufacturing the vulnerability to system disturbances has increased and so, the demand for dependable production equipment. The need for having high production equipment availability causes companies to need a more effective and efficient maintenance strategy in order to stay competitive. Despite the increasing demand on reliable production equipment, few manufacturing companies work with strategic maintenance development and a large part of the manufacturing industry lack clear maintenance strategies. It is therefore difficult to develop the maintenance work in accordance with the strategic goals of the manufacturing companies.

The main objective of this paper is to define a process for formulating maintenance strategy in order to facilitate further development in a strategic way. The problem has been studied by literature review and through case study at one major manufacturing site in Sweden to investigate the company’s view on strategic maintenance development. Hence, a formulated maintenance strategy has been provided and presented. The company’s overall goals considered and translated to the strategic objective of maintenance. Moreover, balanced score card is used as a tool to make a framework of the maintenance strategy. As a result of this study, the company could easily formulate a maintenance strategy by using a simple process based on the tools that they have already used. In addition to this, the result indicated how maintenance strategy can contribute to the company’s business goals.

This paper presents an introductory review of CBM practice applied in manufacturing industry, focusing the technical constituents within condition monitoring. The empirical base for the study is a case study of two major manufacturing sites in Sweden, complemented with a brief benchmark of data from two reference manufacturing sites from France and Brazil. The data from the main studies were collected by interviews and document analysis. The result indicates that there is a wide range within current practice of applying CBM. The implementations are dependent on process type (machining, assembly or heat treatment) and product type. By analysing the empirical data, gaps and challenges for implementing CBM in industry are presented, primarily focusing condition monitoring within manufacturing industry. The paper concludes with a discussion on possible future trends and research areas, needed to increase the industrial use of CBM.

This paper addresses the controversial gap between the environmental perspective and the cost perspective in a manufacturing context. The results of an empirical study on the heat treatment and phosphating processes performed by a manufacturing company indicate that implementing condition-based maintenance contributes not only to cost savings by preventing production losses and reducing equipment downtime but also to a more efficient use of resources by avoiding the generation of scraps and material wastage.

Ranking life insurance firms, particularly regarding customer-oriented criteria, has become a significant research priority of many insurance research centers. This is mainly due to the effective role of life insurance in improving the capital market and the role of service quality in customer satisfaction. This issue has remained one of the major topics associated with insurance industry which has not been sufficiently explored in the literature. This study aims at prioritizing insurance firms which hold the majority proportion of Iran's total life insurance market. Life insurers are assessed and ranked with regard to 5 criteria of customer service quality in the SERVQUAL model as well as opinions of 43 qualified insurance brokers in Tehran, Iran. Fuzzy Analytic Hierarchy Process (FAHP) is utilized to determine the importance weight of each criterion of the SERVQUAL (service quality) model. After which, the Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (Fuzzy TOPSIS) is applied in order to rank the firms. Both Multiple Attribute Decision Making (MADM) methods are conducted in the fuzzy environment to handle the uncertainty and impreciseness of one's subjective judgments. The results revealed the ranking of 13 Iranian insurance companies in the context of life insurance. 

The growth of world-class manufacturing companies and global competition caused significant changes in the way of manufacturing companies operation. These changes have affected maintenance and made its role even more crucial to stay ahead of the competition. Maintenance strategy selection is one of the strategic decision-making issues that manufacturing companies in the current competitive world are facing. In this paper, a comparison between different Multiple Criteria Decision Making (MCDM) approaches is conducted in a dairy manufacturing factory to rank the maintenance strategies. The aim is to suggest an appropriate approach for the best selection of the maintenance strategy. The decision-making elements including evaluation criteria/sub-criteria and problem alternatives, i.e., maintenance strategies are determined and a group of experts from the case-study factory are asked to make their pair-wise comparisons. The pair-wise comparison matrix is constructed by using the crisp and triangular fuzzy numbers, while the aggregation of individual priorities (AIP) approach is utilized to aggregate the decision-makers’ judgments. The priority vectors of decision elements are calculated by Mikhailov’s fuzzy preference programming (FPP) methods and the final weights of the decision elements are found. Results show that when the effectiveness of one element on the other elements is higher, it will have greater weights; and therefore, the results from the analytic network process (ANP) method is completely different from those of the analytic hierarchy process (AHP). The reason for these differences between the AHP and Fuzzy AHP (FAHP) with the ANP and Fuzzy ANP (FANP) is that the methods of AHP and FAHP evaluate the criteria only based on the level of importance and do not consider the interdependencies and interactions among the evaluation elements. In this research, a predictive maintenance is selected as the most appropriate strategy in the case company and the preventive strategies outperformed the corrective strategies. The results of this research are consistent with the results of previous studies found in the literature.

Optimally locating new bank branches is a strategic decision in banking industry in order to stay competitive. The importance of this issue is primarily due to the fact that locating branches in appropriate sites is one of the main factors in absorbing and satisfying bank customers. This results in a core benefit for banks, particularly in a vibrant competition. In addition, without a set of well-chosen selection criteria and their prominence, the goal of locating suitable sites for bank branches would not be efficiently achieved. In this research, six most widely used criteria for bank branch location consideration are obtained from the literature review. These criteria include demographic attributes, access to public facilities, transportation, competition, cost and flexibility. In order to prioritize these criteria, an integrated methodology of the intuitionistic fuzzy set theory as well as Decision Making Trial and Evaluation Laboratory Model (DEMATEL) technique (i.e. IFDEMATEL) are utilized. The DEMATEL technique considers interrelationships between criteria. Furthermore, the intuitionistic fuzzy set theory, which has some advantages over fuzzy set theory, to include the vagueness and imprecision of subjective judgments of specialists is applied. As a case study, a well-known Iranian public bank in the city of Rasht, Iran is considered. Consequently, the obtained ranks from the integrated method provide useful information for bank managers in determining efficient locations of their new branches.