ABSTRACT. Usage of the electronic devices has become part of the human life and with the advancement of technology, people are using more and more electronic gadgets which are getting connected to the Internet to provide better services to the customer. Evolution of Internet of Things (IoT) around customer usage for their daily applications is gaining lot of attention from various service providers. Now, it is very common to find the many of the services are connected with some sensor and data is transmitted to the service providers or they have made smart applications to help the customers are use products even more. But, in any case this information is available or stored somewhere in the cloud.

Energy based companies are also using the smart meters which will be communicating the user’s behavior and usage at regular intervals. Minute details regarding the energy usage can be used for the energy forecasting or load grid management for better resource availability for the customers. But this user level profiling can lead to serious security concerns to the customers. If this information is not well protected that will lead privacy issue, and customers using the services might face a serious security issues in some situations. The service providers needs to be care full where this data is stored and how this information being processed.

ABSTRACT. Large scale technological, economical and environmental changes led to increased energy consumption all over the world. Electrical energy became an indispensable daily factor due to the large automation and emergence of smart devices and equipments. Therefore, efficient resource management is a major goal of the energy market. In order to adapt electricity supply to demand and to prevent waste, companies rely on accurate and granular forecasting of future consumption. Electricity demand forecasting is a complex and deep task as it is influenced often by weather conditions and seasonality. Thus, the aim of this work is to offer more accurate short-term forecasting, evaluating data produced by smart meters, from individual house holds, and considering decisive factors influencing the consumption.

ABSTRACT. On February 6th 2004, Former US President George W. Bush issued Executive Order 13327 mandating "the efficient and economical use of America’s real property assets” and “…assure management accountability for implementing Federal real property management reforms." In order to accomplish the subsequent directives, the Air Force Civil Engineer community has adopted a mindset and framework commonly referred to as Asset Management. This new Asset Management mindset represents a paradigm shift from each base competing to spend the most money on their particular base, to the Civil Engineer community objective deciding which enterprise assets are in the direst need of funding. Put another way, the Air Force Civil Engineer community has been transitioning from a system of independent competition to a system of collective cooperation that makes the best use of limited taxpayer funds. To facilitate this transition Headquarters United States Air Force issued Program Action Directive (PAD) 12-03 in order to “continue the Air Force Civil Engineer’s effort to implement a multi-pronged Asset Management approach to centralize, standardize, streamline, re-organize, and enhance efficiency at all levels of the CE enterprise.” Despite the playbooks and guidance that has followed PAD 12-03, the Air Force has not yet developed a clear and concise way to define or measure overarching success at Asset Management or the implementation of PAD 12-03.

This research effort focuses on closing the knowledge gap between issued policy and implementation. It examines Asset Management implementation efforts in other government agencies, private industries, and in various countries around the world. Combining this information with interviews from Subject Matter Experts at various levels of the Air Force Civil Engineering structure, this research hopes to identify: current limitations in implementation, characterization and definition for Asset Management, key elements that constitute and promote success, barriers to success, military-unique opportunities for success, internal success identifiers, ways to promote continuous improvement, and the essential behaviors within the Air Force Asset Management context. Using this information and recommendations from the Air Force SMEs, suggestions are presented for measuring and incentivizing Asset Management success within an organization

ABSTRACT. Facility, infrastructure, and asset related data is being generated at an unprecedented rate, usually without specific purposes or goals. Data is typically collected in large amounts for exploratory science, achieving significant statistical power, and because of the relatively cheap cost of storing data in the cloud. In many cases however, organizations do not consider the negative issues with indiscriminate data collection to include diminishing returns to reduce uncertainty in asset management decisions and the cumulative costs of the data. This paper proposes a novel 4-step (IEVA) framework for determining the amount of data required for asset management decisions. The framework is built upon the following steps: 1) identify the problem, 2) establish context, 3) verify/collect data, and 4) analyze/decide. The IEVA framework helps to establish a baseline that orientates asset managers to collect decision-focused data and make data-informed decisions. The IEVA framework was tested with energy data collected from seventy-two facilities and the results are presented.

ABSTRACT. Asset management is a major challenge for RTE (Réseau de Transport d’Electricité), the French TSO (Transmission System Operator) since electrical grid components maintenance and renewal represent an important economic issue. Thus, a better assessment of their lifetime could lead RTE to substantial savings while assuring a high quality of service. To tackle this issue, Rte gathers a lot of data (monitoring, material failures, assets database …) and in the same time tries to understand the phenomena of its equipment’s aging leading eventually to failure. RTE chose to take advantage from these two information sources for developing a hybrid model. This model combines data analysis on the gathered datasets and numerical simulation on the physical modeling of the phenomena involved in the accelerated aging of equipment. To illustrate this approach, we are going to present the complete run of the hybrid computation to estimate the overhead lines conductors’ lifespan due to aeolian vibrations. Aeolian vibrations, a case of vortex induced vibrations, are a well-known phenomenon in the overhead lines (OHL) community. These vibrations are caused by the interaction between conductors and low-speed wind (velocities ranging from 1m/s to 7m/s). They induce one of the main causes of conductors damaging: fretting fatigue in the clamp/conductor system. In this hybrid computation, damaging due to fretting fatigue is evaluated using a mechanical multiscale approach when representative loadings and scenarios of loadings are obtained using machine learning techniques.

ABSTRACT. Laboratory experiments have been performed on medium sized roller bearings with two levels of artificial damage. Recordings of long time series have been made from both accelerometers and acoustic emission sensors at a wide range of different radial loads and rotation speeds. Due to non-perfect performance of the control systems for the rotation speed or frequency, significant variations were observed at all rotation speeds, and highest relative variation at the lowest rotation speeds. These variations were also recorded using a rotary encoder (tachometer). In real life condition monitoring, tachometers or rotary encoders are not always present, this can be due to the cost of installation or space limitations for introducing additional sensors. The present work describes the results of applying different methods for order tracking or correction for variations of instantaneous frequency without relying on the rotary encoder. These results are then verified by comparison to the rotary encoder data.

