Priyanka Gandhi
email: priyankagandhi9@gmail.com

Product Lifecycle Management in Education: Key to Innovation in Engineering and Technology

Keywords: PLM, Education, Efficiency, Supply Chain, OEMs, Tools and Processes, Training, Productivity, Innovation, Design Engineering

Product Lifecycle Management in Education is the key to innovation and success in organizations in the engineering and technology sector. This paper illustrates that incorporation of PLM training in coursework and education of best practices, processes and solutions at educational institutions as well as organizations helps leverage the intellectual assets of an organization and turn them into deliverable assets. PLM education and training imparts vision, technical expertise and solutions to improve productivity and efficiency in the fields of engineering, business, operations and supply chain in different industries such as OEMs their suppliers, retail, pharmacy and apparel industry etc. PLM training and applications of core methods, tools and processes achieve major cost savings and resource sharing between different business segments besides advancing the innovation in engineering and technology.

Introduction

Product Lifecycle Management has become one of the fastest growing technology solutions in the last twenty years in engineering organizations. PLM has gained its popularity and established i t s scope in engineering, manufacturing, retail, apparel, pharmacy and various other industries. It h a s become imperative to e d u c a t e employees of OEMs (Original Equipment Manufacturers) and the suppliers in the use of Product Lifecycle M a n a g e m e n t t o o l s and processes. Usually the product development team and its members prior to the implementation of PLM methodologies lack the vision and empowerment to avoid wasteful PLM implementation procedures and err along the lifecycle of product development, thereby under-utilizing the "PLM potential" for a %100 successful outcome [START_REF] Stark | Product Lifecycle Management" 21st Century Paradigm for Product Realization Second Edition[END_REF].

Product Lifecycle Management education and training to experienced engineers and even recent graduates can help in producing better product development expertise, improvised skill and tool knowledge to carry out efficient design, technical competence to manage a large product base, industrial applicability to improve customer satisfaction and overall better engineering solutions to maintain and run existing processes seamlessly in the real world. Usually suppliers of engineering product/parts and services spend a humongous amount of resources in outsourcing the training and certification endeavors to OEMs or other suppliers to educate and certify their engineering workforce to g a i n the technological knowledge to excel in application of PLM solutions to their product lifecycles [START_REF] Xu | A Web-Enabled PDM System in a Collaborative Design Environment[END_REF].

Many companies have therefore realized the added value brought about by PLM Education in cost saving strategies to leverage the quality and productivity of their Product development Lifecycle. One of the essential components of Product Lifecycle Management is the knowledge of PLM tools and their functionality that forms the "Software area of the PLM" [START_REF] Stark | Product Lifecycle Management" 21st Century Paradigm for Product Realization Second Edition[END_REF]. The application of PLM knowledge to specific industries like Industrial, Aerospace, Automotive, Retail or Pharmaceutical requires the knowledge of software tools along with the ability to translate PLM vision and strategy to good design practices and philosophies. Thus application based PLM training involving case studies from experts of the specific industry, industry specific lessons learnt, knowledge of the known wasteful processes, all form an application based approach in PLM training and coaching [START_REF] Gandhi | Article: Configuration Management and PLM[END_REF].

Organizations u s i n g PLM technology are actively seeking PLM Education and training for their workforce thus driving PLM Education to schools and institutions to lay stress on their need for improving productivity and eliminating engineering design downtime. Utilizing PLM-efficient systems to drive productivity and r e s o u r c e sharing between isolated business segments that don't interact with each other and are relatively closed niche has become one of the most important goals along with core functional areas such as engineering design and product development. Karina Kogan, President of Business Management Systems at Vertex believes that PLM education is core to the success of PLM implementation in any industry. She further goes on to saying that, Vertex encourages fresh graduates and students right out of college to work in the fields of PLM and that they are even willing to go a step further beyond and install their tools and products at educational institutions so that they can be trained in fields of PLM before starting out work [START_REF] Ameri1 | Product Lifecycle Management: Closing the Knowledge Loops[END_REF].

Sue Welch, the CEO at Tradestone Software, states that she is very interested in capturing fresh talent as well as educating them on the real-world applications of PLM in the direction to succeed as future PLM leaders of the retail industry. Laura McCann, who is the CEO at Zweave, has been able to launch the first academic PLM project that supports PLM education in the retail and fashion industry. This enables the students to get the PLM knowledge and industrial experience at a much affordable cost. Gerber technology has provided free software to educational institutions for about 40 years now, so as to produce talented PLM consultants that are well versed in the PLM technology [START_REF] Stark | Product Lifecycle Management" 21st Century Paradigm for Product Realization Second Edition[END_REF]. The V.P. of Vertical Market Strategy at PTC, Kathleen Mitford says that, PTC has always pioneered PLM education at the university levels and has provided the PTC software solutions to the academic institutions for learning and development purposes. Lenny Weiss, the V.P. of sales and marketing at Yunique Solutions, says that Yunique has provided access to their PLM tools and processes to the students at FIT (Fashion Institute of Technology) to provide PLM training to the student fraternity in the retail and fashion industry. Phillippe Ribera, the PLM development manager at Lectra, states that they target over 680 fashion and design institutions to impart PLM education. Over 70 schools have implemented coursework and training on PLM technology solutions and design technology developed by Lectra in their curriculum in order to produce well trained PLM graduates for the retail and fashion industry [START_REF] Stark | Product Lifecycle Management" 21st Century Paradigm for Product Realization Second Edition[END_REF].The Vice President of R&D at Visual 2000 International, Charles Benoualid, states that he has always championed the give and take philosophy on PLM in Education. The give and take model allows him to supply free PLM software and technology for training purposes to students at universities to teach them about real life PLM technology solutions and in return the highly learned scholars in design and production with advanced degrees end up providing real solutions to customers across the globe. There are a few companies which are still thinking and giving consideration to the PLM in education perspective but are yet to adopt it. Lawson and Porine spA are a few to name [START_REF] Stark | Product Lifecycle Management" 21st Century Paradigm for Product Realization Second Edition[END_REF].

PLM Training at Educational Institutions and Universities

PLM Education at Purdue University

Purdue University has developed a detailed Research and Development Program to foster the Product Lifecycle Management subject as a philosophy and as a tool that will serve as an important building block in producing successful industry leaders in this area of technology [START_REF] Gandhi | Article: Configuration Management and PLM[END_REF]. The PLM center of excellence at Purdue is a collaboration of the colleges of engineering, science and management, that have come together to conceive a "one stop" PLM educational research and training center to the academia and industries [START_REF] Stark | Product Lifecycle Management" 21st Century Paradigm for Product Realization Second Edition[END_REF]. Purdue aims at propagating through this institute the best industry standards in PLM tools and technology by partnering with the PLM giants in business and merging them with the PLM educational community. The goals of this Research and Development center at Purdue is to advance the Product Lifecycle Management Tools and approaches by leveraging the existing PLM solutions from the tech-industry [START_REF] Gandhi | Article: Product Lifecycle Management Importance and Approach[END_REF].

Purdue University understands the value and significance of PLM as a technology and as a management discipline in today's day and age of technological innovation. The benefits of Product Lifecycle Management as comprehended at Purdue are multiple; from better visualization and management of product data management to increasing the productivity and quality of the end product, it truly understands the potential of PLM and its unrealized scope [START_REF] Stark | Product Lifecycle Management" 21st Century Paradigm for Product Realization Second Edition[END_REF].Purdue professes that PLM brings about streamlined product development at reduced costs through the different lifecycle stages of the product evolution from inception, execution to maturity in engineering design, manufacturing as well as maintenance disciplines. Encouraging PLM in Education Industry is the fundamental goal of the PLM R&D center at Purdue. Purdue University aims to establish s t rategic r elatio n sh ip s w i t h key organizations with a PLM focus through this media [START_REF] Stark | Product Lifecycle Management" 21st Century Paradigm for Product Realization Second Edition[END_REF]. Purdue hopes to surface the advancements in PLM technology from time to time and propagate the PLM tools and training in the academia t o produce future leaders. It also aims at producing better PLM career prospects and seek funding for developing the PLM R&D Initiative. Purdue also has a vision of bringing brand new organizations on board with PLM tools and technology and encouraging more and more educational institutions to i n c o r p o r a t e PLM coursework in their curriculum [START_REF] Stark | Product Lifecycle Management" 21st Century Paradigm for Product Realization Second Edition[END_REF].

PLM Education at Michigan Technological University

The PHD program in Mechanical Engineering at Michigan Technological University (MTU) has Product Lifecycle Management as one of its main focus areas under the mechanical engineering umbrella. The PHD program at MTU is one of its kind research intensive programs that foster PLM as one of the research areas of course work and dissertation. The Graduate ranking of the Doctoral Program is 48th across US according to America's best college rankings. The Undergraduate degree program in Mechanical Engineering is ranked 22 nd across US according to the Americas best college rankings. MTU is a pioneer institution that has about 7000 students enrolled in graduate and undergraduate degree programs. There are about 130 programs in arts, sciences, engineering, and several other subjects at MTU [START_REF] Stark | Product Lifecycle Management" 21st Century Paradigm for Product Realization Second Edition[END_REF].

In order to obtain the undergraduate d egree at MTU, the students need to do a senior design capstone project that tests their design knowledge. In a group of 4 to 6 students they participate in this design challenge which is believed to be more of a first job for them rather than their last class. Michigan Technological University is one of the Major Customers of Siemens that is the creator of Unigraphics their signature PLM tool and solution. Students learn Unigraphics (NX) in their undergraduate degree program when they start out and use their design skills along with the PLM software tool knowledge to propose innovative design solutions and their CAD Design skills [START_REF] Stark | Product Lifecycle Management" 21st Century Paradigm for Product Realization Second Edition[END_REF].

