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The changing nature of manufacturing, in recent years, is evident in industry's willingness to adopt network-connected intelligent machines in their factory development plans. A number of joint corporate/government initiatives also describe and encourage the adoption of Artificial Intelligence (AI) in the operation and management of production lines. Machine learning will have a significant role to play in the delivery of automated and intelligently supported maintenance decision-making systems. While e-maintenance practice provides aframework for internet-connected operation of maintenance practice the advent of IoT has changed the scale of internetworking and new architectures and tools are needed. While advances in sensors and sensor fusion techniques have been significant in recent years, the possibilities brought by IoT create new challenges in the scale of data and its analysis. The development of audit trail style practice for the collection of data and the provision of acomprehensive framework for its processing, analysis and use should be avaluable contribution in addressing the new data analytics challenges for maintenance created by internet connected devices. This paper proposes that further research should be conducted into audit trail collection of maintenance data, allowing future systems to enable 'Human in the loop' interactions. [ABSTRACT FROM AUTHOR]

• Smart bolts with embedded sensor to evaluate the tension with instant status information. • The information is assessed in built-in micro-controller with decision and wireless alarms. • Power needed only for microcontroller to process information and communicate in a network. • Power harvested from radio frequencies to charge batteries and avoid batteries replacement. Bolted joint technology constitutes a critical element in structures safety due to possible bolt tension looseness. The existing axial monitoring methods are mostly visual requiring human intervention. The present paper introduces a new paradigm with a new configuration of a smart bolt capable of monitoring, processing and reporting remotely on the status of its axial tension variation. The information is assessed in a built-in electronic board with decision-making followed by a wireless alarm sent instantly to a receiver to map the health of the bolts within the network. The communication is allowed both ways within the designed network of bolts in a plant. Moreover, the proposed system can be powered by wireless energy transfer, or by battery for power supply maintenance free suitable for these standalone mechatronic devices. This device can be used as a node in a network of bolts remotely monitored in a plant. [ABSTRACT FROM AUTHOR]

Submersible well pumps, widely used for groundwater, are installed at great depths which make typical maintenance actions unworkable and costly. Condition-based maintenance (CBM) through vibration monitoring could be an effective approach for these critical machines. According to ISO 10816-7 (2009) suggestions, a procedure to measure vibration was established and applied on submersible well pumps both in a test facility and in situ. Instruments and measurement location were selected and a methodology for data processing was applied in order to set maintenance alarms. The procedure was tested on several submersible well pumps directly in the testing room of one of the main producers of pumps. Measurements in a testing room made it possible to avoid problems and costs related to instrument installation in the field. In order to demonstrate the technical feasibility of the procedure also in field, the method was also applied in real groundwater plant with a special design of the measurement system, to overcome strict operational work conditions. This paper shows the experimental campaign results, which are the basis to conduct CBM on pumps, in terms of: (1) definition of the typical vibration values of new pumps, not available even by producers, plant managers and standards, and (2) identification of the parameters which influence pump vibration, fundamental to data processing and the setting of proper alarms. The procedure will also be applied for other categories of pumps, used in several industrial applications, to measure reliable vibration data and set specific alarms for maintenance interventions. [ABSTRACT FROM AUTHOR]

Microelectromechanical systems (MEMS)-based sensing networks with on-board signal processing capabilities are becoming very attractive for monitoring the condition of rotating and static equipment. Their advantages in cost and size are an important factor for deployment in a new generation of maintenance called e-maintenance. In this paper, an intelligent monitoring system for e-maintenance (IMSEM) was developed using MEMS accelerometers, a low-power microprocessor and a wireless communication module. The system has a compatible framework and interface with open system architecture for condition-based maintenance (OSA-CBM). It integrates OSA-CBM-defined functions, including a sensing module, signal processing, condition monitoring and health assessment. Thus, the developed system successfully reduced the monitoring complexity and communication overhead with human operators. The performance of IMSEM is evaluated by carrying out fault diagnostics on the rotating unbalance of a mechanical shaft driven by a direct current (DC) motor with varying load and speed. Five statistical features were calculated for 63 vibration datasets. 25 datasets were used to train a support vector machine, with a linear kernel, and the other 38 sets were used for binary classification. About 94.7% of unknown conditions were successfully classified as healthy/unhealthy based on all features, which was improved to 100% using the best three features. This has demonstrated the capability of the developed system in detecting faults and the severity of rotor unbalance, based on ISO 1940-1:2003. [ABSTRACT FROM AUTHOR]

