Application integration for condition monitoring

Nykyaikaiset kunnossapitomenetelmät erityisesti kuntoon perustuvassa kunnossapidossa ovat hyvin tietointensiivisiä. Tieto on kuitenkin usein jaettu tietojärjestelmiin, jotka eivät ole yhteydessä toisiinsa. OPC Unified Architecture on uusi yhteyskäytäntö jonka odotetaan kaventavan palvelukeskeisten tietojärjestelmien ja automaatiojärjestelmien välistä kuilua. Tämä työ tutkii OPC Unified Architecturen soveltuvuutta älykkäiden toimilaitteiden ja kunnonvalvontajärjestelmien yhdistämiseen. Työssä rakennetaan koeympäristö, joka koostuu kunnonvalvontajärjestelmästä (Metso FieldCare) ja kunnossapitojärjestelmästä (CalemEAM), ja suunnitelma näiden yhdistämiseen esitellään. Osa suunnitelmasta toteutetaan .NET sovelluskehyksellä ja toteutus testataan kuntoon perustuvan kunnossapidon prosesseilla. Toteutuksessa sovelletaan MIMOSA OSA-EAI ja OpenO&M Common Interoperability Registry -spesifikaatioita. Tulosten perusteella voidaan sanoa, että OPC Unified Architecture ja erityisesti sen tiedonmallintamisominaisuudet ovat hyödyllisiä verrattuna tämän hetkisiin tekniikoihin. Olemassa olevat tietomallit eivät kuitenkaan riitä kuntotiedon mallintamiseen. Jos mallintamisominaisuuksia ei käytetä, niiden vaikutus on vain spesifikaatiota monimutkaistava.Contemporary maintenance processes particulary in condition based maintenance are very information-intensive. However, the information is usually divided to several information systems that are not interconnected. OPC Unified Architecture is a new protocol expected to bridge the gap between the service-oriented enterprise IT systems and the automation systems. This work studies the feasibility of OPC Unified Architecture to enable connectivity of intelligent devices and condition monitoring systems. A test platform consisting of a condition monitoring system (Metso FieldCare) and an enterprise asset management system (CalemEAM), is implemented and a design to connect the systems is presented. A part of the design is implemented on the test platform with the .NET framework and the implementation is validated with processes of condition based maintenance. MIMOSA OSA-EAI and OpenO&M Common Interoperability Registry specifications were applied in the implementation. The results suggest that OPC Unified Architecture and in particular its information modelling capabilities o_er bene_ts over the older technologies. However, the existing information models are insufficient for presenting condition data. If the information modelling capabilities are not utilised, they remain a source of unnecessary complexity

An industrial analytics methodology and fog computing cyber-physical system for Industry 4.0 embedded machine learning applications

Industrial cyber-physical systems are the primary enabling technology for Industry 4.0, which combine legacy industrial and control engineering, with emerging technology paradigms (e.g. big data, internet-of-things, artificial intelligence, and machine learning), to derive self-aware and self-configuring factories capable of delivering major production innovations. However, the technologies and architectures needed to connect and extend physical factory operations to the cyber world have not been fully resolved. Although cloud computing and service-oriented architectures demonstrate strong adoption, such implementations are commonly produced using information technology perspectives, which can overlook engineering, control and Industry 4.0 design concerns relating to real-time performance, reliability or resilience. Hence, this research compares the latency and reliability performance of cyber-physical interfaces implemented using traditional cloud computing (i.e. centralised), and emerging fog computing (i.e. decentralised) paradigms, to deliver real-time embedded machine learning engineering applications for Industry 4.0. The findings highlight that despite the cloud’s highly scalable processing capacity, the fog’s decentralised, localised and autonomous topology may provide greater consistency, reliability, privacy and security for Industry 4.0 engineering applications, with the difference in observed maximum latency ranging from 67.7% to 99.4%. In addition, communication failures rates highlighted differences in both consistency and reliability, with the fog interface successfully responding to 900,000 communication requests (i.e. 0% failure rate), and the cloud interface recording failure rates of 0.11%, 1.42%, and 6.6% under varying levels of stress

Trusted Artificial Intelligence in Manufacturing; Trusted Artificial Intelligence in Manufacturing