ABSTRACT. The early failure detection of rolling bearings in wind turbine gearboxes (WTGs) can prevent consequential damages. In addition of decreasing the repair costs and increasing the machine availability, the detection of damages during their formation and initial propagation could give an insight into preliminary stages and therefore, expand the knowledge and understanding of failure modes such as white etching cracks. Furthermore, critical operational conditions could be identified and avoided. In this work, it is hypothesised, that changes in the material structure that precede the formation of both fatigue bearing damages and WEC can be detected by a monitoring system (“Acoustic Emission” (AE)) which detects high-frequency acoustic signals. As a first step the Investigations will be carried out on component level using both a thrust bearing (dShaft=60 mm) and radial bearing test rig (dShaft=180 mm). The localisation of the affected area can be done post-testing through ultrasonic analysis and the actual detection and verification of preliminary stages is carried out by microstructural investigations. As a result of the initial investigations, the AE activity could be correlated with the life cycle of an axial cylindrical roller bearing, i.e. the running-in process and progressive fatigue of the bearing could be retrieved in the AE activity. Due to the missing assignment of AE signal forms to crack formation and/or crack propagation in the material, only a test stop after slight surface damage (preliminary stage of a pitting) has been achieved so far.

ABSTRACT. Rolling Element Bearings (REBs) are present in virtually all machines with moving or rotating parts, and are vital for proper performance and safe operation. Maintenance costs can be a substantial part of Total Cost of Ownership (TCO), which motivates development of improved Condition Monitoring (CM) methods for implementation of advanced maintenance regimes. Bearings often receive particular interest, as this component group rarely reach design lifetime and is re-sponsible for a substantial part of machine downtime. This paper focuses on larg-er tapered REBs under axial load, rooted in a previous case study of a top drive main bearing. The top drive was taken out of operation for maintenance, and available for testing using both new and worn bearings. Based on observations of the worn bearing, wear on roller ends in the rib-roller contact area was identified as an area of interest for future research. This failure mode is discussed in detail, as it differs from faults occurring in the load path. Scratches are observed on all roller ends, which indicates that CM methods based on detection of repetitive transients at defect frequencies will be ineffective for fault identification. A test rig for creating and observing accelerated roller end damage is designed, built and com-missioned, intended for use with vibration and Acoustic Emission (AE) sensors. In addition to normal continuous rotation of the bearing, the test rig is also designed for performing oscillation motion tests, a mode of operation of interest to manu-facturers and end users of cranes and winches. Plans and challenges for future work are discussed, in conjunction with the experimental setup.

ABSTRACT. Because of the bandwidth limitation of the engine controller, most gearboxes change speed over time. This change in speed necessitates the resampling of the data, based on a tachometer signal, to facilitate shaft, gear and bearing analysis of the rotating equipment. Without resampling, the quality of vibration analysis is degraded and many mechanical faults would be missed. Further, interfacing with existing tachometer can be both technically difficult due to poor shaft availability or expensive, and in some cases even change certification requirements. The ability for a smart sensor to acquire vibration data, extract the shaft speed from the vibration data, and then process the data allows vibration based fault detection capability at a lower cost, weight and reduced installation complexity than previously possible. Reducing cost, weight and installation complexity will expand the business case for condition monitoring, improving safety and reliability in industrial and transportation systems. This paper demonstrates a two-step process to recover a tachometer signal from vibration data that is of higher quality than raw tachometer data. Statistics are generated from known fault cases to demonstrate the effectiveness through two case studies based on real-world vibration data from wind turbine and helicopter gearboxes.

ABSTRACT. This paper discusses the need for maintenance related training in higher edu-cation and investigates the maintenance related education offered in engi-neering programs in Finland and Sweden. Main study objects are Finnish and Swedish Mechanical and Industrial engineering programs on both bachelor and master level. The study covers, for the selected programs, full programs in maintenance, single courses and a part of courses in which maintenance plays a role. In Finland there are in total 42 universities and applied science schools offering 115 programs within Mechanical or Industrial engineering. Of those, 17 programs contain some sort of maintenance related training. The corre-sponding figures for Sweden are 23 universities and applied science schools offering 87 programs within Mechanical or Industrial engineering, and 10 of these programs contains maintenance related education. Data is collected from course syllabuses; for each course the content and expected learning outcomes are analysed and categorised. The maintenance related education in the studied programs is in general low; less than 15% offer maintenance courses. The content in maintenance courses differs greatly: concept of maintenance, information systems in maintenance, reliability, life-cycle man-agement, condition monitoring and management of maintenance are covered. For increasing the maintenance topics in higher education, the development of appropriate study material and joint online courses are suggested.

ABSTRACT. Defence’s sustainment policy for naval vessels incorporates asset management principles and methods and recognises the need for experts who specialise in asset management as essential to delivering and maintaining maritime capability. For warships and submarines, asset managers constantly weigh technical challenges and costs of maintenance and modernisation against operational and functional benefits to meet the Operating and Support Intent, life cycle management objectives and Seaworthiness requirements. A naval asset management skills model has been developed that focusses on technical compliance, operational capability, and business-related goals intrinsic to Fleet Life Cycle Management. Naval enterprise sustainment efforts are a combined endeavour between Navy, Australian Public Service and defence industry contractors but has no identified or documented minimum asset management capabilities for life cycle management of either individual vessels or entire classes. While De-fence acknowledges the need for asset management within the naval enterprise, it has not established criteria for codifying or formally recognising required competencies directly related to life cycle management of naval vessels. National recognition and professional certification formally credits the learning, development and experiential requirements each warship and submarine life cycle management professional should have as a means to become officially sanctioned asset management specialists within Defence’s maritime sustainment community. Moreover, the nature of naval vessel asset management necessitates formal recognition within Capability and Acquisition Sustainment Group’s Sustainment Management Career Pathway as well as accreditation through the Australian Quality Framework. The US Navy’s Port Engineer Program provides a solid example on which Australia’s naval enterprise can base its own scheme. This paper outlines a method to recognise naval asset management specialists by codifying experience, education, and training requirements for inclusion in Defence’s Sustainment Management Professionalisation and Certification Framework and provides recommendations for establishing a valid career path for Warship and Submarine Life Cycle Managers.

