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This paper reviews the literature on maintenance strategies for energy efficiency as a potential maintenance approach. The purpose of this paper is to identify the main concept and common principle for each maintenance strategy for energy efficiency.

A literature review has been carried out on maintenance and energy efficiency. The paper systematically classified the literature into three maintenance strategies (e.g. inspection-based maintenance [IBM], time-based maintenance [TBM] and condition-based maintenance [CBM]). The concept and principle of each maintenance strategy are identified, compared and discussed.

Each maintenance strategy's main concept and principle are identified based on the following criteria: data required and collection, data analysis/modeling and decision-making. IBM relies on human senses and common senses to detect energy faults. Any detected energy losses are quantified to energy cost. A payback period analysis is commonly used to justify corrective actions. On the other hand, CBM monitors relevant parameters that indicate energy performance indicators (EnPIs). Data analysis or deterioration modeling is needed to identify energy degradation. For the diagnostics approach, the energy degradation is compared with the threshold to justify corrective maintenance. The prognostics approach estimates when energy degradation reaches its threshold; therefore, proper maintenance tasks can be planned. On the other hand, TBM uses historical data from energy monitoring. Data analysis or deterioration modeling is required to identify degradation. Further analysis is performed to find the optimal time to perform a maintenance task. The comparison between housekeeping, IBM and CBM is also discussed and presented.

The literature on the classification of maintenance strategies for energy efficiency has been limited. On the other hand, the ISO 50001 energy management systems standard shows the importance of maintenance for energy efficiency (MFEE). Therefore, to bridge the gap between research and industry, the proposed concept and principle of maintenance strategies will be helpful for practitioners to apply maintenance strategies as energy conservation measures in implementing ISO 50001 standard.

The novelty of this paper is in-depth discussion on the concept and principle of each maintenance strategy (e.g. housekeeping or IBM, TBM and CBM) for energy efficiency. The relevant literature for each maintenance strategy was also summarized. In addition, basic rules for maintenance strategy selection are also proposed.

While pursuing energy management, firms simultaneously strive to boost sales as a path towards economic performance. Also, the literature suggests that family firms exhibit greater environmental commitment than their non-family counterparts. To examine these contentions, this review espouses contingency theory to interrogate the correlations of (1) energy consumption targets, (2) energy efficiency enhancing measures, (3) energy consumption monitoring and (4) the domestic sales performance of small family firms in Turkey's food sector.

Data were sourced from the World Bank Enterprise Survey. A sample of 137 family firms in food production, processing and retail was analysed using non-linear structural equation modelling. Path coefficients were determined to estimate the extent to which energy management practices predict domestic sales.

The path analysis revealed that although energy consumption targets do not directly increase sales performance, they stimulate firms' energy efficiency enhancement measures and energy consumption monitoring to produce this effect by 21%.

The contingency lens espoused leaves room to capture further antecedents in small family food firms' technical, managerial, ownership, operational and architectural configuration that may also interact with or predict the propensity for energy management.

For practitioners, the inherent findings demonstrate that there are firm-specific material benefits arising from adopting energy management practices. And, although small firms such as family food businesses may have low energy intensities, they can improve their sales performance by setting energy targets, installing energy efficiency enhancing measures and embarking on energy consumption monitoring.

Public stakeholders in Turkey such as the Ministry of Energy and Natural Resources, the General Directorate of Energy Affairs and affiliate institutions can reflect on these findings to develop a coherent national energy management policy for small firms. Such initiatives are especially relevant to Turkey and its ambitions to join the EU which requires member states to set up a national energy efficiency action plan.

This inquiry is one of the first to examine energy management in the food sector at the family firm level through the contingency lens. Theoretically, the results draw attention and shed new light on disparate energy management practices and their discrete yet substantial contribution to sales performance.

This paper aims to, using a systematic mixed-methods based monitoring and evaluation approach, investigate the unintended consequences of physical and technical home improvements on energy use, indoor environmental conditions and occupant behaviour in community-led retrofits. The study is part of a UK Research Council funded research project on evaluating the impacts and effectiveness of low carbon communities on energy behaviours.

A graduated measurement, monitoring and evaluation framework has been developed and applied to gather quantitative and qualitative data on energy use and behaviours has been developed and applied to 88 households across the UK. A mixed-methods approach is used, including occupant interviews, questionnaires, activity diaries and continuous physical monitoring of energy use, environmental conditions and low-carbon technologies.

The study has uncovered a number of unintended consequences associated with home energy improvements, both beneficial and detrimental, including improved comfort levels in retrofitted dwellings and reduction in energy use but also an increased likelihood of overheating following fabric improvements, potential under-performance of low-carbon systems due to lack of understanding and inadequate installation and commissioning, along with adaptive energy behaviours leading to increased energy use and a widening gap between predicted and actual savings.

Although 63 case study households are involved, it is difficult to provide statistical analysis from the emerging findings.