The successful deployment of AI solutions in manufacturing environments hinges on their security, safety and reliability which becomes more challenging in settings where multiple AI systems (e.g., industrial robots, robotic cells, Deep Neural Networks (DNNs)) interact as atomic systems and with humans. To guarantee the safe and reliable operation of AI systems in the shopfloor, there is a need to address many challenges in the scope of complex, heterogeneous, dynamic and unpredictable environments. Specifically, data reliability, human machine interaction, security, transparency and explainability challenges need to be addressed at the same time. Recent advances in AI research (e.g., in deep neural networks security and explainable AI (XAI) systems), coupled with novel research outcomes in the formal specification and verification of AI systems provide a sound basis for safe and reliable AI deployments in production lines. Moreover, the legal and regulatory dimension of safe and reliable AI solutions in production lines must be considered as well. To address some of the above listed challenges, fifteen European Organizations collaborate in the scope of the STAR project, a research initiative funded by the European Commission in the scope of its H2020 program (Grant Agreement Number: 956573). STAR researches, develops, and validates novel technologies that enable AI systems to acquire knowledge in order to take timely and safe decisions in dynamic and unpredictable environments. Moreover, the project researches and delivers approaches that enable AI systems to confront sophisticated adversaries and to remain robust against security attacks. This book is co-authored by the STAR consortium members and provides a review of technologies, techniques and systems for trusted, ethical, and secure AI in manufacturing. The different chapters of the book cover systems and technologies for industrial data reliability, responsible and transparent artificial intelligence systems, human centered manufacturing systems such as human-centred digital twins, cyber-defence in AI systems, simulated reality systems, human robot collaboration systems, as well as automated mobile robots for manufacturing environments. A variety of cutting-edge AI technologies are employed by these systems including deep neural networks, reinforcement learning systems, and explainable artificial intelligence systems. Furthermore, relevant standards and applicable regulations are discussed. Beyond reviewing state of the art standards and technologies, the book illustrates how the STAR research goes beyond the state of the art, towards enabling and showcasing human-centred technologies in production lines. Emphasis is put on dynamic human in the loop scenarios, where ethical, transparent, and trusted AI systems co-exist with human workers. The book is made available as an open access publication, which could make it broadly and freely available to the AI and smart manufacturing communities

Proceedings of the WABER 2017 Conference

The scientific information published in peer-reviewed outlets carries special status, and confers unique responsibilities on editors and authors. We must protect the integrity of the scientific process by publishing only manuscripts that have been properly peer-reviewed by scientific reviewers and confirmed by editors to be of sufficient quality. I confirm that all papers in the WABER 2017 Conference Proceedings have been through a peer review process involving initial screening of abstracts, review of full papers by at least two referees, reporting of comments to authors, revision of papers by authors, and reevaluation of re-submitted papers to ensure quality of content. It is the policy of the West Africa Built Environment Research (WABER) Conference that all papers must go through a systematic peer review process involving examination by at least two referees who are knowledgeable on the subject. A paper is only accepted for publication in the conference proceedings based on the recommendation of the reviewers and decision of the editors. The names and affiliation of members of the Scientific Committee & Review Panel for WABER 2017 Conference are published in the Conference Proceedings and on our website www.waberconference.com Papers in the WABER Conference Proceedings are published open access on the conference website www.waberconference.com to facilitate public access to the research papers and wider dissemination of the scientific knowledge

Use, Operation and Maintenance of Renewable Energy Systems:Experiences and Future Approaches

The aim of this book is to put the reader in contact with real experiences, current and future trends in the context of the use, exploitation and maintenance of renewable energy systems around the world. Today the constant increase of production plants of renewable energy is guided by important social, economical, environmental and technical considerations. The substitution of traditional methods of energy production is a challenge in the current context. New strategies of exploitation, new uses of energy and new maintenance procedures are emerging naturally as isolated actions for solving the integration of these new aspects in the current systems of energy production. This book puts together different experiences in order to be a valuable instrument of reference to take into account when a system of renewable energy production is in operation