ABSTRACT. Erasmus plus Strategic partnership are a program for collaboration between European Universities and companies. The projects Colibri 2014-2017(Collaboration and Innovation for Better, Personalized and IT-Supported Teaching) and EPIC 2017-2020 (Improving Employability through Internationalization and Collaboration) both have goals of testing and improving teaching methods. The Colibri project had 7 universities from 7 countries and 3 companies as partners. The goal was to test methods in delivering a common industrial relevant course for Master students from both a business and an engineering background. The test course was "Future Internet Opportunities" that merged internet technologies with internet usage and entrepreneurship. The 5 ECTS course was delivered 3 times with approximate 30 students each time. It consisted of 10 modules in 3 levels (introduction, basic , and advanced) that students took on the internet. The students had to take all modules on the introductory level but selected 5 and 2 on the next levels. After the modules there was a common seminar of a week where all met, students presented advanced module essays, group work methods were presented, and the groups got tasks. These tasks were assignments/ problems from real companies. The groups started to analyze the problems at the seminar and continued at home. All groups had only one member from each country so collaboration was on the internet. Then there was a final seminar with all present. Here groups presented first version of their work, got feedback, improved, and finally presented their work at an oral exam with opponents. Feedback from the students was that this was a very good way of learning where they emphasized the relevance when applying for job, and the international networking experience. We also had feedback from the companies that provided problems that the results were useful in terms of new views and sketch of possible solutions. Given the Colibri results, the project EPIC started in September 2017. Here 8 universities and 2 companies are partners. The purpose is to extend the experiences in Problem Based Learning Projects into Master (and Bachelor) Thesis. So here we have collected problems from real companies and are mixing students from the 8 universities. We have an idea that this collaborative international way of working will train for their future employment. The intention is to test methods and tool when students and companies from different countries are working together on their Master thesis. The first cohort of students starts early 2018, and will have a common seminar in Riga in February. The paper and WCEAM presentation will explain more on the methods used and experiences both on the methods and feedback from students and companies. Results from the first EPIC cohort will not be available for the paper deadline, but will be included in the WCEAM presentation.

ABSTRACT. The importance of information management is gaining momentum within the Engineering Asset Management domain, both in academic literature and industry applications. Being guided by an array of industry standards that solely focuses on information management processes within the life-cycle of engineering assets. Most noticeably PAS 1192-3 focusing on Building Information Modelling (BIM) and the associated information management processes within the operational phase of an asset.

A key focus of PAS 1192-3 is that an organisation should develop Organisational Information Requirements (OIR) which in turn generates Asset Information Requirements (AIR). This process ensures that the AIR’s developed are organisational lead, but in reality the leap from OIR to AIR is too great of a jump for most organisations.

One of the key challenges faced by organisations is trying to disseminate a single organisational information requirement into multiple asset systems and instances, that can easily run into the 1000+ types within a complex asset-centric organisation. Furthermore, it is not known (or standardised) as to what level within the asset hierarchy should asset information be captured. Both these challenges combined means organisations rarely produce information requirements that support the asset management /organisational objectives.

This paper proposes a top-down methodology that develops information requirements directly from the asset management objectives. As stated above the leap from OIR to AIR is too much for most organisations. It is proposed that an intermediate step is required. This step utilises the organisational view of assets as a functional output and proposes that the OIR will generate Functional Information Requirements, which in turn will specify AIR. This approach aids in closing the gap between OIR and AIR but by creating a functional link between the organisation and their assets.

ABSTRACT. The Petroleum Safety Authority (PSA) Norway sets the terms for and follows up that players in the Norwegian petroleum industry maintain a high level of health, safety and the environment and emer-gency preparedness. For oil and gas facilities in late life it is important to ensure good maintenance management processes and structural integrity as a basis for safe and efficient operation, both from a health, safety and environment (HSE) perspective to avoid major accidents and in a holistic perspective on the industry’s asset as a potential infrastructure for further oil and gas developments in the future.

Internal supervision and audits operating companies are critical management functions and key ele-ments in effective risk control and management of health and safety. Historical accident data have shown that poor or inadequate supervision, is a significant factor in accident causation, both for individ-ual and major hazard risk. Supervision by authorities is a supplement to the company’s own follow up.

The PSA has worked together with the other authorities in the North Sea area through the North Sea Offshore Authorities Forum (NSOAF) on this topic. During 2017 and 2018, a Multinational Audit (MNA) has been performed to facilitate lateral learning and best practices of oil and gas facilities late in life. The theme of the MNA has been “Maintaining Safe Operations”. Each country performed audits with the same basic questions adapted to local language and legislation, directed toward late life instal-lations. The audit also targeted assets that had gone through transfer of ownership. The summary of ob-servations from all the individual audits (MNAs) have been collected in a joint report for industry learn-ing. In the following, we will be presenting some of the findings from our supervisory activities ad-dressing the companies’ internal supervision and follow up of the maintenance management.

ABSTRACT. The Seveso Directive are the main EU legislation dealing specifically with the control of on-shore major accident hazards involving dangerous substances. The Directive applies to more than 300 operators in Norway mainly in the chemical and petrochemical industry, as well as in fuel wholesale and storage sectors. Several major accidents have occurred internationally due to the human error and poor maintenance. No similar major accidents have been registered in Norway, and it was therefore interesting to do a research to see whether Seveso operators in Norway take into account human error in maintenance. A comprehensive document study has been conducted of audit reports with deviations, regulatory requirements and reported accidents all relating to maintenance for period 2004 to 2015. Primary data were obtained by a completed survey of 102 Seveso operators in Norway. For questions in the survey, the relevant theory was used to increase the validity of the study. The maintenance is unfortunately a highly error-productive activity because of the human factor. The findings in the study show that human error in maintenance is a well-known problem for many and that the biggest challenge lies in the maintenance activities such as improper and incomplete installation.

ABSTRACT. NOV is a truly independent manufacturer of drilling equipment and supplier of oilfield services. For decades we have been the global leader for supplying the best drilling equipment, enabling our Customers to drill better than anyone else, and providing them oilfield related services with no surprises.

The introduction of artificial intelligence and improvements in digital technology have challenged our classical thinking with regards to equipment and service design. In order to remain the market leader, we brought together our best minds to meet that challenge and developed new strategies on how to control equipment, introduced advanced analytics into maintenance services, and evolved existing field methods.