This study covers new trends and techniques in the field of predictive maintenance, which has been superseding traditional management policies, at least in part. It also presents suggestions for how to implement a predictive maintenance programme in a factory/premise and so on. Predictive maintenance primarily involves foreseeing breakdown of the system to be maintained by detecting early signs of failure in order to make maintenance work more proactive. In addition to the aim of acting before failure, it also aims to attend to any fault, even if there is no immediate danger of failure, to ensure smooth operation and reduce energy consumption. Predictive maintenance has been adopted by various sectors in manufacturing and service industries in order to improve reliability, safety, availability, efficiency and quality as well as to protect the environment. It also has created a separate sector, which specializes in developing predictive maintenance instruments, offering dedicated predictive maintenance solutions and training predictive maintenance experts. Predictive maintenance techniques are closely associated with sensor technologies but for efficient predictive maintenance applications, a comprehensive approach, which integrates sensing with subsequent maintenance activities, is needed to be adapted in accordance with the needs of the particular organization. Recent advances in information, communication and computer technologies, such as Internet of Things and radio-frequency identifications, have been enabling predictive maintenance applications to be more efficient, applicable, affordable, and consequently more common and available for all sorts of industries. Researches on remote maintenance and e-maintenance have been supporting predictive maintenance activities especially in unsafe working environments and scattered locations. [ABSTRACT FROM AUTHOR]

Within the era of e-manufacturing and e-business, e-maintenance provides the opportunity for a new maintenance generation. E-maintenance integrates existing telemaintenance principles, with web-services and modern e-collaboration principles. Collaboration allows not only to share and exchange information but also knowledge and (e)-intelligence. This paper outlines the basic capabilities provided by e-maintenance to companies as well as describes emerging challenges to benefit from these new operational improvement opportunities

Manufacturing operations can take substantial advantage of the proactivity concept by utilising event-driven information systems, able to process the sensor data and to provide proactive recommendations. Despite the recent advances in technology and information systems and the variety of methods for prognosis, decision models for joint maintenance and inventory optimization on the basis of real-time prognostic information have not been explored. We propose a proactive event-driven decision model for joint predictive maintenance and spare parts inventory optimization which addresses the Decide phase of the “Detect- Predict- Decide- Act” model and can be embedded to an Event Driven Architecture (EDA) for real-time processing in the frame of e-maintenance concept. The proposed approach was tested in a real manufacturing scenario in automotive lighting equipment industry and proved that maintenance and inventory costs can be significantly reduced by transforming the company's maintenance strategy from time-based to Condition Based Maintenance (CBM). [ABSTRACT FROM AUTHOR]

Purpose – The purpose of this paper is to perform an extensive literature review in the area of decision making for condition-based maintenance (CBM) and identify possibilities for proactive online recommendations by considering real-time sensor data. Based on these, the paper aims at proposing a framework for proactive decision making in the context of CBM. Design/methodology/approach – Starting with the manufacturing challenges and the main principles of maintenance, the paper reviews the main frameworks and concepts regarding CBM that have been proposed in the literature. Moreover, the terms of e-maintenance, proactivity and decision making are analysed and their potential relevance to CBM is identified. Then, an extensive literature review of methods and techniques for the various steps of CBM is provided, especially for prognosis and decision support. Based on these, limitations and gaps are identified and a framework for proactive decision making in the context of CBM is proposed. Findings – In the proposed framework for proactive decision making, the CBM concept is enriched in the sense that it is structured into two components: the information space and the decision space. Moreover, it is extended in a way that decision space is further analyzed according to the types of recommendations that can be provided. Moreover, possible inputs and outputs of each step are identified. Practical implications – The paper provides a framework for CBM representing the steps that need to be followed for proactive recommendations as well as the types of recommendations that can be given. The framework can be used by maintenance management of a company in order to conduct CBM by utilizing real-time sensor data depending on the type of decision required. Originality/value – The results of the work presented in this paper form the basis for the development and implementation of proactive Decision Support System (DSS) in the context of maintenance. [ABSTRACT FROM AUTHOR]

Purpose – The purpose of this paper is to develop a multifaceted perspective on e-maintenance research and practice over 12 years from 2002 to 2013. Design/methodology/approach – A qualitative research approach is conducted through analysing e-maintenance literature published in peer-review journals from 2002 to 2013 in operations management, information systems, computer science and engineering disciplines. Findings – A multifaceted perspective that reflects evolutionary, managerial, and technological domains of e-maintenance research has been emerged and explained. In addition, stages of e-maintenance process (i.e. integration, aggregation, and prediction) tend to synchronize with organizational levels (i.e. strategic, tactical, and operational) and stimulate the value of e-maintenance practices across the enterprise. However, there are many managerial and technological challenges that inhibit successful implementation of e-maintenance system. Practical implications – The present research offers managers and vendors a frame of reference that facilitates e-maintenance adoption and implementation. In addition, there is a need for theoretical as well as empirical research in the future to validate the multifaceted perspective in the present study and to obtain more insight into the nature of e-maintenance issues in various settings. Originality/value – The present paper is one of the first attempts to bridge the gaps in a currently cluttered field of e-maintenance research. It also provides both academics and practitioners with a useful framework that sustains rigorous e-maintenance research and practice. [ABSTRACT FROM AUTHOR]