Factors Influencing Customer Satisfaction towards E-shopping in Malaysia

Online shopping or e-shopping has changed the world of business and quite a few people have decided to work with these features. What their primary concerns precisely and the responses from the globalisation are the competency of incorporation while doing their businesses. E-shopping has also increased substantially in Malaysia in recent years. The rapid increase in the e-commerce industry in Malaysia has created the demand to emphasize on how to increase customer satisfaction while operating in the e-retailing environment. It is very important that customers are satisfied with the website, or else, they would not return. Therefore, a crucial fact to look into is that companies must ensure that their customers are satisfied with their purchases that are really essential from the ecommerce’s point of view. With is in mind, this study aimed at investigating customer satisfaction towards e-shopping in Malaysia. A total of 400 questionnaires were distributed among students randomly selected from various public and private universities located within Klang valley area. Total 369 questionnaires were returned, out of which 341 questionnaires were found usable for further analysis. Finally, SEM was employed to test the hypotheses. This study found that customer satisfaction towards e-shopping in Malaysia is to a great extent influenced by ease of use, trust, design of the website, online security and e-service quality. Finally, recommendations and future study direction is provided. Keywords: E-shopping, Customer satisfaction, Trust, Online security, E-service quality, Malaysia

Development of helicopter attitude axes controlled hover flight without pilot assistance and vehicle crashes.

In this work, we show how to computerize a helicopter to fly attitude axes controlled hover flight without the assistance of a pilot and without ever crashing. We start by developing a helicopter research test bed system including all hardware, software, and means for testing and training the helicopter to fly by computer. We select a Remote Controlled helicopter with a 5 ft. diameter rotor and 2.2 hp engine. We equip the helicopter with a payload of sensors, computers, navigation and telemetry equipment, and batteries. We develop a differential GPS system with cm accuracy and a ground computerized navigation system for six degrees of freedom (6-DoF) free flight while tracking navigation commands. We design feedback control loops with yet-to-be-determined gains for the five control "knobs" available to a flying radio-controlled (RC) miniature helicopter: engine throttle, main rotor collective pitch, longitudinal cyclic pitch, lateral cyclic pitch, and tail rotor collective pitch.We develop helicopter flight equations using fundamental dynamics, helicopter momentum theory and blade element theory. The helicopter flight equations include helicopter rotor equations of motions, helicopter rotor forces and moments, helicopter trim equations, helicopter stability derivatives, and a coupled fuselage-rotor helicopter 6-DoF model. The helicopter simulation also includes helicopter engine control equations, a helicopter aerodynamic model, and finally helicopter stability and control equations. The derivation of a set of non-linear equations of motion for the main rotor is a contribution of this thesis work.After discussing the integration of hardware and software elements of our helicopter research test bed system, we perform a number of experiments and tests using the two specially built test stands. Feedback gains are derived for controlling the following: (1) engine throttle to maintain prescribed main rotor angular speed, (2) main rotor collective pitch to maintain constant elevation, (3) longitudinal cyclic pitch to maintain prescribed pitch angle, (4) lateral cyclic pitch to maintain prescribed roll angle, and (5) yaw axis to maintain prescribed compass direction. (Abstract shortened by UMI.)We design and build two special test stands for training and testing the helicopter to fly attitude axes controlled hover flight, starting with one axis at a time and progressing to multiple axes. The first test stand is built for teaching and testing controlled flight of elevation and yaw (i.e., directional control). The second test stand is built for teaching and testing any one or combination of the following attitude axes controlled flight: (1) pitch, (2) roll and (3) yaw. The subsequent development of a novel method to decouple, stabilize and teach the helicopter hover flight is a primary contribution of this thesis.The novel method included the development of a non-linear modeling technique for linearizing the RPM state equation dynamics so that a simple but accurate transfer function is derivable between the "available torque of the engine" and RPM. Specifically, the main rotor and tail rotor torques are modeled accurately with a bias term plus a nonlinear term involving the product of RPM squared times the main rotor blade pitch angle raised to the three-halves power. Application of this non-linear modeling technique resulted in a simple, representative and accurate transfer function model of the open-loop plant for the entire helicopter system so that all the feedback control laws for autonomous flight purposes could be derived easily using classical control theory. This is one of the contributions of this dissertation work

Application of knowledge management principles to support maintenance strategies in healthcare organisations