As a result, a new generation of digital Condition Based Maintenance (CBM) “Rigsentry” services was introduced in 2016. Until then, NOV was providing Asset Management and technical services on more than 40 vessels and on hundreds of equipment units within Subsea (Riser & BOP), Drilling, and Lifting and Handling disciplines.

Services we offer range from technical advisory support to full Total Cost of Ownership (TCO) programs. All services depend on modern technology infrastructure and holistic information architecture. This combination encompasses the flexibility of delivering human, machine based, and database information in digital format, while keeping the Customer’s needs as the primary focus.

Our Global team continually uses experience to improve the operating technology, services formats, and the design of tools and equipment. Instead of relying on the common beliefs and practices of the past, our Key Performance Indicators (KPI) use high speed data to measure cost, availability, and value created to guide our developments. Improving efficiency is our constant goal. To achieve this, we will process and analyses all available information, working towards the improvement of NOV equipment, Asset Management tasks, and additionally, improve the organization and functionality of our supply chain and service teams.

We at NOV, will continue to lead the OEM support market in Asset Management by working alongside Customers and with such Class organizations as DNV/GL and ABS Eagle. This will build ecosystem style partnerships, where quality, value and risk sharing will become a viable and sustainable alternative to the traditional reactive support methods of the past.

ABSTRACT. The advancements concerning the development of ICT systems including Internet of Things (IoT), big data, cloud computing and and NoSQL databases provide new opportunities and challenges for industrial asset management. The use of NoSQL databases have emerged due to the limitations of the relational databases, among others, to scale-up horizontally to manage the data that is constantly generated by the industry. The current work highlights the key aspects of both the relational and NoSQL databases. Further, the paper provides a review of the above-mentioned technologies. In addition, it explains the steps involved to design and implement a NoSQL data structure within the industrial maintenance domain. In this context, in order to demonstrate the effectiveness and adequacy of NoSQL databases, some real industrial use cases are presented.

ABSTRACT. Excess pressure and increases in pressure within water supply and distribution systems correlate directly to increased water losses from pipe leakages. Pressure management in water supply and distribution systems, is one of the most influential, most important and most cost-effective interventions that can be implemented in order to reduce leakage.

Excess pressure available in water supply and distribution systems can be used as a renewable, low cost clean energy alternative for energy production with no significant environmental impacts. Similar to the use of PRVs, hydraulic turbines and pumps as turbines can be used to reduce excess pressure in a water network, but with the added benefit of converting the excess pressure into electric power rather than to dissipate the energy.

Asset management systems, inclusive of asset management plans and asset registers, provides unabridged information on water supply and distribution systems with regards to spatial, technical, operational and financial data. Analysis of this data with respect to energy recovery highlights the currently undetected opportunities.

The energy consumption in urban water supply and distribution systems represents 7% of the world’s energy consumption. The paper investigates and proposes the leveraging of asset management data for optimizing pressure management to enable maximum energy recovery and reduce the leakage rate from the system. Energy recovery decreases the carbon foot-print of the water distribution system while simultaneously either generating a stream of revenue for the operator or resulting in an energy cost saving. This increase in revenue or cost saving impacts on the dynamic of an asset management plan and provides for a more sustainable system. The paper also investigates the asset life cycle implications of energy recovery on the asset management system as well as the addition of an energy recovery and leakage reduction layer to current asset management software.

ABSTRACT. This paper describes how asset management decisions in energy networks can leverage a new system driven dynamic ageing model which considers system reliability and resilience. This model is an important part of the new strategic asset management tool called AIO, developed by Cosmo Tech in partnership with RTE.

ABSTRACT. Digitalization blurs industry boundaries and disrupts businesses. It offers opportunities and challenges for asset management related to, for instance, condition monitoring, machine prognostics and reliability issues. However, there are also many other opportunities for companies to enhance their service offering. To meet the challenges and opportunities of digitalization for asset management services, the establishment of new competences and agile development practices are utilised. For example, more competencies in the field of data analytics are required. In addition to the agile development practices, there is a need for systematic approaches that support service design. Currently, many companies concentrate on experimentation and agile development practices. The individual experiments may remain disconnected from strategic focus of the companies unless there is a holistic approach in place. In this paper, we propose a top-down approach for digital asset service development. The approach is created using design science methodology. The approach combines activities such as roadmapping and scenario planning, under-standing the customers decision-making context (decision-making levels and situations) and business model development. Roadmapping and scenario planning produce guidelines for the service development process. It provides a path for reaching the strategic intent of the company and defines its desired role in the customer’s business. Decision-making context connects the service to decision situations at different decision-making levels (strategic, tactical, operative). Business model development focuses on listing the available business model archetypes, selecting the most suitable ones and tailoring them to the needs of the company. Finally, we present case studies in which this approach is utilised.

ABSTRACT. The balance between maintenance and production activities plays a pivotal role for any asset in an organisation. Maintenance activities can require that the asset must be unavailable for production during maintenance and hence reduce the production volume. However, if the asset is not maintained the technical condition will degrade and can result in unexpected breakdowns and reduced plant capacity. An important question will then be: How can an organisation ensure the right balance of maintenance during the lifetime of the asset? To approach this question, fundamental understanding in asset management and strategic approach in an organisation is indeed necessary. In the field of asset management the associated standards ISO 55000 and EN 16646 have been developed. ISO 55000 provides the management overview, principles, terminology, and guidelines for asset management, whereas EN 16646 provides the management principles of how the maintenance process is coordinated with all the other asset management processes. In more details, EN 16646 the interrelationship between maintenance and other processes at asset and asset system level. Although a list is provided, it remains to investigate more in detail how the relationship between operation and maintenance processes is relevant for asset management strategy implementation. The objective of this article is therefore to propose an asset management strategy that will ensure a right balance between plant capacity and maintenance activities during the life cycle an asset. As a result, this paper demonstrates application of relevant key performance indicators (KPIs) and predictive maintenance approach for a gas turbine as a case example.