A typical example of a senior capstone design project was a case study with whirlpool dryers that ended up resulting in a 11 cents/ unit saving adding up to $ 1.85 million savings for the company annually [ Fig 1]. There was an option to use Pro-E as the CAD tool but the Unigraphics tool's CAM option was more suitable and familiar for the senior design team. The systems noise level requirement was also taken into consideration and there were two options developed but it was demonstrated that one of the option that couldn't meet the systems noise requirements was rejected and the other option which met or exceeded the systems noise level requirements was chosen which led to savings of 11 cents per unit and $1.85 million annually [10]. PACE is t h e "Partners for the Advancement of Collaborative Engineering Education" Program that links several institutions academically including the Michigan Technological University for the development of PLM solutions that cater to the automotive O E M s . Several key team players of the Automotive I n d u s t r y participate in judging the PACE endeavor like GM, Siemens, HP, Oracle, etc. PACE fosters the goals of PLM to provide Product Lifecycle Management as an integrated engineering solution from conceptualizing, product development, marketing, distribution, maintenance and ultimately disposition and recycling of the product, if necessary [START_REF] Gandhi | Article: Configuration Management and PLM[END_REF].

PLM Education at Oakland University

The center for Product Lifecycle Management at Oakland University in Michigan is one of its kind institutes that inculcate the important lessons of PLM implementation in the form of coursework offerings. Oakland University has developed a center for PLM Education that will touch upon the three areas of Product Development, PLM (Product Lifecycle Management), ERP (Enterprise Resource Planning 5. Customer Satisfaction and Product Support through its Lifecycle.

6. Reducing the impact of the product on the environment thus easing the recycling and disposition process.

The academic institutions in Michigan are striving hard to develop the PLM skills in their students and while doing so they face the challenge of lack of I.T. infrastructure to provide them with the necessary tools and processes. A collaborative online approach that provides them the necessary tool infrastructure and support along with the course curriculum is thus needed [START_REF] Stark | Product Lifecycle Management" 21st Century Paradigm for Product Realization Second Edition[END_REF]. The academic center has relationships with essential PLM vendors that can help provide the necessary IT infrastructure and the non-member academic institutions can in turn partner with this academic center in order to reap the benefits of their accessibility to the PLM tools and technology made available at this academic center. The academic center is also aiming at providing software tools installation and IT support to the member schools and services as the IT hub that all the member institutions can go to with license installation issues and tool support requirements [START_REF] Stark | Product Lifecycle Management" 21st Century Paradigm for Product Realization Second Edition[END_REF].The academic center also aims at including PLM course offerings especially in the technology track courses like the masters in engineering management program to include the PL/ERP/MES courses. The academic center also aims at starting virtual manufacturing labs where the member institutions can access the software tools necessary to simulate manufacturing environments to test the feasibility of their product design. Virtual labs are better than physical labs since they do not need the full scale IT infrastructure to function [START_REF] Gandhi | Article: Configuration Management and PLM[END_REF]. As schools always face the lack of funds and staff to maintain and run the individual labs, the virtual labs help them to train their students in manufacturing domain of the PLM without the need to set up an actual lab [START_REF]Understanding Product Lifecycle Management[END_REF]. The goals of the academic center are clearly also in line with the vision of President Obama who envisions that America is in need of smarter engineering and manufacturing solutions that create products and jobs within America versus outsourcing them to Asia or Europe. For the overall success of technology and innovation in USA, it's imperative to bring technology learning in schools and at the academic level [START_REF] Xu | A Web-Enabled PDM System in a Collaborative Design Environment[END_REF].

Strategic Partnerships between Academic Institutions and Organizations to foster PLM

One example of a significant relationship between academic institutions and Organizations in the fields of PLM is the example of Siemens and Oakland University located in Rochester, Michigan. Siemens has provided Oakland University approximately $ 12 million in software licenses and products that will directly benefit the students in becoming future PLM leaders. Siemens has always propagated that it will support Oakland University in producing smart graduates that are well versed in PLM design and implementation m e t h o d o l o g y . In order to encourage and support Oakland University's PLM center's initiative, Siemens has come forth and provided the access to software licenses particularly the Technomatix Robcad Software amounting to $ 11,846,850. This software will enable in design, validation as well as automation of the manufacturing processes [START_REF] Stark | Product Lifecycle Management" 21st Century Paradigm for Product Realization Second Edition[END_REF]. This is a pure example of academic institutions partnering with organizations to foster PLM education in Research and Development. Professor Robert Van Til from the department of Industrial and Systems Engineering Department vouches for the contribution of Siemens PLM software in establishing Oakland University as a premier PLM R& D center. Oakland University believes that this software along with other software licenses and products supplied by Siemens helps greatly in producing educated PLM graduates and helps promote the quality of the academic program significantly. Tom Hoffman, marketing director at Siemens PLM software for manufacturing processes believes that Siemens has been and will continue to be a major contributor to the academic wealth and knowledge bank in the field of PLM at academic institutions like Oakland. Organizations like Siemens have contributed significantly in turning South East Michigan as a major hub of PLM Engineering Services. Siemens feels privileged to be a supporter of the "STEM" programs offered at Oakland University. In return the students from Oakland University contribute to the l e a n m a n u f a c t u r i n g processes through these robotic software licenses [START_REF] Gandhi | Article: Product Lifecycle Management Importance and Approach[END_REF]. Siemens has a distinct interest in donating and giving back to the community through its "GO PLM" initiative. The director of "GO PLM" initiative, Hula King says that they want to continue to provide PLM licenses and software to Oakland University to encourage the R&D Center to grow, as these software tools are not available readily and only used by multinational companies across the globe. This is a huge advantage to the academic development. Professor Robert Van also states that Siemens support further extends to training and support in the usage of their software and products to their academic community [START_REF] Gandhi | Article: Configuration Management and PLM[END_REF].

Dassault Systems is the world leader in PLM tools and technology like ENOVIA, DELMIA and SIMULIA. Dassault Systems and Oakland University have also partnered in coming up with a short 4 weeks post graduate course in PLM at the Academic Center for PLM research and development. This course has been developed with the collaboration of the School of Engineering and Computer Sciences (SECS) that integrates both engineering and business expertise. The main goal of this partnership was to retain the workforce within Michigan and to further the PLM endeavor as well [START_REF] Gandhi | Article: Configuration Management and PLM[END_REF]. Displacement of worked due to involuntary job loss was a common phenomenon in 2009 due to recession and to avoid the displacement of engineering workforce this step was taken [START_REF] Ameri1 | Product Lifecycle Management: Closing the Knowledge Loops[END_REF].

Roy Smolky of DELMIA Academic Relations Program from Dassault believes that this program is the right step in the direction of retaining workforce within Michigan State itself as well as spreading the importance of the PLM subject matter expertise to produce future PLM leaders. The students during the course will be learning in detail the Dassault System DELMIA suite of tools for digital manufacturing and production and after completion of the course they will be administered to take the DELMIA proficiency certification exam. Professor Robert Van feels that this course is different from conventional professional courses as it is more hands on in training provided by Dassault Systems in the tools which will definitely experience double digit growth in the next 5 years [START_REF] Grieves | Product Lifecycle Management[END_REF].

Fig. 1 :

 1 Fig. 1: Whirlpool Dryer Senior Design Capstone Project at Michigan Technological University. A dryer designed by MTU students that led whirlpool to alter its design and bring about savings worth $1.85 million dollars is shown above. Michigan Technological University teaches a program on engineering modeling and design course the ENG1102 where eight students participate annually in the PACE design competition showcasing innovative design solutions to a panel of judges appointed by the MTU. The criteria for the selection of the best design project includes, form, fit, function of the design and the presentation and feasibility of the design. Examples of PACE winning team projects include a robotic vehicle and projects utilizing the alternative energy sources like solar and wind energy [9].

  ) and MES (Manufacturing E x e c u t i o n Systems) in order to keep the jobs within the state of Michigan itself [Fig 2] [8]. The goals of the Academic Center of Excellence for PLM at Oakland University can be summarized into the following five points [Fig 3]: 1. To act as the main point of origination of Leadership Strategies for Development of the PLM Workforce.

  The IFIP WG5.1 11th International Conference on Product Lifecycle Management -PLM14Yokohama, Japan 7 th -9 th , July, 2014 2. Collaborate the academic center for PLM with Local K-12 schools and community colleges.

Fig 2 :

 2 Fig 2: Functional Areas of I.T. Enterprise Architecture. The figure shows the three integrated areas of Product Lifecycle Management, Enterprise Resource planning, and Manufacturing Execution Systems [6].

Fig 3 :

 3 Fig 3: Academic Center for PLM at Oakland University. This figure shows the breakdown of integrated areas of PLM

Fig 4 :

 4 Fig 4: Stages of PLM. This figure shows the different stages of Product lifecycle management.

Acknowledgments: Purdue Center of R&D for PLM, Oakland Center for PLM, MTU Center for PLM, Whirlpool, Dassault Systems.

Author:

Priyanka Gandhi


Gary Ford

Joel Igba

Chris Mcmahon

Kazem Alemzadeh

Chris Rowley

Keld Henningsen

Knowledge Management: A Cross Sectorial Comparison of Wind Generation and Naval Engineering

Keywords: Knowledge Management, Offshore Wind Farm, Naval

des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

This paper details a comparison of Knowledge Management (KM) in two distinct engineering domains, i.e. offshore Wind Farms (WF) and marine engineering in the Royal Navy (RN). Each domain may be viewed as a system of systems, i.e. whose system elements are themselves systems; typically these entail large scale interdisciplinary problems with multiple, heterogeneous, distributed systems [START_REF]Systems Engineering Handbook. A Guide for System Life Cycle Processes and Activities. Ver. 3.2 INCOSE[END_REF]. The KM issues are particular to each technology, however, a number of similarities and differences are seen to exist. The approach taken is as follows. After outlining key characteristics KM the paper examines each domain and summarises and compares a number of issues during in-service.

