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Long Term Knowledge Retention Atlantic Meeting

Long Term Knowledge Retention Atlantic Meeting. Chris McMahon University of Bath, 12 February 2007. The Bath Plug. Innovative design and Manufacturing Research Centre. IMPROVING THE DESIGN OF MACHINES, SYSTEMS AND PROCESSES. WHOLE LIFE DESIGN INFORMATION AND KNOWLEDGE MANAGEMENT.

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Long Term Knowledge Retention Atlantic Meeting

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  1. Long Term Knowledge RetentionAtlantic Meeting Chris McMahon University of Bath, 12 February 2007

  2. The Bath Plug Innovative design andManufacturing Research Centre IMPROVING THE DESIGN OF MACHINES, SYSTEMS AND PROCESSES WHOLE LIFE DESIGN INFORMATION AND KNOWLEDGE MANAGEMENT REVERSE ENGINEERING & METROLOGY MACHINE MODELLING & OPTIMISATION RESPONSIVE MANUFACTURING PROCESSES & SYSTEMS DESIGN FOR X CHANGEOVER & SUSTAINABLE MANUFACTURE Id MRC USING DESIGN INFORMATION REPRESENTING DESIGN INFORMATION ORGANISING DESIGN INFORMATION

  3. The Importance of Information • “'Knowledge management' is an umbrella term for a variety of organizational activities, none of which are concerned with the management of knowledge. Those activities that are not concerned with the management of information are concerned with the management of work practices, in the expectation that changes in such areas as communication practice will enable information sharing.” • T.D. Wilson, “The nonsense of ‘knowledge management’”, Information Research, Vol. 8 No. 1, October 2002

  4. The Need for Evidence • “Most clinical practice is based on limited evidence, mostly in the form of textbook information, obsolete premises, untrustworthy research or case studies, partial or unendorsed reviews, and anecdotal or personal clinical experience. Proven therapies backed by ample evidence are underutilized for lack of knowledge or grasp of available evidence and, often, clinicians do not believe that results observed in clinical trials can be directly translated into clinical practice” • Rodrigues, R.J., Information systems: the key to evidence-based health practice, Bull World Health Organ vol.78 no.11 Genebra Nov. 2000

  5. The Need for Evidence • “Most clinical practice is based on limited evidence, mostly in the form of textbook information, obsolete premises, untrustworthy research or case studies, partial or unendorsed reviews, and anecdotal or personal clinical experience. Proven therapies backed by ample evidence are underutilized for lack of knowledge or grasp of available evidence and, often, clinicians do not believe that results observed in clinical trials can be directly translated into clinical practice” • Rodrigues, R.J., Information systems: the key to evidence-based health practice, Bull World Health Organ vol.78 no.11 Genebra Nov. 2000

  6. Context - Product-Service Systems

  7. Distributed Business Courtesy Ludo Van Vooren, Exostar

  8. Diverse Representations

  9. Proprietary Software Engineering is dominated by proprietary interests in software and in data and information

  10. So How Are We Doing? We need to be able to • Record/represent our work and its outcomes – “engineering stuff” • Read/interpret different representations of stuff • Do (2) reliably into the future • Organise and find stuff • Maintain, correct, aggregate and discover stuff

  11. Representing engineering stuff • Mature (but incomplete and imperfect) representation of product – CAD models; BoM, developed incrementally over 40+ years • Various representations of process, organisation, rationale, intent etc. – but not agreed or widely applied • Mostly descriptions are in practice embedded in text documents – reports, minutes, emails . .

  12. Read/interpret representations • Multiple proprietary formats for product representations - but reducing number • Standards in place or under development for most aspects of product modelling: • STEP, PLCS . . . • Lightweight representations 3D-XML, PLM-XML, JT, X3D • But some bits work better than others, and adoption is limited • De facto standards for documents, emerging interest in XML-based approaches.

  13. Rapid Turnover of Computer Systems

  14. Read reliably into future • Much of what has been done with computers is “lost” • Curation strategies include refreshing, preservation, transfer, emulation, migration, encapsulation – no single approach is the answer • Practice mainly based on time consuming transfer to new media/new versions of software • Future through OAIS, but will be very challenging in engineering

  15. Organise and find stuff • Mainly based on enumerative classifications/ directory structures/metadata in databases/free text search • “I can never find anything” • Affordances of traditional paper-based approaches lost • Emails often very uncontrolled: • need to treat as records and integrate with processes • Future: • Need equivalent to PageRank for organisational information • New approaches needed – ontology-driven? faceted classification? Topic Maps?

  16. Maintain, update, aggregate, discover • “The only people who can find information are those that put it there” • “The only people who can use information are those that have read it” • Double loop learning is very difficult. • Aggregation is very time consuming • Discovery is impossible

  17. Murray-Rust “Datuments” This is not computer interpretable This data is not accessible computationally

  18. KIM Grand Challenge Project • Centred on the EPSRC Innovative Manufacturing programme and Innovative Manufacturing Research Centres (IMRCs) • Project on knowledge and information management through life is one of four funded from October 2005 • £5.5 million (c$10 million) over 3.5 years, 11 University partners, >25 industrial partners.

  19. Work Packages Work Package 1 Advanced Product Information Representation & Management Bath EngineeringCambridgeHeriot-WattImperialLeedsLoughboroughStrathclydeUKOLN Work Package 2 Learning Throughout the Product-Service CycleBath EngineeringCambridgeLancasterLiverpoolLoughboroughReading Work Package 3 Managing the Knowledge System Life CycleBath ManagementCambridgeImperialLancasterLiverpoolLoughboroughReadingSalford Work Package 4 Integrating Activities All Partners

  20. WP1 Tasks • To develop combined product, process and rationale models that will allow the capture of extended models of product designs (including records of design trade-offs, results of negotiation, evidence of decision making and details of successful and unsuccessful designs) • To develop approaches to design information organisation based on these combined models and on the need to capture feedback from service • To explore automated techniques for the capture of design knowledge to reduce the overhead in building the new models.

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