ABSTRACT. This paper introduces a dynamic Maintenance Work Order (MWO) schedule model for offshore facilities’ daily maintenance management. The objective of the MWO schedule model is to improve maintenance performance by reducing MWO overall delay and suspension time and the related cost. More facilities now are equipped with predictive maintenance systems to generate MWOs in short time periods, which means periodical maintenance forecasting and planning strategies are now challenged by a more dynamic context. We examine these challenges and design a model to generate an optimal MWO schedule instantly, based on cost analysis and real-time data processed by customized heuristic algorithms.

ABSTRACT. Asset management can be regarded as managing the degradation of assets by means of timing of interventions. Basically two types of interventions exist, maintaining or replacing the asset. In practice, maintenance and replacement are often optimized independently, as the timeframes and costs involved are often very different. Only at the end of asset life the disciplines connect in the choice between maintaining and replacing the asset. However, as maintenance impacts asset life, in long term planning of the asset base both should be considered in coherence. In this paper we present our simplified marginal approach for integrating maintenance in long term replacement planning considerations. The results are compared with numerical optimization by means of life cycle costing. Although the results align in general, there may be cases that a marginal approach does not provide the right result. The conditions under which this happens will require further research.

ABSTRACT. The Industrial presentation will present the development and challenges related to a National/Country Guideline for Low Enthalpy Geothermal Asset Management and Material & Corrosion cost life cycle. The guidelines was required by Regulator to ensure safer asset, control and compliance of Geothermal Asset. The Low Enthalpy Geothermal Asset typically combines a production well including an electric submersible pump (ESP) lifting the hot fluid to a surface heat exchanger and an injection well pumping the heat depleted fluid back into the source reservoir. The presentation will cover the relevant corrosion and scaling threats and their mitigations in geothermal assets (well and surface facility), including practical guidance on materials selection and the use of life–cycle costing so that cost-effective material choices can be made for wells at the design stage. Process for material selection decisions will be discussed. Further, the challenges for the development of Asset Integrity Management guideline/plan related to operator organisation, asset size, technical operational specificity, Integrity Risk management, inspection and monitoring frequencies will be addressed. A risk framework covering concept to operation phase and the associated identified risks will be presented.

ABSTRACT. A shared workplace is a workplace where one employer exercises the main authority and more employers or self-employed workers than one, operate simultaneously or successively in such a way that the work may affect other employees’ safety or health. Both the EU and Finnish legislation state that the employers and self-employed workers at such a workplace shall together in adequate cooperation ensure that their activities do not endanger the employees’ safety and health (Directive 89/391/EEC, 738/2002). Shared workplaces take place especially in the fields of construction, manufacturing and transportation and storage industries.

This study aimed at forming a holistic view on the occupational safety and health (OSH) challenges at shared workplaces of construction industry. The material consisted of randomized OSH inspection reports (N=79) by the Regional State Administrative Agency. Reports concentrating on the shared workplaces were analyzed to gain information on observed deficiencies. In the analyses the reports were categorized based on the holistic work system model (ISO 6385, 2016).

Observation categories related to organizational processes showed a peak in deficiencies related to design and planning. In categories related to the employee the observations on the use of personal protective equipment and in categories related to tools and technologies the condition and inspections of tools were pronounced. The deficiencies related to work environment focused on access ways and fall hazards.

The analysis carried out in this study resulted in the recognition of common challenges at shared workplaces of construction industry. With this method, an individual observation profile for each industry branch can be formulated. Such profiles can be used in the planning of industry-specific inspection check-lists for the supervision of OSH.

References: Directive 89/391/EEC , COUNCIL DIRECTIVE of 12 June 1989 on the introduction of measures to encourage improvements in the safety and health of workers at work (89/391/EEC) (OJ L 183, 29.6.1989, p. 1) (http://eur-lex.europa.eu/legal-content/EN/TXT/PDF/?uri=CELEX:01989L0391-20081211&from=EN).

ISO 6385 (2016). Ergonomics principles in the design of work systems. International Organization for Standardization.

Occupational Safety and Health Act (738/2002) Chapter 6: Special situations of organising work. Ministry of Social Affairs and Health. Unofficial translation. http://www.finlex.fi/en/laki/kaannokset/2002/en20020738.pdf.

ABSTRACT. Supplier management is a key issue for many large industrial companies from both performance and sustainability viewpoints. In this study, a supplier audit system in a Finnish industrial cluster is examined. The cluster has created a supplier assessment procedure, and roughly 200 supplier HSEQ audits have taken place. The aim of this study is to analyse a sample of these audits to identify common improvement areas among supplier companies. Improvement suggestions taken from the audits are classified into five themes and 39 categories. The results paint a picture of the most common HSEQ improvement areas for suppliers.

ABSTRACT. Professional truck drivers face various kinds of challenges during their workday. A high prevalence of work-related musculoskeletal disorders and high accident rates are associated with the trucking industry. In addition, various different psychosocial stressors affect truck drivers’ work ability. Accidents, disorders, and stressors all affect working careers. There is both a constant need for a skilled new workforce, but also a need for prolonging working careers.

Some characteristics can be identified on truck drivers’ work; the drivers mainly work alone and their work contains static work postures while sitting and physical activities while working outside the cab. While working, the driver often faces opportunities for unethical and unsafe actions to ease the workload. This poses challenges to the occupational health and safety (OHS) management.

This article provides a scoping review of the risks and hazards that the professional truck drivers face while working. Both driving and non-driving work activities are covered. Special attention is paid to selected new modes of transportation and a discussion is held on the possible OHS chal-lenges that they may bring along. High capacity transports (HCT) are dis-cussed as an emerging mode of road transportation that enables larger loads to be freighted and intermodal transportations (IMT) are used increase the effi-ciency of the transportations by combining different transportation modes. However, very little attention is being paid in the current OHS literature on the possible adverse OHS effects concerning the driver.