Knowledge Management

The Knowledge is a relatively simple word; indeed the Oxford English Dictionary defines knowledge as "awareness or familiarity gained by experience" [START_REF]The Concise Oxford Dictionary of Current English[END_REF]. Within an enterprise, knowledge may be seen as the cumulative data/information acquired and developed, both tacit, written and recorded. The function of preventing its loss/corruption and thus obviating the time, experience and effort required to recreate may be seen as Information Management (IM). KM encompasses IM but also extends the capability and value of information by providing a Knowledge Lifecycle [START_REF] Ammar-Khodja | An Overview on Knowledge Management[END_REF].

Charles Dickens in "A Tale of Two Cities" declares, "It was the best of times, it was the worst of times" [START_REF] Dickens | A Tale of Two Cities[END_REF]; KM may be viewed similarly. The "best of times" is reflected in the capability of hardware and software technology, whereas, "the worst of times" is illustrated by the lack of structure, accessibility, volume, etc. and potential unknown value of a strategic resource.

According to Wong et al. [START_REF] Wong | Informing preliminary design by incorporating service knowledge[END_REF], there are four key activities in KM -creation, mapping, retrieval and reuse of knowledge. Other authors such as Goh and McMahon [6] may describe these activities as a process of knowledge capture (collection), feedback and reuse. With respect to the challenges in KM, there is not a very clear boundary which distinguishes the challenges faced in each activity of KM. However, with the advancement in information technology, one can easily know what the challenges are and where they lie. For instance, McMahon and Ball [START_REF] Mcmahon | Information Systems Challenges for through-life Engineering[END_REF] stated: "We are constrained now not by the ability to capture but by our ability to retain, organise and interpret the information (and to some extent by our ability not to be overwhelmed by the quantity of data that we can capture)". This implies that with the amount of data we can capture now, much effort is also needed to ensure knowledge feedback and reuse, suggesting that data has no value if it is not used for a purpose [START_REF] Markeset | Integration of RAMS and risk analysis in product design and development work processes A case study[END_REF]. Furthermore, information reuse only occurs when it has been assimilated and used in new applications, producing useful insights and knowledge [START_REF] Goh | Improving reuse of in-service information capture and feedback[END_REF], for example -using in-service knowledge for new product development.

Offshore Wind Power

The gradual shift in trend from onshore to offshore wind power, which has largely been due to social and political reasons [START_REF] Hameed | Challenges in the reliability and maintainability data collection for offshore wind turbines[END_REF], has resulted in the steady growth of the offshore wind sector. However, the offshore wind sector is still in its nascent state, hence lots of new ideas and concepts needed to cope with the hostile marine environment keep emerging [START_REF] Hameed | Challenges in the reliability and maintainability data collection for offshore wind turbines[END_REF]. Examples of such new concepts can be seen in the evolution of offshore wind turbine foundation structures [START_REF] Berkhout | Wind Energy Report Germany[END_REF] and the pre-assembly of parts of the turbine on floating vessels while ashore before shipping to the offshore environment to install.

Offshore WFs are complex engineering systems which harness the energy from wind to generate electrical power. The nature of this complexity is not only defined by the number and interactions of systems that comprise the WF, e.g. electromechanical, structural, control, etc. It is also defined by the considerable number of inputs from nearly every field of engineering and many of the natural and even social sciences [START_REF] Dykes | Applications of systems engineering to the research, design, and development of wind energy systems[END_REF]. The WF itself is made up of individual wind turbines which are all interconnected to the grid. Furthermore, the extended supply chain related to the transportation, installation and operations & maintenance of WFs [START_REF] Dykes | Applications of systems engineering to the research, design, and development of wind energy systems[END_REF], which are heavily influenced by the weather and sea conditions [START_REF] Hameed | Challenges in the reliability and maintainability data collection for offshore wind turbines[END_REF][START_REF] Igba | A Systems Approach Towards Reliability-Centred Maintenance (RCM) of Wind Turbines[END_REF], also contribute to the complexities of offshore wind power life cycle management. Other complexities result from the broad mix of stakeholders involved throughout the life cycle of offshore wind. Of interest in this paper are the issues relating to knowledge and information management during the in-service stage, which arise as a result of these complexities.

Naval Engineering

Unlike offshore wind power the RN has existed since the reign of King Henry VIII (1491 ~ 1547) and his development of a "Navy Royal". The design and configuration of a naval vessel is intended to provide a "sustained" capability as described in the Concept of Operations, e.g. air defence, humanitarian relief.

Capability requirements may be conflicting and competing, e.g. stable and maneuverable platform, capable of operating from the arctic to the tropics, fuel efficient but able to sustain 30+ knots, deck space for weapons and sensors but clear for replenishment at sea, etc. KM is utilised at the earliest stages of the lifecycle, whereby previous experience and designs are included / excluded. Indeed a modern naval vessel will encompass more than 100 integrated hard systems [START_REF]The Collins Class[END_REF], linked electrical, hydraulically, mechanically, etc. Furthermore, the complexity of modern naval vessels dramatically skews the comparative cost of systems and hull, In the United Kingdom, systems represent the biggest percentage of the price of a warship -70% compared to 30% for the hull. This is in stark contrast to commercial vessels, where almost the reverse is true, i.e. 20% systems, 80% hull [START_REF] Choi | The Costs of 21st Century Shipbuilding: Lessons for Canada from the Littoral Combat Ship Program[END_REF].

Preventive maintenance is undertaken to sustain the capability of the vessel: the RN utilise Reliability Centred Maintenance (RCM). The methodology was selected following a review of failures in a Type 23 Frigate and comparing them with the Age-Reliability Patterns developed by Nowlan and Heap [START_REF] Nowlan | Reliability Centered Maintenance[END_REF]. The results indicated within the naval domain only 7% of failures may be attributed to "wear" (Pattern A to C) whilst 93% were "random" (Pattern D to F) (Figure 1). It should be noted KM is incorporated at the early stages of formulating the maintenance package to ensure "lessons learnt" are incorporated.

Similar to offshore wind power, a broad mix of stakeholders are involved throughout the life cycle of a naval vessel, e.g. RN, Ministry of Defence (MOD), Babcock, BAe. Issues related to KM during the in-service stage will be reviewed.

Current State-Of-The-Art in Knowledge Management and Challenges

Ford et al. [START_REF] Ford | Product Life Cycle Data Management: A Cross-Sectoral Review[END_REF] previously identified that the major challenges the wind industry face in life cycle KM are observed during the in-service stage. However, to build upon this and expand further, a brief review of the state-of-the-art of in-service KM in the offshore wind sector would be done. This would provide some context to the issues and challenges during in-service KM specific to offshore WFs. Previous authors would agree that majority of the challenges experienced during the in-service stage of offshore wind turbines arise as a result of the harshness and unpredictability of the offshore environment. Furthermore, typical offshore WFs are sited at remote locations at distances from the shore ranging from about 5km to more than 50km [START_REF] Berkhout | Wind Energy Report Germany[END_REF]. Hence, be it transportation and logistics, or operations and maintenance, weather effects are a major source of uncertainty whilst in-service. This has prompted the need for extensive forecasting, planning and scheduling of tasks and activities, in a flexible manner so as to avoid delays caused by weather and sea conditions. Specific to KM, due to the remoteness of offshore WF's, the industry's state-of-the-art are remote monitoring and control through condition monitoring systems (CMS) and supervisory control and data acquisition (SCADA) systems. SCADA systems were primarily installed in wind turbines to measure operational and environmental conditions, such as wind speed, ambient temperature and temperature/pressure sub-systems in the turbine [START_REF] Yang | Wind turbine condition monitoring: technical and commercial challenges[END_REF]. On the other hand, CMS are used to monitor parameters such as vibrations, acoustic emissions, and oil particle counts, to name a few. These two remote monitoring techniques produce large quantities of data collected either as 10 minute averages or even every 10 seconds. Apart from the remote monitoring data acquisition systems, other manual or human assisted techniques exist for documenting in-service records. These include: service or work orders, inspection reports and maintenance, repair and overhaul reports. Unlike the automated remote CMS and SCADA techniques, knowledge captured through One of the main issues with remote monitoring is linked to the size of data generated. Having huge data collected from a large number of turbines poses challenges in analysing and interpreting the data. Fast growing databases from remote monitoring of offshore WF's require advanced signal processing techniques and data mining to extract the most useful information [START_REF] Nie | Review of Condition Monitoring and Fault Diagnosis Technologies for Wind Turbine Gearbox[END_REF]. However, such data are not without noise and can result in generating poor models [START_REF] Feng | Use of SCADA and CMS signals for failure detection and diagnosis of a wind turbine gearbox[END_REF]. It is also difficult to convincingly interpret and convey the results of analysis obtained from remote monitoring to wind farm managers and specialists [START_REF] Feng | Use of SCADA and CMS signals for failure detection and diagnosis of a wind turbine gearbox[END_REF].

Finally, there are concerns about the reliability and accuracy of the sensors that acquire the data [START_REF] Yang | Wind turbine condition monitoring: technical and commercial challenges[END_REF], for instance, if the sensors are not installed properly and in the right location, the data collected might be erroneous. Hence a lot of effort is needed in the design and development stage in specifying remote monitoring technologies and their installation and operation.

2.) KM Challenges in Manual Techniques:

The primary challenge with capturing manual data is the issue with physical access to the WFs. Harsh weather conditions make it almost impossible to even attempt to capture maintenance records from inspections and other maintenance tasks in the turbine. For example, WFs which are just a few kilometers offshore have been previously known to have experienced months with over 20 unworkable days.

When service personnel eventual have access to the turbines there is then the inability to complete maintenance records within the turbine due to safety concerns and space limitations [START_REF] Ford | Product Life Cycle Data Management: A Cross-Sectoral Review[END_REF]. Hence, technicians who keep record of maintenance activities and inspections may have to result to other means like taking photographs and then completing the reports after leaving the turbine. The time lag between when the inspection is done to when reports are produced depends on the technician and is difficult to control. There is also the possibility of data being diluted and of poor quality between the time the maintenance task is done and when the report is made, since the technician may forget a few details even in the presence of pictures.