Healthcare is a vital service that touches people's lives on a daily basis by providing treatment and resolving patients' health problems through the staff. Human lives are ultimately dependent on the skilled hands of the staff and those who manage the infrastructure that supports the daily operations of the service, making it a compelling reason for a dedicated research study. However, the UK healthcare sector is undergoing rapid changes, driven by rising costs, technological advancements, changing patient expectations, and increasing pressure to deliver sustainable healthcare. With the global rise in healthcare challenges, the need for sustainable healthcare delivery has become imperative. Sustainable healthcare delivery requires the integration of various practices that enhance the efficiency and effectiveness of healthcare infrastructural assets. One critical area that requires attention is the management of healthcare facilities. Healthcare facilitiesis considered one of the core elements in the delivery of effective healthcare services, as shortcomings in the provision of facilities management (FM) services in hospitals may have much more drastic negative effects than in any other general forms of buildings. An essential element in healthcare FM is linked to the relationship between action and knowledge. With a full sense of understanding of infrastructural assets, it is possible to improve, manage and make buildings suitable to the needs of users and to ensure the functionality of the structure and processes. The premise of FM is that an organisation's effectiveness and efficiency are linked to the physical environment in which it operates and that improving the environment can result in direct benefits in operational performance. The goal of healthcare FM is to support the achievement of organisational mission and goals by designing and managing space and infrastructural assets in the best combination of suitability, efficiency, and cost. In operational terms, performance refers to how well a building contributes to fulfilling its intended functions. Therefore, comprehensive deployment of efficient FM approaches is essential for ensuring quality healthcare provision while positively impacting overall patient experiences. In this regard, incorporating knowledge management (KM) principles into hospitals' FM processes contributes significantly to ensuring sustainable healthcare provision and enhancement of patient experiences. Organisations implementing KM principles are better positioned to navigate the constantly evolving business ecosystem easily. Furthermore, KM is vital in processes and service improvement, strategic decision-making, and organisational adaptation and renewal. In this regard, KM principles can be applied to improve hospital FM, thereby ensuring sustainable healthcare delivery. Knowledge management assumes that organisations that manage their organisational and individual knowledge more effectively will be able to cope more successfully with the challenges of the new business ecosystem. There is also the argument that KM plays a crucial role in improving processes and services, strategic decision-making, and adapting and renewing an organisation. The goal of KM is to aid action – providing "a knowledge pull" rather than the information overload most people experience in healthcare FM. Other motivations for seeking better KM in healthcare FM include patient safety, evidence-based care, and cost efficiency as the dominant drivers. The most evidence exists for the success of such approaches at knowledge bottlenecks, such as infection prevention and control, working safely, compliances, automated systems and reminders, and recall based on best practices. The ability to cultivate, nurture and maximise knowledge at multiple levels and in multiple contexts is one of the most significant challenges for those responsible for KM. However, despite the potential benefits, applying KM principles in hospital facilities is still limited. There is a lack of understanding of how KM can be effectively applied in this context, and few studies have explored the potential challenges and opportunities associated with implementing KM principles in hospitals facilities for sustainable healthcare delivery. This study explores applying KM principles to support maintenance strategies in healthcare organisations. The study also explores the challenges and opportunities, for healthcare organisations and FM practitioners, in operationalising a framework which draws the interconnectedness between healthcare. The study begins by defining healthcare FM and its importance in the healthcare industry. It then discusses the concept of KM and the different types of knowledge that are relevant in the healthcare FM sector. The study also examines the challenges that healthcare FM face in managing knowledge and how the application of KM principles can help to overcome these challenges. The study then explores the different KM strategies that can be applied in healthcare FM. The KM benefits include improved patient outcomes, reduced costs, increased efficiency, and enhanced collaboration among healthcare professionals. Additionally, issues like creating a culture of innovation, technology, and benchmarking are considered. In addition, a framework that integrates the essential concepts of KM in healthcare FM will be presented and discussed. The field of KM is introduced as a complex adaptive system with numerous possibilities and challenges. In this context, and in consideration of healthcare FM, five objectives have been formulated to achieve the research aim. As part of the research, a number of objectives will be evaluated, including appraising the concept of KM and how knowledge is created, stored, transferred, and utilised in healthcare FM, evaluating the impact of organisational structure on job satisfaction as well as exploring how cultural differences impact knowledge sharing and performance in healthcare FM organisations. This study uses a combination of qualitative methods, such as meetings, observations, document analysis (internal and external), and semi-structured interviews, to discover the subjective experiences of healthcare FM employees and to understand the phenomenon within a real-world context and attitudes of healthcare FM as the data collection method, using open questions to allow probing where appropriate and facilitating KM development in the delivery and practice of healthcare FM. The study describes the research methodology using the theoretical concept of the "research onion". The qualitative research was conducted in the NHS acute and non-acute hospitals in Northwest England. Findings from the research study revealed that while the concept of KM has grown significantly in recent years, KM in healthcare FM has received little or no attention. The target population was fifty (five FM directors, five academics, five industry experts, ten managers, ten supervisors, five team leaders and ten operatives). These seven groups were purposively selected as the target population because they play a crucial role in KM enhancement in healthcare FM. Face-to-face interviews were conducted with all participants based on their pre-determined availability. Out of the 50-target population, only 25 were successfully interviewed to the point of saturation. Data collected from the interview were coded and analysed using NVivo to identify themes and patterns related to KM in healthcare FM. The study is divided into eight major sections. First, it discusses literature findings regarding healthcare FM and KM, including underlying trends in FM, KM in general, and KM in healthcare FM. Second, the research establishes the study's methodology, introducing the five research objectives, questions and hypothesis. The chapter introduces the literature on methodology elements, including philosophical views and inquiry strategies. The interview and data analysis look at the feedback from the interviews. Lastly, a conclusion and recommendation summarise the research objectives and suggest further research. Overall, this study highlights the importance of KM in healthcare FM and provides insights for healthcare FM directors, managers, supervisors, academia, researchers and operatives on effectively leveraging knowledge to improve patient care and organisational effectiveness