Renewable energy sources such as wind energy are available without any limitations. In order to extract this energy efficiency, the reliability of such technologies is critical if pay back periods and power generation requirements are to be met. Due to recent developments in the field of wind engineering and in particular the expansion of installed capacity around the world, the need for reliable and intelligent diagnostic tools is of greater importance. The number of offshore wind turbines installed in the seas around Britain's coasts is likely to increase from just fewer than 150-7,500 over the next 10 years with the potential cost of £10 billion. Operation and Maintenance activities are estimated to be 35 % against the cost of electricity. However, the development of appropriate and efficient maintenance strategies is currently lacking in the wind industry. The current reliability and failure modes of offshore wind turbines are known and have been used to develop preventive and corrective maintenance strategies which have done little to improve reliability. In addition, the failure of one minor component can cause escalated damage to a major component, which can increase repair and or replacement costs. A reliability centered maintenance (RCM) approach offers considerable benefit to the management of wind turbine operations since it includes an appreciation of the impact of faults on operations. Due to the high costs involved in performing maintenance and the even higher costs associated with failures and subsequent downtime and repair, it is critical that the impacts are considered when maintenance is planned. This paper provides an overview of the application of RCM and on line e-condition monitoring to wind turbine maintenance management. Unplanned maintenance levels can be reduced by increasing the reliability of the gear box and individual gears through the analysis of lubricants. Finally the paper will discuss the development of a complete sensor-based processing unit that can continuously monitor the wind turbines lubricated systems and provide, via wireless technology, real time data enabling on shore staff with the ability to predict degradation anticipate problems and take remedial action before damage and failure occurs. [ABSTRACT FROM AUTHOR]

An equipment monitoring and e-maintenance information system prototype customised for the robotic production capabilities is presented in this paper. Such an infrastructure enables stakeholders from the robotic field to share and take advantage of maintenance knowledge, create virtual monitoring rooms for remote management used to track equipment performing in real production environment over the life cycle. An ontology-based representation model is developed and used in a prototype for the sharing and use of maintenance knowledge related to the robotic field. The prototype can be dynamically scaled on a hybrid cloud computing infrastructure in order to fit the needs for maintenance and monitoring of other type of production equipment. [ABSTRACT FROM AUTHOR]

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 between different factors, layers and systems. Practical implications - The study results could be used for benchmarking purposes or to highlight state-of-the-art of IT utilisation in maintenance, and thereby set the topic on the corporate agenda. Originality/value - Studies describing IT utilisation within maintenance in the form of case studies and surveys exist, but they mainly focus on one aspect. This study approached the problem from a socio-technical perspective, covering several aspects connected to IT utilisation. [ABSTRACT FROM AUTHOR]

Effective and efficient maintenance requires proper information logistics, which can be delivered through eMaintenance solutions. An eMaintenance solution provides services for data acquisition, data processing, data aggregation, data analysis, data visualization, context-sensing, etc. The development of eMaintenance solutions faces challenges and one of these challenges is how to ensure a high quality of data. Data Quality (DQ) concerns all the phases of the maintenance process. Hence, the purpose of this paper was to explore and identify the aspects of DQ in eMaintenance. To achieve this, seven case studies, within three industries, were conducted. The empirical data was collected through interviews, observations, archival records and workshops. In this paper, the different aspects related to DQ were presented with their relationship to the phases of a generic maintenance process. Furthermore, the DQ issues have been related to how data is generated, either by manual input (Human-generated) and/or automatic input (Machine-generated). One of the main findings of this paper shows that the organizations do not often implement maintenance solutions whole-heartedly, thus, the application of the systems never are used to their full potential. [ABSTRACT FROM AUTHOR]

Approaches to service design share human–computer interaction's (HCI's) commitment to developing with and for people useful, usable and accessible services. However, there has been little explicit interaction between the emerging service sciences and the interaction design communities. This article explores HCI's actual position and opportunities to service design and requirements and vice versa. We propose a design framework for service-oriented interactive systems integrating the concept of persona. This enables to extract relevant elements towards deriving the design of the main functionalities of the user interface. This framework is applied to a case study of the e-maintenance of an agro-alimentary group. [ABSTRACT FROM AUTHOR]