Furthermore, since the periods of access to the turbine is largely dependent on the weather and hence not predetermined, there is a risk of inconsistency in the periods between data capture. Hence the accuracy of captured maintenance data heavily depends on the selection of a suitable observation window [START_REF] Hameed | Challenges in the reliability and maintainability data collection for offshore wind turbines[END_REF]. For example, maintenance visits should be planned and periodic, giving consistency to findings, i.e. monthly, quarterly, yearly or a period defined by the age or condition of the turbine. However, this is very difficult to achieve for offshore WFs, hence giving difficulty in collating records to make suitable judgments about the service history of the turbines. As maintenance reports are largely a mix of hand written or typed spread sheets, there is always the risk of typographical and spelling errors [START_REF] Hameed | Challenges in the reliability and maintainability data collection for offshore wind turbines[END_REF].

A naval vessel will encounter similar issues with respect to the harshness and unpredictability of the marine environment; however, unlike a static WF a vessel whilst in transit may experience large variations in temperature, humidity and movement, i.e. heave, sway and surge in addition to shock and vibration. Unlike a WF, RN vessels have onboard operators and maintainers, however, base support, spares and tools may be thousands of km away [START_REF] Roulston-Eldridge | HMS Illustrious Port Outer Gas Generator Exchange The Last Mount of Olympus at Sea? The Naval Engineer[END_REF] or not available due to operational constraints. For example, a Vanguard class submarine will remain submerged for 3 months with no contact or support but none-the-less required to provide 100% availability and capability throughout each patrol.

The RCM process formulates a maintenance regime which enables a maintainer to perform maintenance and ascertain the material state. Data created and utilised by maintainers includes, engineering logs, vibration data, oil samples, running hours, etc. The onboard operational maintenance data is typically objective and structured, e.g. diesel engine hours run. However, if a vessel encounters a defect that impacts the operational capability, assessment by naval command will often necessitate a subjective assessment of potentially unstructured and aggregated data.

Summary

It seems that offshore WF's largely rely on remote monitoring for obtaining information about the operational and performance data. Remote access provides the possibility of controlling wind turbines in multiple WFs from a central remote location. Another advantage not immediately apparent is the ability to optimise power production from the wind farm by matching operating and environmental conditions with wind turbine controls. One example of this, is the pitch control [START_REF] Berkhout | Wind Energy Report Germany[END_REF][START_REF] Yang | Wind turbine condition monitoring: technical and commercial challenges[END_REF][START_REF] Feng | Monitoring wind turbine gearboxes[END_REF] of each individual blades to adapting blade angle to wind conditions so as to provide the optimum power output and noise levels. Even though state-of-the-art remote monitoring techniques are capable of providing useful measures of the condition of the major systems that constitute the WF, WF operators and technical specialists still rely on the information that are collected manually through human effort. The visual inspections, images and measurements taken manually, provide more explicit details about the nature of wear and tear in the turbines.

Given that WF operators need to rely on both sources of knowledge for life cycle management, it will also be useful to identify some common issues affecting both techniques. Some of the general issues with KM in offshore wind include:

 Inconsistency in data file formats: A typical modern WF would have at least a combination of 10-Minute average SCADA data, fault/alarm logs, service orders and O&M contractor reports [START_REF] Wilkinson | Methodology and Results of the Reliawind Reliability Field Study[END_REF]. Service and O&M reports, unlike SCADA, are a mixture of spreadsheets and hand written reports. As a consequence, a lot of effort is needed in filtering and preprocessing these disparate sources in order to aggregate them for suitable analysis. This poses a challenge of data reuse when seeking to combine data from multiple sources in order to make inferential judgments from it. It also increases the lead time to decision making as more time and effort is consumed in harmonising the information contained in different data sources. Experience by previous research have shown that a substantial effort is needed to connect these different sources [START_REF] Wilkinson | Methodology and Results of the Reliawind Reliability Field Study[END_REF].  Organisational (institutional) barriers exist with respect to ownership of failure data of the wind turbine components. For example during the warranty period operators have general information of the number of failures and the general types, but may not have information of their root causes [START_REF] Walford | Wind turbine reliability: understanding and minimizing wind turbine operation and maintenance costs[END_REF].

 Missing or incomplete information is very likely to occur in maintenance records, due to the weather and location effects interrupting scheduled service or inspections. In-Service KM in the naval domain may be considered to exist in two distinct spheres, i.e. onboard and onshore. The onboard data and knowledge may be considered "tactical", i.e. single vessel, local, immediate, single stakeholder, whereas onshore has a "strategic" focus, i.e. aggregation of multiple vessels / systems, remote, latent, long term planning, multiple stakeholders. The "Common knowledge" relates to the interface and interaction of onboard and onshore knowledge The onboard management, maintenance information flow and KM is extremely hierarchical, e.g. junior operator/maintainer  senior maintainer  junior officer  Marine Engineering Officer (MEO). The MEO and staff have an enduring responsibility for "the good material order and maximum availability of all equipment and systems within its responsibility, in order to maintain the seagoing and fighting capability of the ship" [START_REF] Br | BR ██ -██ Marine Engineering Department Standing Orders[END_REF]. Objective information originates from discrete systems and is collected by junior operators/maintainers which is collated, processed, aggregated and analysed by senior staff often requiring a subjective assessment of numerous information sources and influences both internal and external. The combination of structured / unstructured and objective / subjective information may be seen to exist as a matrix (Table 1), i.e. As information passes up the management hierarchy, e.g. typically originating in Sector 3, a broader perspective and higher level of KM function may be seen to exist as it passes to Sector 2. Whereupon the MEO may be expected to fuse numerous information sources / controls / enablers, deliberate and decide upon a course of action. Onboard, a large number of knowledge sources exist, e.g. Standard Operating Procedures (SOP), Books of Reference (BR), work books, tacit knowledge.

Onshore "strategic" knowledge Onboard "tactical" knowledge

Common knowledge

Reflecting upon the principles of KM detailed by Wong et al [START_REF] Wong | Informing preliminary design by incorporating service knowledge[END_REF], the onboard KM process is established, controlled and structured.

The onshore KM and associated stakeholder activity is dependant upon the function / role of the vessel, e.g. Upkeep (deep maintenance), Tasking (operational deployment). The KM activity of assessing the material state of a Tasking vessel and hence its operational capability is primarily the monitoring of Operational Defects, i.e. defects that may degrade the capability of the vessel -as contained within the "Common knowledge". The KM assessment is highly subjective and is frequently dependant upon the tacit knowledge of RN personnel within the context of the mission. The onshore KM of a Tasking vessel may be seen to exist extensively in Sector 2.

Prior to Upkeep, stakeholders responsible for deep maintenance will be dependant upon information that is highly subjective, e.g. diesel generator #1 is a bit noisy. However, a key KM function during Upkeep is the generation of detailed objective and structured information (Sector 3), e.g. survey reports, defects. The formulation of such information facilitates logical decision making, e.g. if valve leaking then replace. It also enables searching and comparison with previous records to enable reuse of existing knowledge.

Onshore, an even greater knowledge bases exists, e.g. design documentation, test spec's, original equipment manufacturer, SOP's, BR's, work books, tacit knowledge. Once more, reflecting upon the principles of KM detailed by Wong et al [START_REF] Wong | Informing preliminary design by incorporating service knowledge[END_REF], the onshore KM process is also established, controlled and structured.

Conclusion

The KM process within the naval engineering domain is "mature", having been developed and refined over considerable time, whereas wind generation has yet to refine its procedures. The issues identified by wind generation, i.e. (i) inconsistency in data file formats and (ii) missing or incomplete information, also exist in the naval domain. However, they are not as prevalent as there is a single customer, i.e. MOD, instead of multiple. Furthermore, the issue of "organisational (institutional) barriers" is markedly less given the support of surface ships is undertaken by a Surface Ship Support Alliance. Consequently, all members of the alliance work together in support of the RN rather than in competition. Finally, the maturity of the naval engineering process and artefact is a key factor in minimising the issues compared with wind generation.

Figure 1 :

 1 Figure 1: Distribution of failures -Type 23 Frigate [16]

  Pattern A -Bathtub Pattern B -Traditional Pattern C -Gradual Increasing Pattern D -Low failure rate Pattern E -Random Failure Pattern F -Reverse J Curve these means are only obtained on an interval basis, depending on how frequent such service or maintenance actions are required. 1.) KM Challenges in Remote Monitoring Techniques:

Figure 2 :

 2 Figure 2: Onboard/onshore knowledge spheres

Table 1 :

 1 Information matrix

		Objective	Subjective
		Sector 1	Sector 2
	Unstructured		Complex / complicated
		Sector 3	Sector 4
	Structured	Simple, e.g. hours run

Acknowledgments. The work reported was supported by the Bristol/Bath Industrial Doctorate Centre in Systems, funded by EPSRC grant EP/G037353/1.


I Pontes Duff

S Gugercin

C Beattie

C Poussot-Vassal

C Seren

H 2 -optimality conditions for reduced time-delay systems of dimension one

Keywords: model reduction, optimal H 2 approximation, time-delay systems

In this note, we first attempt to generalize the H 2 optimal interpolation conditions for more general reduced order models. To this aim, we first expose the necessary optimality conditions in the case where the reduced system is of dimension one and have a single state delay structure. This can be viewed as a first step toward the H 2 optimal model approximation where the reduced system correspond to an infinite dimensional system. Finally, we illustrate the results with an academic example.

INTRODUCTION

Let us suppose we are given a stable Single-Input/Single-Output (SISO) linear dynamical system described by its transfer function G(s), which is assumed to be meromorphic with poles in the open left half-plane C -(hence analytic in the open right half-plane C + ). A priori, no particular structure will be imposed for the transfer function, although in practice G(s) should represent either a finite dimensional, but large scale, dynamical systems or an infinite-dimensional one, e.g., time-delay systems and irrational transfer functions.