Lean Six Sigma maturity model within Saudi Arabian organisations : an empirical study

Lean Six Sigma (LSS) is a continuous improvement methodology that aims to reduce the costs of poor quality, improve the bottom-line results and create value for both customers and shareholders. LSS has been deployed in organisations in the Western countries for more than two decades. However, its implementation in Middle Eastern countries has only just begun to emerge. Furthermore, there is a lack of empirical studies in the area of understanding the current status of LSS in these countries. Therefore, the purpose of this research is to investigate the current status of Lean Six Sigma (LSS) in Saudi Arabian organisations and subsequently develop a Lean Six Sigma Maturity Model (LSSMM) which can be used to assess their current level of LSS maturity. The study is based on a systematic literature review of 45 papers that were published on LSS in high ranking journals in the field and other specialist journals, from 2000 to 2015. LSS themes identified include: LSS benefits, critical success factors, motivational factors, tools and techniques, critical failure factors, and limitations. A descriptive survey via a questionnaire was conducted in the second phase of the data collection process and multiple case studies were conducted in the third phase. Based on the literature review and the findings of the empirical research, a LSSMM was developed and used to assess the current level of LSS deployment maturity in five organisations in Saudi Arabia. The results of the empirical study show that LSS is in the early stages of implementation and that organisations in Saudi Arabia have only recently started to recognise the importance of LSS to their business. This finding was also supported by the evaluation of LSS maturity level that was assessed using the model developed in this study. This study contributes to understanding the current status of LSS in Saudi Arabian organisations and provides recommendations to guide the future of LSS in Saudi organisations by comparisons with the LSS literature and best practice. The contribution to knowledge and theory in this study is through validating and extending current operations management theories to LSS deployment, including organisational learning theory, theory of motivation and goal theory. The adoption of a mixed method approach contributes to the advancement of the methodology applied within LSS research in Saudi Arabian organisations. This study adds value for academics and practitioners in the field of LSS in Saudi Arabia by providing an intensive study on the current status of LSS deployment together with the LSSMM

Safety and Reliability - Safe Societies in a Changing World

The contributions cover a wide range of methodologies and application areas for safety and reliability that contribute to safe societies in a changing world. These methodologies and applications include: - foundations of risk and reliability assessment and management - mathematical methods in reliability and safety - risk assessment - risk management - system reliability - uncertainty analysis - digitalization and big data - prognostics and system health management - occupational safety - accident and incident modeling - maintenance modeling and applications - simulation for safety and reliability analysis - dynamic risk and barrier management - organizational factors and safety culture - human factors and human reliability - resilience engineering - structural reliability - natural hazards - security - economic analysis in risk managemen