This paper demonstrates the unintended consequences of home energy improvements. It aims to bring awareness of these issues to various sectors and stakeholders involved in delivering community retrofit programmes or the National Green Deal programme.

The paper fulfils an identified need to study the impacts of home energy improvements within existing homes through a robust, comprehensive M&E approach.

There is a great interest in developing eco-friendly operations as alternative uses of resources in the university campus, making the employment of technologies more sustainable. Practices such as energy management and efficiency initiatives have been encouraged to meet these sustainability goals. The purpose of this paper is to describe and discuss the main features of the GENIIOT project, a system of energy management using Internet of Things applied in a Brazilian university campus to support energy education practices and to promote lasting energy efficiency measures. The focus of the study is directed at the energy consumption of the air-conditioning system, which is responsible for 40% of the total electricity consumption. In addition, this project also scrutinizes processes such as the building occupants’ comfort demands, lighting levels and energy waste control.

A case study at the Unicamp campus was conducted to illustrate the design procedures through qualitative description. This study comprises an overview of the physical plant, hardware and software development, energy data monitoring, management process and energy education.

The GENIIOT project enables energy efficiency actions by concerning the use of air-conditioning equipment based on monitored data, different types of monitored rooms, user’s behaviors and their feedback. This initiative requires the engagement, awareness and actions from users combined with investment in energy efficiency to achieve an efficient use of this type of equipment. The proposed approach can be applied in the future to similar situations, inside the Unicamp campus and at other university campuses. In addition, this project can contribute to building efficiency analysis by using the hardware structure developed to monitor facilities and carry out evaluations, providing valuable information for strategic initiatives in energy efficiency projects and research and development programs based on practical experience and promoting a discussion about sustainability aspects in the context of the university campus for energy efficiency.

The GENIIOT project is aligned with some of the sustainable development goals, among which sustainability and responsible consumption are identified. Considering the sustainability issues, the economic dimension can be evaluated through a cost–benefit analysis of energy efficiency projects with prudent investment, while the social attractiveness of the project is ensured by education and awareness practices for the community that interacts with the system and learns about a more efficient way of using resources in the campus. Furthermore, there is a more conscious use of natural resources by minimizing waste from the use of electricity and reducing carbon dioxide emissions. GENIIOT is part of Sustainable Campus Project, a living laboratory which aims at developing energy-efficiency-related research activities in the university campus to reduce costs in higher and federal institutions of education in Brazil.

Environmental rating systems typically focus on building characteristics at a specific point in time; but from investment and valuation perspectives, actual performance over time should be the most important thing. Newly constructed commercial buildings today usually come with a high degree of technically advanced installations and a wide range of monitoring possibilities. This provides us with the possibility of monitoring a building’s in-use performance. The purpose of this paper is to investigate how frontrunners in the Swedish green building market actually monitor their new buildings, and look for similarities in that area.

By investigating a selected case study, conducting a survey and follow-up interviews among Swedish real estate companies and finally studying the available industry information, this paper considers what key performance indicators real estate developers choose to monitor as well as how they go about collecting and using the data. By doing this, we can get an idea of what is already monitored and to what extent. The case study also provides an insight into what is technologically possible.

A comparison of the gathered data from this study is then made with information that investors and property valuers would be expected to be interested in. The results show that these data are, to a large extent, information that the frontrunners already gather, but it is not made publicly available. One area where important information is lacking, however, is data about indoor climate.

The study is solely focussed on commercial buildings in Sweden and also on real estate owners with a high sustainability profile.

This paper presents a starting point in introducing the research area of the continued sustainability performance of our built environment. In order to understand and improve the environmental performance over time of our buildings and the connection to potential value, it is important to know what we can and should monitor.

Under the dual pressure of resources and environment, many countries have focused on the role of railways in promoting low-carbon development of integrated transportation and of even the whole society. This paper aims to provide a comprehensive study on methods to improve railway energy efficiency in other national railways and achievements made by China’s railways in the past practice, and then to propose ways in which in the future China’s railways could rationally select the path of improving energy efficiency regarding the needs of the nation's ever-shifting development and carry out the re-engineering for mechanism innovation in energy conservation and emission reduction process.

This paper first studies other national railways that have tried to promote the improvement of railway energy efficiency by the ways of technology, management and structural reconstruction to reduce energy consumption and carbon emissions. Among them, the effect of structural energy conservation and emission reduction has become more prominent. It has become the main energy conservation and emission reduction measure adopted by foreign railway sectors. The practice of energy conservation and emission reduction of railways in various countries has tended to shift from a technical level to a structural one.

Key aspects in improving energy efficiency include re-optimization of energy structure, re-innovation of energy-saving technologies and optimization of transportation organization. Path selection includes continuing to promote electrified railway construction, increasing the use of new and renewable energy sources, and promoting the reform of railway transportation organizations.