We assume G(s) to be a function in H 2 , the Hilbert space of complex-valued functions F : C → C that are analytic in the open right-half plane (Re(s) > 0) and such that R F(iω)F(iω)dω < ∞. If s ∈ C, we denote its complex conjugate by s ∈ C. This Hilbert space is equipped with the H 2 -inner product defined as,

H, G H2 = 1 2π ∞ -∞ H(iω)G(iω)dω, for H, G ∈ H 2 with the corresponding induced-norm G H2 = G, G 1 2
H2 . Notice that if G(s) and H(s) represent real dynamical systems then H, G H2 = G, H H2 and G, H H2 is real. In addition, G(s) ∈ H 2 is strictly proper system if lim ω→∞ G(±ωi) = 0.

Firstly, let us consider, for given order r, another model Ĥ ∈ H 2 whose transfer function is given by a finite dimensional descriptor state-space

Ĥ(s) = Ĉ( Ês -Â) -1 B, (1)
where Â, Ê ∈ R r×r , and B, ĈT ∈ R r×1 . The problem of finding a reduced order system Ĥ which is the best H 2 approximation of G ∈ H 2 , i.e.,

G -Ĥ H2 = min

H ∈ H 2 order(H) = r G -H H2

(2) has been largely investigated, see for example [START_REF] Meier | Approximation of linear constant systems[END_REF], [START_REF] Antoulas | An overview of model reduction methods and a new result[END_REF], [START_REF] Gugercin | H 2 model reduction for large-scale linear dynamical systems[END_REF]. The necessary optimality conditions of this problem where first introduced by [START_REF] Meier | Approximation of linear constant systems[END_REF] as interpolation conditions for the SISO case and then generalized to MIMO systems by [START_REF] Gugercin | H 2 model reduction for large-scale linear dynamical systems[END_REF] and [START_REF] Van Dooren | H 2 -optimal model reduction of MIMO systems[END_REF]. These latter can be stated as follows:

Proposition These conditions motivated the development of interpolationbased methods to construct the reduced order model Ĥ and this has been a research topic with a lot of new contributions in the past ten years; see for instance [START_REF] Antoulas | Approximation of Large-Scale Dynamical Systems[END_REF] [START_REF] Mayo | A framework for the solution of the generalized realization problem[END_REF], [START_REF] Gugercin | H 2 model reduction for large-scale linear dynamical systems[END_REF] Here, we are interested in revisiting Proposition 1 in the case where the reduced order model has a different structure. Hence, we should consider a reduced order model having the following coprime structure Ĥd (s) = Ĉ(s) K(s) -1 B(s), which is more general than the finite dimensional state-space representation. Indeed, a great amount of models can be represented by such coprime structures and some interpolation-based model reduction methods were already developed; see [START_REF] Beattie | Interpolatory projection methods for structure-preserving model reduction[END_REF] for structure preserving interpolation; for timedelay systems (e.g., K(s) has a multiple-delay structure) see Scarciotti andAstolfi (2014, 2015b) for matching moments using Sylvester equations and Pontes Duff et al. (2015a), [START_REF] Schulze | Data-driven interpolation of dynamical systems with delay[END_REF] and Scarciotti and Astolfi (2015a) for data-driven framework. In this paper, we will consider the case where the reduced order system is described by a single time-delay equation. Therefore, we have B(s) = φ ∈ R, Ĉ(s) = 1 ∈ R and K(s) -1 = 1 s-αe -τ s , with α ∈ R and τ ∈ R + , and its transfer function is given by

Ĥd (s) = φ s -αe -sτ ∈ H 2 . ( 4
)
We will consider the delay τ is fixed. We call such model Ĥd a single reduced time-delay model of dimension one.

The word dimension here refers to the minimal number of delay-differential equations necessary to represent the model. The model Ĥd has the following time-domain representation:

Ĥd := ẋ(t) = αx(t -τ ) + φu(t) y(t) = x(t)
Hence, the approximation problem is stated as follows :

Problem 1. Given a stable model G(s) ∈ H 2 and τ ∈ R + , find a model Ĥd = φ s-αe -sτ ∈ H 2 such that G -Ĥd H2 = min ( φ, α)∈R 2 G - φ s -αe -sτ H2 (5)
Although the reduced order system is defined only by two real parameters, i.e., φ, α ∈ R, its infinite dimensional structure generates some very rich H 2 -optimality conditions. Moreover, the results presented here can be seen as a first step towards the H 2 -optimality conditions for more general reduced models.

Notation. From now on, the model Ĥd will be decomposed as

Ĥd (s) = φP τ (s)
where φ ∈ R is the gain part, and P τ (s) = 1 s-αe -sτ is the transfer function containing the spectral information of Ĥd .

Contribution. The main contribution of this paper is to present the generalization of the H 2 -optimality conditions for single reduced time-delay models of dimension one. Moreover, some new H 2 -inner product formula based on the infinite partial fraction decomposition of a single timedelay model is developed throughout Section 2.

Outline. The paper is organized as follows: Section 2 introduces preliminary results on the H 2 -inner product and on the spectral decomposition of single time-delay models. Section 3 presents the main results of this paper, namely the first order optimality condition from Problem 1. Finally, Section 4 illustrates those conditions through an academic example.

PRELIMINARY RESULTS

In this section we provide some new results about the H 2 inner-product computation based on the pole-residue decomposition and about the spectral decomposition of Ĥd . Those results will be useful to prove the main result stated in the next section.

H 2 inner-product properties

Firstly, here is a list of some important properties of the H 2 inner-product: Proposition 2. (H 2 inner-product properties). Let G, H ∈ H 2 are strictly proper transfer functions. Let us suppose moreover that G , H ∈ H 2 . Then the following properties hold:

(1) If φ ∈ C and λ ∈ C -, then φ s-λ , G H2 = φG(-λ).

(2) The derivative with respect to s is an Hermitian operator, i.e., H , G H2 = H, G H2 .

( 1) is an implication of the Cauchy's residues theorem (see [START_REF] Antoulas | Approximation of Large-Scale Dynamical Systems[END_REF] and [START_REF] Gugercin | H 2 model reduction for large-scale linear dynamical systems[END_REF]). Item ( 2) is obtained using integration by parts as follows. Let H, G ∈ H 2 and let us consider the integral over [-ω, ω]. By applying integration by parts one obtains :

) If φ ∈ C and λ ∈ C -, φ (s-λ) 2 , G H2 = -φG (-λ). Proof Item ( 3
S ω = ω -ω H (iω)G(iω)dω = 1 i H(iω)G(iω) ω -ω Rω + ω -ω H(iω)G (iω)dω Tω .
Since H and G are strictly proper elements of H 2 , then

H H2 < ∞, G H2 < ∞, and lim ω→±∞ H(iω)G(iω) = 0.
In addition, we can take the limit when w goes to infinity because H, H , G and G ∈ H 2 . Hence, the result follows noticing that S ω → H , G H2 , T ω → H, G H2 and R ω → 0 when ω → ∞. Finally, item (3) is obtained by observing that φ s-λ = -φ (s-λ) 2 and applying (1) and (2).

Spectral decomposition of Ĥd

A characterization of the spectral decomposition of Ĥd can be given in terms of the Lambert function. Let us recall the definition of this function. Definition 1. (Lambert function W k ). The Lambert function W k (s) is a multivalued (except at 0) complex function associating for the k th complex branch, a complex number W k (s) such that :

s = W k (s)e W k (s) , k ∈ Z (6) i.
e., given a s ∈ C, for each complex branch. Equation ( 6) has one solution, namely W k (s) (See [START_REF] Corless | On the lambertw function[END_REF]).

The Lambert function has many applications for the analysis and control of time-delay systems (see [START_REF] Yi | Time-delay systems: Analysis and control using the Lambert W function[END_REF]). With the help of the Lambert function, one is able to determine the poles and the infinite partial fraction decomposition of Ĥd . This is stated in the following proposition.

Proposition 3. Let Ĥd = φ s-αe -sτ . Then, the model Ĥd has infinite poles which can be computed using the Lambert function as follows :

λ k = 1 τ W k (τ α), for k ∈ Z (7)
and Ĥd is stable iff 0 < -α < π 2τ . Moreover, if Ĥd = φP τ , the infinite partial fraction decomposition of P τ = 1 s-αe -sτ is given by

P τ (s) = ∞ k=-∞ φ k 1 s -λ k , (8)
where

φ k = 1 1 + τ λ k .
Proof The poles of Ĥd (s) are the zeros of d(s) = sαe -sτ . Let us suppose that λ k is the pole on the kth complex branch. Then, applying the Lambert function definition, we have

λ k e λ k τ = α ⇔ λ k = 1 τ W k (τ α).
See Cepeda-Gomez and Michiels (2015) for more details.

In order to obtain the partial fraction decomposition of P τ (s) = 1 s-αe -sτ , one should apply the residues formula. Thus, since all the poles of P τ (s) are simple:

φ k = lim s→λ k P τ (s)(s -λ k ) = 1 lim s→λ k s-αe -sτ s-λ k = 1 (s -αe -sτ ) | s=λ k = 1 1 + τ αe -λ k τ = λ k = αe -λ k τ 1 1 + τ λ k .
See Pontes [START_REF] Duff | Model reduction for norm approximation: An application to large-scale time-delay systems[END_REF] for more details.

One should note that Ĥd has an infinite number of poles and that is why it represents an infinite dimensional model.

We present now the infinite partial fraction decomposition of P 2 τ , which will be useful for the proof of the main result. Proposition 4.