ABSTRACT. Production is depending on skills and competences used by planned interplay of tangible and intangible assets. This paper deals with efficient and effective contribution of human assets. Interplay is enabled by social and technical skills, leadership and management, psychosocial work community, motivation, and confidence, etc. The “continuum of understanding” comprising data, information, knowledge, and wisdom, is needed for production and managing it, intra- and inter-organizationally. The above issues are dealt within the context of an industrial case – a Finnish cluster of big companies, the one for running an activity comprising Health, Safety, Environment, Quality Assessment Procedure (HSEQ AP, www.HSEQ.fi). HSEQ AP is for defining the maturity level and achieved results of an organization’s Integrated Management System (IMS). HSEQ AP aims at increasing the productivity of a networked business, improving the business skills in HSEQ matters. It provides a comprehensive picture of an organization’s capabilities, consisting of description of IMS and a lot of alphanumeric or categorized performance indicators. The paper shows examples of typical measured indicators, and their progress on time-scale. One explaining approach emphasizes following drivers, “a chain of phenomena”, for high level of desired outcomes within production: (1) employees’ involvement in production processes to build and enable motivation, competence and confidence; (2) this participation “produces” benefits for production by offering humans’ technical and social skills then fully available. For utilization the above chain, much more human-centered communication is needed in management. The main stream of quantitative information only is not enough for effective businesses and all individuals within them. Technology-mediated digital communication gives many opportunities to tell and discuss about both facts and feelings in an illustrative and interesting way, with empathy, wisdom and appreciation. In brief, this paper presents needs and shows examples that quantitative knowledge management should and can be enriched with illustrative and qualitative features.

ABSTRACT. The ESF –funded (European Social Fund) project Prepared for working life! (in Finnish Valmiina työelämään! VALTE) aims to develop students’ working life knowledge and skills in all educational levels. The project produces nationally usable study modules that prepare young adults for their future working life. In the scope of the project (1st Nov, 2015 - 31st Oct, 2018) up to 11 educational institutions collaborate to ensure that different perspectives will be acknowledged. Institutions involved in VALTE are •Universities of Turku, Oulu, Jyväskylä, Vaasa and Lapland •Universities of Applied Sciences of Oulu, Jyväskylä, Vaasa, Saimaa and Turku •Oulu Vocational College.

In Oulu, all the three educational levels, i.e., university, polytechnics and vocational college, have collaborated. The cooperation includes for example monthly meetings, two seminars for representatives of the different stakeholders of the working life and for students, and study modules that utilize virtual learning. The study modules are for example an occupational safety module, which was tested with student group that consisted of students from the University of Oulu and from the University of Applied Sciences of Oulu, and a module that covers occupational interaction and communication between superiors and subordinates, and with peers. The last-mentioned module was developed in cooperation between the University of Applied Sciences of Oulu and the University of Oulu.

The Oulu project team also cooperates with the HSEQ Training Park in Northern Finland. The HSEQ Training Park is an area of which is 1.2 hectare (12,000 m2) and which consists of full-scale spaces, work stations (mock-ups) and work task situations with tools and equipment, even heavy machinery. The Park is a safety innovation where visitors can be trained on a practical level to perform safely at work, and manage and utilize effective and efficient good practices tailored to human abilities and limitations. The HSEQ Training Park consists of over 20 different training points that are practical, real working life demonstrations of construction of buildings and infrastructure, process and manufacturing industry, energy industry, rail transport, industrial services. Students visited the HSEQ Training Park in multidisciplinary groups as the groups consisted of students from University of Oulu, from University of Applied Sciences of Oulu and from Oulu Vocational College. The groups went through training points concerning safety management and responsibilities, ergonomics, working environment with physical and chemical risks, and protective equipment. Studying in multidisciplinary groups promotes the understanding about the others’ professional knowledge and skills and furthermore strengthens cooperative skills. Most companies employ young adults with background from all the three education levels, and therefore the collaboration of all students probably is a new “powerful tool” in work life studies.

In the final year of the VALTE project, the Oulu project team aims to pilot and finalize the study modules, strengthen the cooperation between the three educational levels, organize a seminar for representatives of the different stakeholders of the working life and for students, and further develop the use of the HSEQ Training Park in studies. Concerning the HSEQ Training Park, the team is developing a lifting simulation and a game following escape room’s style, and virtualizing some of the training points.

ABSTRACT. Many companies offering physical assets and products have to adapt to different market requirements in a profitable way. Modularisation is a common solution for this challenge that suppliers (manufacturers) of engineering assets use. Modularisation enables product variety and increases commonality between product variants. Modularisation includes defining a set of modules, interfaces, modular architecture and configuration rules and constraints based on a case specific par-titioning logic. Many motives may be behind a realised structure of a specific as-set. This paper reviews the main value creation mechanisms (VCM’s) of product modularisation in the manufacturing industry and studies what kind of VCM’s are related to the main lifecycle stages of engineering assets. Focusing on engi-neering asset lifecycle, the key VCM’s were recognised, but from a supplier’s per-spective there are also other VCM’s. Suppliers should consider the whole lifecycle when designing products and engineering assets and clarify which VCM’s are the most important guiding principles that should be followed and where trade-offs are made.

ABSTRACT. The aim of this research is to develop and test new method for evaluating the value and costs of technology in manufacturing industry based on Design Science.

Motivation of this research came from industry where new technologies are seen as a important source of competitiveness. Method is directed to support decision making in technology related questions in managerial level. Target application for developed method is existing product and business environment where sufficient design knowledge is available. Result of valuation is given in monetary terms.

Research question is: How to create and structure the information to evaluate the value and costs of technology in manufacturing industry?

Constructive research strategy is used and Design Research Method (DRM) with case study in industry is applied in developing and evaluating the method.

Because value of technology is situational company-specific knowledge is center of analysis. Developed method is six step method and the information is gathered mainly in workshops with company or technology experts. During the process main targets and limitations for technology exploitation are defined. Product characteristics and properties are modelled and technology characteristics are evaluated against them. Technology business impact is evaluated based on modelled value creation mechanisms and available financial data.

Developed method open the product, which is traditionally seen as a black box in technology valuation techniques, for technology evaluation process. Value creation mechanisms are recognized and used to evaluation.

