Exploring the role of E-maintenance for value creation in service provision

Technological innovations has always played an important role in economic growth and industrial productivity, but they have also potential to influence service industry. In particular, they can offer support to the process of servitization in manufacturing companies. This article presents a study regarding the prospective value that different technological innovations can offer to maintenance service provision. A review of different baseline technologies and a categorization of several types of E-maintenance tools and applications has been carried out in order to understand the new functionalities that can potentially bring to the provision of smart maintenance services. Moreover, a value analysis method for representing the contribution of tool categories to several value dimensions is presented here. This method can be used for identifying the best technological solution, matching both customer value and provider value, i.e. conforming a win-win situation for the parties involved in the service provision. Some preliminary results based on a survey are eventually given as a first test of its applicability

Studying the funding principles for integrating Asset Management in Operations: an empirical research in production companies

The aim of this paper is to investigate Asset Management (AM) implementation as a business process within production systems to contribute to operational excellence. The main fundamentals to be considered to properly implement AM within production companies according to the existing literature and standards are identified and they are: two dimensions - i.e., the asset life cycle (Beginning of Life, Middle of Life, End of Life phases) and the hierarchical level of the asset-control activities (strategic level, tactical level, operational level) - and four funding principles - i.e., life cycle orientation, system orientation, risk orientation and asset-centric orientation. An empirical investigation is then developed through multiple case-study involving eight production companies in Italy, in order to assess the level of orientation towards those funding principles within production companies as it is nowadays, in order to identify existing gaps and areas for improvements

Diagnosis and management of iridocorneal endothelial syndrome

The iridocorneal endothelial (ICE) syndrome is a rare ocular disorder that includes a group of conditions characterized by structural and proliferative abnormalities of the corneal endothelium, the anterior chamber angle, and the iris. Common clinical features include corneal edema, secondary glaucoma, iris atrophy, and pupillary anomalies, ranging from distortion to polycoria. The main subtypes of this syndrome are the progressive iris atrophy, the Cogan-Reese syndrome, and the Chandler syndrome. ICE syndrome is usually diagnosed in women in the adult age. Clinical history and complete eye examination including tonometry and gonioscopy are necessary to reach a diagnosis. Imaging techniques, such as in vivo confocal microscopy and ultrasound biomicroscopy, are used to confirm the diagnosis by revealing the presence of "ICE-cells" on the corneal endothelium and the structural changes of the anterior chamber angle. An early diagnosis is helpful to better manage the most challenging complications such as secondary glaucoma and corneal edema. Treatment of ICE-related glaucoma often requires glaucoma filtering surgery with antifibrotic agents and the use of glaucoma drainage implants should be considered early in the management of these patients. Visual impairment and pain associated with corneal edema can be successfully managed with endothelial keratoplasty

Techno-Economic Optimization Of A Stand-Alone Hybrid Microgrid For The Rural Electrification In Sub Saharan Africa

Paper presented to the 3rd Southern African Solar Energy Conference, South Africa, 11-13 May, 2015.This paper is focused on the design of a stand-alone micro-grid for rural electrification. The aim of this work is to define the best mix of energy sources and the optimal size of the energy storage for a small isolated village on the Ghana seaside. We obtain the optimal solution by simulating one year of operation for several different combinations of prime movers and battery sizes and comparing the economic performance in terms of levelized cost of electricity. We adopt a rolling-horizon strategy to simulate the micro-grid operation, which optimizes generators and loads schedule over a 12 hours time horizon. We solve a Mixed Integer Linear Programming problem for each time step, exploiting weather forecast for predicting the energy available from sun and wind and taking into account a realistic operation of each component like energy losses and costs during start-up of dispatchable generators and ageing cost for the battery. The optimal configuration found includes a 30 kWel wind turbine, a 60 kWel photovoltaic array, a 30 kWel biomass fired ORC and a 50 kWel diesel. The limited use of the diesel engine in the optimal solution demonstrates that energy access in a sustainable and economic way is possible even in rural contexts. Finally, two sensitivity analyses are presented varying the cost of the biomass and the error of wind speed forecast.cf201

Selection Maps for ORC and CO2Systems for Low-Medium Temperature Heat Sources

Low-medium temperature heat sources in the range 5 - 50 MWthare made available by many industrial fields but they may also be of interest for biomass and solar energy applications. ORC has been proposed in the last 20 years as a reliable solution for the exploitation of these energy sources since the alternative represented by steam cycles leads to an inefficient conversion of such small available thermal powers. However, the use of organic fluids involves a number of safety and environmental issues, either related to fluid flammability (for hydrocarbons) or to their high-Global Warming Potential (for halogenated fluids), and of limitations to the achievable cycle maximum temperature, due to fluids thermal decomposition. To overcome these limitations, CO2-based transcritical and supercritical cycles have been proposed, in recent years, as a viable option for waste heat recovery applications. The present work aims to present a fair comparison between CO2and ORC power plants for waste heat recovery applications

Maintenance business model: a concept for driving performance improvement

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Local Digital Twin-based control of a cobot-assisted assembly cell based on Dispatching Rules

In the context of an increasing digitalization of production processes, Digital Twins (DT) are emerging as new simulation paradigm for manufacturing, which leads to potential advances in the production planning and control of production systems. In particular, DT can support production control activities thanks to the bidirectional connection in near real-time with the modeled system. Research on DT for production planning and control of automated systems is already ongoing, but manual and semi-manual systems did not receive the same attention. In this paper, a novel framework focused on a local DT is proposed to control a cobot-assisted assembly cell. The DT replicates the behavior of the cell, providing accurate predictions of its performances in alternative scenarios. Then, building on these predicted estimates, the controller selects, among different dispatching rules, the most appropriate one to pursue different performance objectives. This has been proven beneficial through a simulation assessment of the whole assembly line considered as testbed

Maintenance plan adaptation based on health ratings of servitised machines through a fleet-wide machine clustering method

The increased requests for value-added services to integrate product performance push manufacturing companies to extend their service offerings to meet customers’ needs. In this context, maintenance planning can leverage new possibilities offered by digital technologies for data analytics services. The present research then proposes an approach for maintenance plan adaptation based on a data-driven method applied over a fleet of machines installed in different production sites. The method relies on collaborative prognostics to develop a clustering of machines’ behaviour aimed at providing the health ratings of the machines and the subsequent maintenance plan adaptation due to the deviation from the expected behaviour. The method is adopted from the perspective of an Original Equipment Manufacturer, as part of a transformation path towards an advanced provision of digitalization for maintenance service offerings. The method is validated in the context of two lines at selected customer’s premises. This demonstrates the viability and effectiveness of adapting the maintenance plans thanks to the data analytics in light of the current behaviour of the machines within the lines

On the role of Prognostics and Health Management in advanced maintenance systems

The advanced use of the Information and Communication Technologies is evolving the way that systems are managed and maintained. A great number of techniques and methods have emerged in the light of these advances allowing to have an accurate and knowledge about the systems’ condition evolution and remaining useful life. The advances are recognized as outcomes of an innovative discipline, nowadays discussed under the term of Prognostics and Health Management (PHM). In order to analyze how maintenance will change by using PHM, a conceptual model is proposed built upon three views. The model highlights: (i) how PHM may impact the definition of maintenance policies; (ii) how PHM fits within the Condition Based Maintenance (CBM) and (iii) how PHM can be integrated into Reliability Centered Maintenance (RCM) programs. The conceptual model is the research finding of this review note and helps to discuss the role of PHM in advanced maintenance systems.EU Framework Programme Horizon 2020, 645733 - Sustain-Owner - H2020-MSCA-RISE-201