Let P τ = 1 s-αe -sτ ∈ H 2 . Then P 2 τ (s) = ∞ k=-∞ ψ k 1 (s -λ k ) 2 + ρ k 1 s -λ k (9)
where

ψ k = 1 (1 + τ λ k ) 2 and ρ k = 2τ 2 λ k (1 + τ λ k ) 3 .
Proof A similar procedure is followed here such as in Proposition 3. First, notice that all the poles of P 2 τ have multiplicity two. That is why we need the square term as well. To obtain the coefficients one should use the residues formula taking into account that all the poles have multiplicity two. Thus :

ψ k = lim s→λ k P 2 τ (s)(s -λ k ) 2 = 1 (s-αe -sτ ) | s=λ k 2 = 1 (1 + τ λ k ) 2 ρ k = lim s→λ k d ds P 2 τ (s)(s -λ k ) 2 ) = 2τ 2 λ k (1 + τ λ k ) 3 2.3 H 2 -inner product computation
The following proposition allows to compute the H 2 -inner product using the spectral decomposition of Ĥd . Proposition 5. Spectral H 2 -inner product : Let F ∈ H 2 and P τ = 1 s-αe -sτ . Then :

P τ , F H2 = ∞ k=-∞ φ k F(-λ k ), ( 10
)
where φ k = 1 1+τ λ k . Proof One can straightforward writes :

P τ , F H2 = φ k 1 s-λ k , F H2 = φ k 1 s-λ k , F H2 = φ k F(-λ k )
where the last step we have applied item (1) from Proposition 2. By noticing that λ k is also pole of P τ whose residue is φ k , one can reorder the serie and the result follows.

In addition, we obtain a similar formula of the H 2 -inner product computation using the partial fraction decomposition of P 2 τ (s). This point is the result presented in Proposition 6. Proposition 6. Spectral H 2 -inner product 2 : Let F ∈ H 2 and P τ = 1 s-αe -sτ . Then

P 2 τ , F H2 = ∞ k=-∞ ρ k F(-λ k ) -ψ k F (-λ k ) (11)
where

ψ k = 1 (1+τ λ k ) 2 and ρ k = 2τ 2 λ k (1+τ λ k ) 3 . Proof Similar to Proposition 5. Thus P 2 τ , F H2 = ρ k 1 s-λ k , F H2 + ψ k 1 (s-λ k ) 2 , F H2 = ρ k 1 s-λ k , F H2 + ψ k 1 (s-λ k ) 2
, F H2 and now one should apply the inner product properties (1) and (3) from Proposition 2. Then, by noticing that λ k is also pole of P 2 τ , one obtains Equation (11).

Other formulas

The following result will be useful to demonstrate the main theorem in the Section 3. Proposition 7.

Let P τ = 1 s-αe -sτ ∈ H 2 . Then :    P τ (s) = -1-τ αe -sτ (s-αe -sτ ) 2 ∂P τ ∂ α (s) = e -sτ (s-αe -sτ ) 2 .
which, by association, leads to :

∂P τ ∂ α (s) = -1 ατ P τ (s) + P τ 2 (s) . ( 12
)
We are now ready to state the main result of this paper, namely the H 2 optimality conditions for single reduced time-delay models.

MAIN RESULT: H 2 -OPTIMALITY CONDITIONS

In this section, we state and prove an extension of Proposition 1 in the case the reduced order model is a single time-delay model of dimension one, i.e., Ĥd (s) = φ s-αe -sτ . Firstly, let us write the H 2 -mismatch error E between the full model G and the reduced model Ĥd as follows :

E( φ, α) = G -Ĥd 2 H2 = G -Ĥd , G -Ĥd H2
Following the same reasoning developed in [START_REF] Meier | Approximation of linear constant systems[END_REF], let Θ = { φ, α} be a variable parameter defining Ĥd . Let us take the derivative of E with respect to Θ. Since only Ĥd depends on Θ, the derivative of the H 2 -mismatch error with respect to Θ is given by :

∂E ∂Θ = -2 G -Ĥd , ∂ Ĥd ∂Θ H2 . ( 13
)
Notice that in order to obtain formally Equation ( 13), one needs to justify that the inner-product commute with the partial derivative. This is possible using the Lebesgue Dominated Convergence Theorem. Hence, by using the propositions from Section 2, the following results can be stated.

Proposition 8. The partial derivative of the H 2 error E with respect to the parameters are given analytically by :

       ∂E ∂ φ = -2 G -Ĥd , P τ H2 ∂E ∂ α = 2 φ ατ G -Ĥd , P τ + P τ 2 H2
Proof One has to apply the formula (13) for each parameter and use ∂ Ĥd ∂ φ = P τ and the formula (12). For the second equation, we use the fact that ∂ ∂ φ commutes with the H 2 inner-product.

Finally, by setting those partial derivatives to zero, one obtains the H 2 -optimality conditions for the Problem 1. Moreover, by applying the inner product computation result (10), one has the generalization of the interpolation conditions from Proposition 1.

Theorem 1. Let Ĥd = φ s-αe -sτ ∈ H 2 and G ∈ H 2 . Let us suppose also that G ∈ H 2 . If Ĥd is the best H 2 approximation of G, then : ∞ k=-∞ G(-λ k )φ k = ∞ k=-∞ Ĥd (-λ k )φ k , (14)
∞ k=-∞ G (-λ k )(φ k -ψ k ) + ∞ k=-∞ G(-λ k )ρ k = ∞ k=-∞ Ĥ d (-λ k )(φ k -ψ k ) + ∞ k=-∞ Ĥd (-λ k )ρ k (15)
where λ k , for k ∈ Z, are the poles of

H d , φ k = 1 1+τ λ k , ψ k = 1 (1+τ λ k ) 2 and ρ k = 2τ 2 λ k (1+τ λ k ) 3 .
Proof Equation ( 14) is obtained by setting ∂E ∂ φ = 0 and using the H 2 -inner product computation formula (10). Equation ( 15) is obtained by setting ∂E ∂ α = 0 which means G, P τ + P τ 2 H2 = Ĥd , P τ + P τ 2 H2 . Hence, using the Hermitian property from the H 2 -inner product, G, P τ H2 = G , P τ H2 and the result is obtained using the H 2 -inner product computation formula ( 10) and ( 11). Indeed, Theorem 1 generalizes Proposition 1. Due to the infinite dimensional nature of time-delay systems, the H 2optimality conditions here are no longer interpolation conditions and become interpolation of series depending on both G and Ĥd and the spectral decomposition of Ĥd . If we choose τ = 0, i.e., Ĥd (s) = 1 s-α , we get back the result from Proposition 1, because the sum are over the poles and in this case Ĥd has only one pole. The reader should remark that the conditions presented in Theorem 1 are necessary optimality conditions.

APPLICATION

In this section we find one local optimum to Problem 1 when G is a very simple model. Then, we verify numerically that it satisfies the conditions ( 14) and (15).

Let us consider Problem 1 applied to the following very simple model :

G(s) = 10 s 2 + 11s + 10
.

G and G are clearly elements of H 2 . Let us fix τ = 1. Then, Problem 1 consists in finding φ ∈ R and α ∈ (-π/2, 0) which minimizes :

E( φ, α) = G -H d 2 H2 = E( φ, α) 2

H2

where H d (s) = φ s -αe -s . To find a local minimum we have used the MATLAB function fminunc. The criterion was computed solving delay Lyapunov equations (see [START_REF] Jarlebring | Characterizing and computing the H 2 norm of timedelay systems by solving the delay lyapunov equation[END_REF]). The delay state space realization of E( φ, α) used here was Now, let us verify that G and Ĥd satisfy the conditions stated in Theorem 1. Since this result involves infinite sums, we then rely on a truncation scheme to evaluate them. Let us use the set :

E( φ, α) := ẋ(t) = Ax(t) + A τ x(t -τ ) + Bu(t) y(t) = Cx(t)
D N = {first N dominant poles of P τ (s)} = {λ k = W k (-α), k = -N, -N + 1, . . . , N -2, N -1}
to compute an approximation of the infinite sum. Notice we have chosen the poles λ k to go from -N to N -1 so that D N is closed under complex conjugation, i.e., if λ ∈ D N , λ ∈ D N . In this way, the model constructed by modal truncation is real. Then one should have :

S 1,G,N = N -1 k=-N G(-λ k )φ k ≈ N -1 k=-N Ĥd (-λ k )φ k = S 1, Ĥd ,N and S 2,G,N = N -1 k=-N G (-λ k )(φ k -ψ k ) + N -1 k=-N G(-λ k )ρ k ≈ S 2, Ĥd ,N = N -1 k=-N Ĥ d (-λ k )(φ k -ψ k ) + N -1 k=-N Ĥd (-λ k )ρ k .
The following table shows the truncation results for different number of poles : This approximation shows that the truncation conditions are close to the optimality conditions from Theorem 1.

N S 1,G,N S 1, Ĥd ,N S 2,G,N S 2, Ĥd ,N 2

CONCLUSION

In this paper, the H 2 -optimality conditions for single reduced time-delay models of dimension one were found as an extension of the interpolation results from the delayfree case (see Proposition 1). In order to prove the main theorem, some results about the spectral decomposition of H d and the H 2 -inner product computation where exposed. In addition, an academic example were presented in order to illustrate these conditions. This results have a great potential to be extended to more complex structured reduced models and an algorithm needs to be developed in order to find reduced order models satisfying these new optimality conditions.

  1. (SISO H 2 -optimality conditions). Let Ĥ = be a reduced model having only simple poles. If Ĥ is the best rth order H 2 approximation of G(s), then, for k = 1, 2, . . . , r, G(-λk ) = Ĥ(-λk ) and G (-λk ) = Ĥ (-λk ), (3) where G (s) denotes the derivative of G(s) with respect to s.

Fig. 1 .

 1 Fig. 1. Error H 2 as function of φ and α

Proof

  Appendix A. ., . H2 AND ∂ ∂ α COMMUTATION Proposition 9. Let Ĥd = φ s-αe -sτ , where τ ∈ R , α ∈ (-π 2τ , 0) and φ ∈ R. If G ∈ H 2 , then ∂ ∂ α G -Ĥd , G -Ĥd H2 = 2 G -Proposition 3 asserts that Ĥd will be stable for all α ∈ (-π 2τ , 0). Define Hd (s) = φ s -α e -τ s . For any α, α ∈ (-π 2τ , 0), Ĥd , Hd ∈ H 2 andthere is an open neighborhood of α, B α ⊂ (-π 2τ , 0) and a finite M α > 0 such that for all α ∈ B α, | Hd (ıω)| < M α uniformly with respect to α for all ω ∈ R.Now for any fixed α ∈ (e -ıωτ(ıω -α e -ıωτ )(ıω -α e -ıωτ ) = -2 φ e -ıωτ (ıω -α e -ıωτ ) 2 = ∂ ∂ α Ĥd (ıω) for any ω ∈ R. Evidently, ∂ Ĥd ∂α ∈ H 2 so long as α ∈ (-π 2τ , 0). Furthermore, for all α ∈ B α, Ĥd (ıω) -Hd (ıω) the result.