This paper provides further challenges and research directions in the proposed area and has referential value for the methodologies, approaches for practice in a Chinese context. To achieve the expected goals, relevant supporting policies and measures need to be formulated, including actively guiding integrated transportation toward railway-oriented development, promoting innovation in energy-saving and emission reduction mechanisms and strengthening policy incentives, focusing on improving the energy efficiency of railways through market behavior. At the same time, it is necessary to pay attention to new phenomena in the railway industry for track and analysis.

The purpose of this paper is to investigate the link between maintenance and energy saving in a commercial refrigeration setting.

Since there is little data available from within the industrial sector, the authors have surveyed the literature for evidence of a link.

Maintenance procedures play a major role in ensuring refrigeration equipment operates at maximum efficiency.

Little real world data is available and this is a major problem at present. Improved maintenance policies can only be developed.

Substantial energy savings can be achieved if maintenance procedures are improved based on detailed measurement of energy usage. Monitoring the condition and performance of individual parts of a system are found to be crucial aspects in obtaining optimal performance.

This paper highlights a neglected area in both energy saving and in maintenance planning.

This paper aims to describe research work to create an innovative, and intelligent solution for energy efficiency optimisation.

A novel approach is taken to energy consumption monitoring by using ambient intelligence (AmI), extended data sets and knowledge management (KM) technologies. These are combined to create a decision support system as an innovative add-on to currently used energy management systems. Standard energy consumption data are complemented by information from AmI systems from both environment-ambient and process ambient sources and processed within a service-oriented-architecture-based platform. The new platform allows for building of different energy efficiency software services using measured and processed data. Four were selected for the system prototypes: condition-based energy consumption warning, online diagnostics of energy-related problems, support to manufacturing process lines installation and ramp-up phase, and continuous improvement/optimisation of energy efficiency.

An innovative and intelligent solution for energy efficiency optimisation is demonstrated in two typical manufacturing companies, within one case study. Energy efficiency is improved and the novel approach using AmI with KM technologies is shown to work well as an add-on to currently used energy management systems.

The decision support systems are only at the prototype stage. These systems improved on existing energy management systems. The system functionalities have only been trialled in two manufacturing companies (the one case study is described).

A decision support system has been created as an innovative add-on to currently used energy management systems and energy efficiency software services are developed as the front end of the system. Energy efficiency is improved.

For the first time, research work has moved into industry to optimise energy efficiency using AmI, extended data sets and KM technologies. An AmI monitoring system for energy consumption is presented that is intended for use in manufacturing companies to provide comprehensive information about energy use, and knowledge-based support for improvements in energy efficiency. The services interactively provide suggestions for appropriate actions for energy problem elimination and energy efficiency increase. The system functionalities were trialled in two typical manufacturing companies, within one case study described in the paper.

This paper aims to describe the creation of innovative and intelligent systems to optimise energy efficiency in manufacturing. The systems monitor energy consumption using ambient intelligence (AmI) and knowledge management (KM) technologies. Together they create a decision support system as an innovative add-on to currently used energy management systems.

Energy consumption data (ECD) are processed within a service-oriented architecture-based platform. The platform provides condition-based energy consumption warning, online diagnostics of energy-related problems, support to manufacturing process lines installation and ramp-up phase and continuous improvement/optimisation of energy efficiency. The systems monitor energy consumption using AmI and KM technologies. Together they create a decision support system as an innovative add-on to currently used energy management systems.

The systems produce an improvement in energy efficiency in manufacturing small- and medium-sized enterprises (SMEs). The systems provide more comprehensive information about energy use and some knowledge-based support.

Prototype systems were trialled in a manufacturing company that produces mooring chains for the offshore oil and gas industry, an energy intensive manufacturing operation. The paper describes a case study involving energy-intensive processes that addressed different manufacturing concepts and involved the manufacture of mooring chains for offshore platforms. The system was developed to support online detection of energy efficiency problems.

Energy efficiency can be optimised in assembly and manufacturing processes. The systems produce an improvement in energy efficiency in manufacturing SMEs. The systems provide more comprehensive information about energy use and some knowledge-based support.

This research addresses two of the most critical problems in energy management in industrial production technologies: how to efficiently and promptly acquire and provide information online for optimising energy consumption and how to effectively use such knowledge to support decision making.

This research was inspired by the need for industry to have effective tools for energy efficiency, and that opportunities for industry to take up energy efficiency measures are mostly not carried out. The research combined AmI and KM technologies and involved new uses of sensors, including wireless intelligent sensor networks, to measure environment parameters and conditions as well as to process performance and behaviour aspects, such as material flow using smart tags in highly flexible manufacturing or temperature distribution over machines. The information obtained could be correlated with standard ECD to monitor energy efficiency and identify problems. The new approach can provide effective ways to collect more information to give a new insight into energy consumption within a manufacturing system.