ABSTRACT. Smart grids can be perceived as an instrument for achieving a set of energy goals: political, social, environmental, economic, etc. At the same time, there is still no common understanding on how smart grids have to be implemented, while roles and responsibilities have to be clearly defined and assigned to major actors within the paradigm. The trend towards electricity grids digitalization is gradually leading to the shift of business value towards more sustainable and efficient electricity services. Sustainability and efficiency are challenged by the increasing demand for electricity which is followed by a dramatic transformation of energy systems. While smart grids seem to be crucial in this process, there is a discrepancy in understanding the costs and benefits for the multiple actors involved and, consequently, absence of an adequate mechanism for value creation, delivery and capture. In addition, there are benefits of smart grids that cannot be measured directly in terms of money – such as higher energy system reliability, system security or commitment to carbon reduction. This calls for the identification of corresponding business models as well as incentives and values that are important for the implementation of smart grids in the electricity distribution system. A growing body of research is devoted to the dynamics and aspects of energy systems transformation, while most of the literature is focused on exogenous pressures and technological advancements as stimuli for change. Despite the rise of interest to the managerial aspects of smart grids implementation and development (collaboration of actors in particular), many aspects remain out of the scope. One of them is the business model for smart grids that would allow for value co-creation, delivery and capture in particular. This paper contributes to the research of smart grids by providing a conceptualized business model for an Autonomous Energy Complex (Smart Grid analogue, being implemented in Russia), which is aimed to balance the interests of its major actors via creation and delivery of maximum value to each one of them. A Russian energy sector perspective is primarily considered throughout the paper. The research is supported by evidence from interviews with a number of industrial experts and its results may be used for developing the roadmap of innovative development of Russian power industry.

ABSTRACT. Digitalization is a trend that is changing society and that will also have significant effects on the manufacturing industry. Simultaneously with the digitalization trend, formerly product-centric companies have been increasingly adopting service components in their products and basing their competitive strategies on services. The purpose of this study is to increase the understanding of how manufacturing companies see the effects of digitalization in their business, and how digitalization might affect their product and service provision. The paper presents the views of important actors in the manufacturing service ecosystems. The paper utilises case study approach and the nature of the study is exploratory. The research data was collected by semi-structured interviews with experts representing different roles in manufacturing ecosystems. The different views of solution providers, ICT infrastructure companies, and subcontractors are presented. According to the study, digitalization has the potential to make the benefits of the product-service sytems (PSS) more transparent. Lead producers and IT infrastructure companies already utilise information produced in their business ecosystem, but the subcontractors consider that the use of external information will realise in 5 to 10 years. Currently, digitalization mainly affects assets and asset related services. The importance of ICT and service components increases when moving towards more advanced PSS. Digitalization is expected to drastically disrupt the way the manufacturing companies operate and potentially threaten the market position of the incumbents. The paper builds a classification for digitalization-enabled PSS for manufacturing industry and contributes to the scarce body of literature that deals with digitalization-enabled PSS. The study also identifies the significance and value of the ICT and service components as a part of advanced forms of PSS.

ABSTRACT. To manage successfully a fleet of assets requires data collection from a fleet that can be distributed globally and to several companies. Thus, data collection is often conducted by multiple actors in business ecosystem, which makes it difficult to get access to all the data concerning a fleet. It is important to demonstrate the value that can be achieved by systematically utilizing fleet data as a support of fleet-level decision making. There is a huge potential to benefit from fleet data due to increasingly gathered data, Internet of Things technologies, and data analysis tools. In this paper, a model is proposed to illustrate the ecosystem around a fleet and how to evaluate the costs and benefits of fleet life-cycle data utilization in the ecosystem. An example ecosystem is proposed, formed by an equipment manufacturer, its customer company, and an information service provider. The model demonstrates the costs and benefits for each actor in the ecosystem and works as a managerial tool to develop the collaboration, fleet data utilization, service development, and data-based value creation in the ecosystem. The results deepen the scientific discussion about value of information and emphasize the importance of measuring the benefits that need to exceed the costs of data refining in order to create value from data.

ABSTRACT. Remote monitoring services are required to meet the very high demands on availability and efficiency of industrial systems. The fast evolution of technologies associated with the deeper penetration of Internet of Things in industry creates considerable challenges for such services. These are related to the whole data lifecycle, encompassing data acquisition, real-time data processing, transmission, storage, analysis, and higher added value service provision to users, with adequate data management and governance needed to be in place. The sheer complexity of such activities the need to ground such processing on sound domain knowledge emphasises the need for context information management. The aim of this paper is to survey and analyse recent literature that addresses internet of things context information management, mapping how context-aware computing addresses key challenges and supports delivering appropriate monitoring solutions.

ABSTRACT. Industry 4.0 is the future scenario of industrial production since it enables a new level of organising and controlling the entire valve chain with the product lifecycle by creating dynamic and real-time understanding of cross-company behaviours. Therefore, most of the oil and gas (O&G) companies at the Norwegian continental shelf (NCS) are looking forward to digitalise and automatize their asset and oper-ations in order to get the promising benefit of industry 4.0. There are recommen-dations from the ministry of industry toward the industrial digitalisation, together with commercial incentives taken by large-scale oil and gas operating companies. The holistic picture of the status of industry 4.0 at the Norwegian industrial sector is still missing. Industrial managers at the NCS, who are either ready for industry 4.0 or already progressing toward this industrial transition, are still lacking answers to several significant questions. Industry 4.0 originated in manufacturing sector and most of the current experiences are related to that specific sector, thus, can industry 4.0 technologies be useful for companies of operating and maintenance service providers? And what would be the specific requirements to revolutionise the current maintenance into smarter maintenance? Consequentially, the paper tries to present whether the complete solutions (i.e. product availability and busi-ness models) of intelligent maintenance are available and how mature they are. Moreover, it tries to illustrate how intelligent maintenance can be technically de-veloped, optimally managed and economically assessed.