Gary Ford

Chris Mcmahon

Chris Rowley

Information Resources for the Identification of Complex Asset Condition: A Naval Engineering Case Study

Keywords: Lifecycle, Maintenance, Naval, Data

des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

There is extensive interest today in how we may use information technologies to improve our capability to judge the condition of complex engineered assets such as buildings, energy, transportation and infrastructure systems [START_REF] Costello | Underground asset location and condition assessment technologies[END_REF][START_REF] Ollier | Intelligent Infrastructure The Business Challenge[END_REF]. In particular there is interest in exploiting the information collected during the design, manufacture, maintenance and operation of such systems. This paper is concerned with an example of such a complex engineered asset -naval ships -and with exploiting the information collected during their operation and maintenance for identification of their state.

Royal Navy (RN) surface ships and submarines are a compilation of complex systems, i.e. "integrated set of elements, subsystems, or assemblies that accomplish a defined objective" [3]. A warship / submarine will contain in excess of 100 integrated "hard" systems which are linked structurally, mechanically, electrically, hydraulically, pneumatically and electronically [START_REF] Collins Class | [END_REF]. Warfare demands a constant change in offensive and defensive capability, and, in addition to its offensive and defensive capability a warship must also be capable of providing, "humanitarian assistance and disaster relief operations to relieve human suffering" [START_REF]Joint Doctrine Publication 0-10 British Maritime Doctrine[END_REF] -e.g. the assistance of HMS Daring and HMS Illustrious in the Philippines following Typhoon Haiyan [START_REF]Britain will deploy a Royal Navy warship and RAF military transport aircraft to help people devastated by Typhoon Haiyan[END_REF][START_REF]HMS Illustrious picks up stores for Philippines aid[END_REF].

The United Kingdom's Ministry of Defence (MoD) utilise a systems lifecycle model known as CADMID. The 6 CADMID stages are Concept, Assessment, Demonstration, Manufacture, In-Service and Disposal [START_REF] The | [END_REF]. A high degree of commonality exists between the stages specified in ISO 15288 (Systems and Software Engineering -System Life Cycle Processes) and CADMID (table 1).) During its life a vessel should experience a linear progression through each stage of the lifecycle. In 2009 a Surface Ship Support Alliance (SSSA) was formed between the MoD, Babcock and BAE Systems, the intention being to "to reduce costs and increase availability" for surface ships. The SSSA introduced a "risk and reward" incentive, linking expenditure and availability, savings to be shared between all members of the alliance. The MoD remains the platform duty holder, with responsibility for the vessel. The formation of a Class Output Management (COM) team as part of the SSSA is intended to provide an industry, rather than a MoD led organisation with respect to planning and execution of maintenance.

Within the CADMID In-Service stage, a naval vessel will cycle through 3 discrete phases (Figure 1), i.e. Tasking, Upkeep and Regeneration.

Request technical support

In addition to the information available to ascertain the material state of a system varying with the cyclical phase, stakeholder and objective, the validity and life of information will also fluctuate, e.g.

 Engineering logs ~ primarily generated and exploited during Tasking and Regeneration phase  Pre-Upkeep Maintenance Assessment (PUMA) reports ~ generated during Tasking phase but exploited for Upkeep  Unit Maintenance Management System (UMMS) ~ generated and exploited throughout all phases. This paper details an investigation into the key data sources that may be used to determine the material state during each operational phase. The data sources were identified from a series of recorded semi-structured interviews conducted at the interviewees' offices. All interviewees (In-Service stakeholders) were highly experienced MoD, RN, Babcock and system supplier personnel, divided in the key phases as follows:

 Tasking: Fleet Operations Maintenance Officer (FOMO), Ship staff  Upkeep: COM team, Babcock Project Managers  Regeneration: Force Generating Authority, Flag Officer Sea Training, Maritime Capability Trials and Assessment  Support: Defence Equipment and Support (DE&S) Spares, Finance, Chilled

Water System Supplier The "Support" organisations are a component of "In-Service" lifecycle, consequently they were interviewed to assess their "enabling" and "control" influence during the cyclical phase of an RN vessel.

The objective of the interviews was to ascertain the Inputs, Controls, Mechanisms and Outputs within each functional cyclical phase (process), with a view to then exploring (in later research) how engineering experts make a judgement about asset state based on the information sources. In the remaining sections of this paper the key data sources generated at each phase will be explored and then a brief evaluation of their characteristics and their potential as a source of asset condition will be presented.

Key Data Within Each Cyclical Phase

This section provides an overview of the processes and key data in each cyclical phase.

Tasking: Initiation of the Tasking phase and hence completion of any previous Regeneration phase is receipt of the "Ready for Ops" signal (see below). An operational vessel, although under the command of Commander Maritime Operations (COMOPS) must also operate as an autonomous safe seaworthy vessel under the direction of the captain. The Marine Engineering Officer (MEO) as department head is accountable for, "the good material order and maximum availability of all equipment and systems within its responsibility, in order to maintain the seagoing and fighting capability of the ship" [10].

Within the Tasking phase, two distinct information pathways detailing and assessing the material state may be seen to exist, i.e.

Internal data that is generated and utilised solely within the vessel. The internal reporting and assessment of the material state will typically comprise multiple "stove pipe" sources, e.g. hand written engineering logs, vibration records, oil sampling, UMMS. The information will be used by the MEO to facilitate the "maximum availability of all equipment and systems", as well as enabling the vessel fight the internal battle, i.e. the preparation, training, management and rectification of action damage and systems failure, in effect enabling the vessel to continue to execute the external battle, e.g. engage air / surface / sub-surface combatants.

The internal information sources will typically be objective, e.g. temperature, pressure, vibration, failure, etc. trend analysis being limited to the vessel. Data is invariably current, given the source is contained within the vessel, however, the urgency of assessing the data / information or subsequent action will be dependent upon the "command aim", i.e. the mission objective. Consequently there may be a concentration of focus upon a singular system at the expense of more general analysis or maintenance. System failures that degrade the operational capability of a vessel are reported to naval command as Operational Defects (OpDef's). However, operational constraints may prohibit the vessel from seeking technical support or guidance from FOMO, e.g. submarines on submerged patrol, consequently the vessel is highly dependant upon the accuracy and currency of onboard documentation, configuration management and the knowledge / experience / training of maintainers. Furthermore, a solitary vessel may be unaware of deficiencies / performance issues affecting a system common to a class. Figure 2 illustrates the commonality of maritime systems in RN vessels Figure 2: RN Common Maritime Systems [START_REF] Hyde | Systems Engineering in Defence Procurement: A SEIG & Maritime Combat Systems Perspective[END_REF] External data generated, analysed and (potentially) aggregated within the vessel before transmission to FOMO for interpretation, execution and provision of assistance. Typically, FOMO will assess OpDef signals and capability reports received from the vessel to assess the material state and subsequent impact upon capability / availability. The data available to FOMO is primarily a latent abstraction of the primary data source potentially containing a mix of objective and subjective data. The FOMO organisation will apply their extensive tacit knowledge to formulate a predominantly subjective assessment of the data and will advise command regarding the material state of vessel and any potential risk to capability in the context of the command aim.

In addition to advising command, a key function of FOMO is to liaise with DE&S "desk officers" for the provision of support and stores. Where stores / equipment are not available from store, FOMO may initiate a 'stores robbery', i.e. the removal of items from other vessels, initially from those within DE&S control, e.g. HMS Duncan -"Early in build, one of our gas turbines was removed for [HMS] Daring after hers was damaged" [START_REF] Henderson | Beating Last Ship Syndrome Delivering HMS Duncan. A Ship's Staff Perspective[END_REF]. If equipment / systems are not available from non-operational vessels, equipment will be taken from operational vessels. The potential impact upon condition assessment is that "new" equipment may have actually encountered considerable usage / load / shock / vibration and a maintenance regime that is possibly unknown to the final user.

Upkeep: The planning and preparation for the Upkeep of a naval vessel starts during the Tasking phase. Initial milestones / stages associated with the instigation and formulation of the work package are detailed in BR8593 [13].

The work package is a composite of numerous maintenance activities contained within UMMS, survey reports including statutory inspections "Lloyds Register class inspections", Work Requisition Forms, OpDefs, etc. The work package will often reflect the impact of operating the vessel in an environment at the limit of its design specification, e.g. high ambient temperatures as experienced in tropical regions. In addition to maintenance activities the work package will include Alterations & Additions, i.e. enhancements to a vessel's capability, life extensions, statutory modifications.

Pre-Upkeep surveys are often undertaken by the maintenance contractor, e.g. Babcock, supported by the Original Equipment Manufacturer (OEM), to provide a detailed material assessment of systems and equipment. The surveys are perceived as a datum with respect to defining the scope of the work package and potential variations. In addition to surveys conducted by the maintenance contractor BR1313 [START_REF]BR 1313 -Maintenance Management In Surface Ships[END_REF] specifies a requirement to undertake various pre-Upkeep inspections, e.g. resulting in PUMA reports.

A considerable number of surveys (structural and system) are undertaken early in the Upkeep phase, these are reviewed in detail at a Hull & Structural Assessment meeting where the initial work package is reviewed and potentially enhanced by means of Variation Orders.

The Upkeep phase will generate a considerable volume of documents including test specifications, Lloyds surveys, etc. however, the Material State Portfolio (MSP) created by the COM is an objective assessment of the vessel's state upon completion.

The document details the work undertaken and the condition of the vessel and is a key data source.

Regeneration: The initiation of the Regeneration process is the receipt of a Force Generation Order (FGO) by the Force Generation Authority (FGA), specifying the required capability of the vessel. The FGO may be perceived as a "User Requirement" with respect to a vessels operational capability. Upon receipt of the FGO a meeting is held with ship staff and the FGA, whereupon deficiencies and areas of concern are identified given the planned objective and the potential impact upon hard and soft systems. Typically the ship will utilise the Manpower, Equipment, Training and Sustainability (METS) construct for reporting

The FGA will formulate the specific regeneration requirements of a vessel including any specialist Military Task Equipment (MTE). MTE, are equipments required for directed military tasks but which do not exist in sufficient numbers to fit to all platforms at all times, consequently, potentially resulting in a lack of familiarity regarding maintenance.

The FGA will subsequently liaise with Flag Officer Sea Training (FOST) to formulate the specific program of regeneration and systems necessitating particular assessment. It is the responsibility of FOST to generate the vessel to the capability specified by the FGA who, "own the regeneration process". The testing and validation of systems will reflect the planned deployment, including physical environment and potential threats, e.g. deployment East of Suez: prioritisation of chilled water cooling systems, davits for boarding.

It should be noted, a vessel may be generated with a specific capability but may subsequently be re-tasked potentially without the requisite capability: Naval Command will subsequently "manage" the associated risk.

In addition to the operational assessment the RN Maritime Capability Trials and Assessment (MCTA) organisation assess mechanical and weapons systems by means of Harbour Acceptance Trials, Sea Acceptance Trials, Ship Performance Assessment's (SPA) and Operational Capability Confidence Check's (OCCC). Detailed objective reports are provided by MCTA to the vessel detailing where standards have been achieved, partially achieved or not achieved.

Completion of Regeneration is marked by a "Final Signal" and a "Ready for Ops" signal that will detail within the METS pillars what is outstanding to generate as specified in the FGO and any associated risks to operational capability when in theatre, e.g. chilled water system. This will raise awareness within FOMO such that any subsequent OpDefs pertaining to highlighted equipment / systems may impact capability.

Review

Information: The information sources are diverse, ranging from very detailed objective records of temperature and pressure etc. to latent subjective assessments derived from numerous sources. Stakeholders will attribute characteristics / properties both to their own requirements and the individual data sources. Information characteristics may include:  Accessibility -location, security, ownership, cost, media  Process and uncertainty characteristics -fuzziness, randomness, incompleteness [15]  Granularity -abstraction, aggregation  Media -paper, digital, standard, propriety  Validity -range, precision, accuracy  Volume -growth rate, initial A review of the information sources identifies a number of key sources that are exploited to ascertain the material state in all phases, i.e.  OpDef's -defects that impact / reduce the operational capability, updated and interrogated constantly, i.e. identify maintenance / upgrades, performance, operational constraints  UMMS -the system not only schedules preventive maintenance and will identify outstanding maintenance but is also a repository of persistent defects  Stores -analysis of material usage provides information regarding persistent defects, i.e. Comprehensive Royal Naval Inventory Systems Project The information sources identified as key during Tasking are the engineering and condition based maintenance logs. The sources are generated and analysed locally (onboard) and offer a high level of data granularity but provide poor accessibility due to the format, i.e. paper based. The Fuel and Lubrication Consumption (FLUBCON) report provides a record of engine and lubrication usage, analysis will indicate increased usage which may be indicative of increased wear.

During Upkeep the information is primarily objective and detailed, the numerous system and structure survey reports provide considerable detail when aggregated, however, this requires manual processing. Similarly the MSP is a reliable document, however, its creation is a manual process drawing together numerous digital and nondigital data sources, furthermore, it only provides a perspective for a given point in time.

The assessments undertaken by MCTA during Regeneration, i.e. SPA and OCCC are detailed assessments of the material state, which combined with the "Ready for Ops" signal provides a reflective assessment of issues.

Each information source will provide a perspective of the material state to each of the stakeholders, e.g. UMMS provide ship staff information regarding scheduled maintenance as well as a repository for defects. The MEO will be particularly interested in maintenance that is outstanding. The COM may interrogate UMMS to review persistent defects and potential assistance from the OEM. Artefact Information: The distinctive "concept of operations" and design of naval vessels necessitates and creates a range of data that is not comparable with similar size commercial vessels. Although a number of systems may be similar to commercial vessels, the manner of operation within a naval vessel is not, e.g. "crash stop" a chilled water system to simulate action damage. A number of systems are unique thus minimising the opportunity for comparison. Comparing RN vessels with other naval forces highlights a high degree of similarity with respect to policies, procedures and data collected, e.g. engineering logs, vibration monitoring. The variation being the terminology, e.g. the US Navy refer to an operational defect (OpDef) as a CASREP -Casualty Report.

4 A Proposed Use Of Maintenance Data -"The main thing is, we need to deliver capability" [16] During Upkeep, substantial preventive and corrective maintenance is undertaken in addition to enhancing a vessels capability, e.g. HMS Ocean's Upkeep (2012-2014) ~ £65 million, 15 months planned duration that will including over 60 upgrades [17,[START_REF]Key milestone in major upkeep programme, as HMS Ocean undocks[END_REF].

The Upkeep work package will encompass numerous sources; however, key to developing the work package is an assessment of the material state prior to "Upkeep", i.e. Tasking. Information sources containing data indicative of the material state during Tasking are,  OpDef's: Contains defects that degrade the operational capability of the vessel, the data is transmitted to a central repository  SPA: Undertaken by an external authority during Tasking, identifying where standards have not been achieved  UMMS: Contains details of preventive and corrective maintenance, however, the utilisation of the system is not consistent, furthermore, data is recorded onboard with periodic uploads to a central repository RN vessels support UK maritime doctrine, i.e. the "ability to project power at sea and from the sea to influence the behaviour of people or the course of events" [START_REF]Joint Doctrine Publication 0-10 British Maritime Doctrine[END_REF]. Consequently, a defect that degrades "capability" may potentially endanger and negate the raison d'etre of the vessel. The OpDef system records all defects that degrade capability and therefore must be perceived as a key information source and indicator of a vessels "capability" material state. The value of the SPA is the assessment is undertaken by an external authority and will identify ME and WE deficiencies necessitating rectification. In this instance UMMS is discounted as a consequence of the latency of the data and the variations in usage and management.

The OpDef system contains structured objective and subjective data which includes information detailing the "loss of operational capability", associated defect(s), the Effect category and associated Repair Indicator, the Operational Repair Plan and the rationale that prevented the defect being cleared [START_REF] Br ████ | OpDef Signals -Detailed Instructions[END_REF].

Analysis of operational defects and SPA's across multiple platforms by Upkeep planners will not only reflect the value perceived by FOMO & DE&S but also provide a real time indication of single and re-occurring system defects / deficiencies and their resolution (Figure 3). The information will not only highlight systems of concern and hence the risk of future failure, forewarn of potential future maintenance activities but also identify systems necessitating detailed pre-Upkeep survey. Further analysis of OpDef's, SPA's and Hull & System surveys may highlight deficiencies in the provision of onboard spares and maintenance, thus providing a feedback loop with respect to through-life maintenance.

Conclusion

A range of issues have been identified as a consequence of this research, i.e.

 The lack of integration of the multifarious data sources is the initial conclusion; however, this reflects the development of dicrete functionality, e.g. UMMS, SPA, OpDefs  The usage and interpretation of information for purposes it was not intended, e.g. FLUBCON records hours run and lubrication usage, the extrapolation of usage, wear and maintenance was potentially not considered as the report does not record environmental issues that may influence any conclusions.  The remote operation and potential isolation of RN vessels is an issue not normally encountered in civilian / commercial industry. A Trident submarine with a complement of 135 will undertake a 3 month patrol without contact or re-supply whereas the International Space Station is in constant contact and receives supplies typically each month [START_REF]International Space Station. Vehicle Arrivals and Departures[END_REF]. The proposed use of maintenance data detailed above is an initial step in improving vessel capability and reducing Upkeep costs by the early assessment of material state.

Further consideration with respect to the development of a "black box" capable of logging and retaining condition data will provide the potential for system prognostics.

Acknowledgments. The

Figure 1 :

 1 Figure 1: Cyclical phase of naval vesselsTasking is the phase during which a vessel is under Navy Command Authority and thus available for or undertaking operational tasks. The upkeep phase is when a vessel is subject to major maintenance work, typically including docking periods, Regeneration involves the timely activation, in full or in part, of existing force structures and infrastructure, including the restoration of manning, equipment and

Figure 3 :

 3 Figure 3: Proposed Use of Maintenance Data Currently SPA's and OpDef's are analysed in isolation by RN and DE&S staff but not systematically by Upkeep planners, the proposed change would utilise and combine existing data in a manner not currently undertaken. Furthermore, a risk model of potential defects would enable Upkeep planners to plan the availability of resources and purchase spares.

Table 1 :

 1 ISO 15288 / MoD CADMID Lifecycle

	ISO-15288
	Concept		Development	Production	Utilisation	Support	Retirement
	C		D	P	U	S	R
	C	A	D	M	I		D
	Concept Assessment	Demonstration	Manufacture	In-Service	Disposal
	MoD -CADMID

Table 2

 2

	illustrate. A naval vessel

Table 2 :

 2 Stakeholder and objective as a consequence of cyclical phase

	Phase	Stakeholder	Objective		Information Interaction
	Upkeep	Maintenance	Filter hydraulic system to	Provide test results
		organisation	remove particulates
		Ship staff	Observe filtration process	Validate results
	Tasking	Maintenance	Liaise with OEM as technical	Provide technical advice as
		organisation	authority		requested
		Ship staff	Ensure	availability	of
			hydraulic system

  work reported was supported by the Bristol/Bath Industrial Doctorate Centre in Systems, funded by EPSRC grant EP/G037353/1.

	Operational	Analysis & risk	Review
	Defects + SPA's	model	Maintenance + Spares
	Hull and System	Upkeep Work
	Surveys	Package