ABSTRACT. Since the cycle of development of the new products gets shorter and shorter, to manage Product Life Cycle becomes more important and complex. The new generation products have more functionalities and sub-assemblies compared to the previous ones on applying enabling technologies. However, machine learning techniques have limitations in the initial phases of the development of new generation products as Middle-Of-Life (MOL) data is insufficient. Guided by this challenge, the study addresses predictive maintenance issues of new generation products and provides a data sampling approach to overcome the lack of MOL data at the initial phases of predictive maintenance applications. Doing this, we aim at facilitating the information search relevant to the maintenance recommendation and providing an optimized maintenance management considering insufficient data of further functionalities of new generation products. In that regard, the implementation of the proposed approach could help manufacturing companies (i) address knowledge representation, exploitation, openness and diffusion in the maintenance domain, (ii) overcome insufficient MOL data using manufacturing intelligence; (iii) enable predictive maintenance strategies at the initial phase of application, and (iv) improve innovative maintenance plan using enabling technologies. Accordingly, the study paves the way for predictive manufacturing to early-predict equipment condition and make optimized recommendations for adjustments and maintenance to ensure normal operations.

ABSTRACT. The changing nature of manufacturing, in recent years, is evident in industries willingness to adopt network connected intelligent machines in their factory de-velopment plans. While advances in sensors and sensor fusion techniques have been significant in recent years, the possibilities brought by Internet of Things cre-ate 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 comprehensive framework for its processing, analysis and use should be an important goal in ad-dressing 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 and the provision of comprehen-sive framework for its processing analysis and use. The concept of ‘Human in the loop’ is also reinforced with the use of audit trails, allowing streamlined access to decision making and the ability to mine decisions.

ABSTRACT. The world economic forum in 2017 highlighted that Predictive maintenance in O&G is expected to have a total benefit impact in 160 USD billions until 2025 reducing inspection and maintenance cost. This expected impact is based on the digital transformation initiatives in the era of industry 4.0. Several companies have started the progress toward revolutionizing their assets and operations to be smarter. Therefore, several assessment models for the readiness and maturity of the digital transformation are existing e.g. IMPULS. These maturity models assess the level of implementing Industry 4.0 philosophy with respect to several dimension i.e. strategy, leadership, customers, products, operations, culture, people, governance. It is worthy to note that these models are oriented to assess the manufacturing companies, as it is the origin of industry 4.0. Thus, using such models to assess the maturity of operation and maintenance systems for O&G platform requires more customized maturity model. The purpose of this paper is to present the developed maturity model, which assess the practices in eight dimensions (Asset, perception, transmission, conversion, computation, cognition, configuration and business) and generate advisory for a further development e.g. roadmap, strategic plan. The eight dimensions are categorized into three main categories (Physical space, Cyberspace and Business) which allow to assess specific details in the assets, IT and management configuration.

ABSTRACT. When dealing with risk related to complex systems, and for safety systems in particular, a main task is to identify and assess events that could threaten reliability performance of the system. With respect to this task, there are two important types of failures commonly referred to, i.e. systematic and systemic failures. Both of these relate to system thinking somehow, however, the meaning and importance of the two concepts should be distinct. In this paper, we study this distinction and relevance to complex systems by addressing available definitions of these given in international standards, and giving some examples. Despite the exact definition of the two concepts may vary, a main conclusion is that it is only when dealing with complex systems, that it is appropriate to use both concepts for the purpose of risk management.

ABSTRACT. This work presents a modeling methodology for sensors and equipment condition monitoring developed during a research project to enhance dependability of pre-salt petroleum extraction platforms. The methodology aims to improve the capability of the auto-associative models applied for sensors monitoring in the last decades in nuclear power plants, chemical industry, refineries, gas transport and processing plants. However, actual operation problems or fault in equipments also may lead to false measurement error detection. This problem observed in the previous applications motivated the development of the improved method able to detect measurement errors and fault conditions in the process or equipments. This improvement has been obtained adding data (real or simulated) of the different conditions of operation, including the fault conditions (undesired data in the previous methodology). Therefore, the models become able to make accurate sensor estimation, even under fault conditions in the monitored process, and they also give a proper fault diagnoses about the measurement instruments and the process reducing false alarms compared to the traditional approaches. Also, some modeling challenges were observed during the development such as optimization of parameters, memory size and computing complexity. The methodology is demonstrated using simulated a process of a Petroleum Platform application. The achieved results showed a possible methodology to improve or replace the traditional approaches in the past application.

ABSTRACT. Due to an increasing demand for operation at sea depths as low as 3000 m and under, the use of fiber ropes for offshore application in deep sea lifting and mooring is increasing. Consequently, improved knowledge is required regarding these ropes’ thermo-mechanical properties and how these properties change as the rope is being used. This paper presents a 2D model of heat transport in the axial and radial directions along a 28mm diameter fiber rope typically used for offshore applications. The model is combined with temperature measurements during heating and cooling of the rope, using both thermocouples and a thermal camera. Measurements are performed both on a new rope and on a used rope that has been through a high number of bending cycles. This allows for determining how the rope’s thermal conductivity changes with use, which is a requirement for the use of temperature measurements as a method for monitoring the rope’s health.

ABSTRACT. Canonical variable analysis (CVA) is one of the most commonly applied fault detection methods for industrial systems. However, conventional CVA is unable to handle the characteristics of time-varying processes. To address the challenge of implementing diagnostics in real-world applications with time-varying prop-erties, the time-invariant CVA model is extended using first order perturbation theory, resulting in the improved adaptive CVA (ACVA) diagnostic model. Moreover, a bias-corrected exponentially weighted moving average approach is used in combination with the ACVA-based contributions to identify variables that are closely related to faults. The proposed technique is validated through condition monitoring data acquired from an operational centrifugal compressor. The results indicate that the proposed method can effectively detect and diagnose faults in real industrial systems under time-varying operating conditions.

ABSTRACT. This work presents the use of radial basis function artificial neural network to estimate the sensors readings, exploring the analytical redundancy via auto association. However, in order to guarantee good performance of the network the training and optimization process was modified. In the conventional training algorithm, although the stop criteria, such as summed squared error, is reached, one or more of the individual performance metrics, including: i) accuracy; ii) robustness; iii) spillover and iv) filtering matrix of the neural network may not be satisfactory. The paper describes the proposed algorithm including all the mathematical foundation. A dataset of a petroleum refinery is used to train a RBF network using the conventional and the modified algorithm and the performance of both will be evaluated. Furthermore, AAKR model is used to the same dataset. Finally, a comparison study of the developed models will be done for each of the performance metrics, as well as for the overall effectiveness in order to demonstrate the superiority of the proposed approach.