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Knowledge Management: An Engineering Perspective

Knowledge Management: An Engineering Perspective. Dr. Christian Hicks Professor Paul Braiden University of Newcastle upon Tyne. Capital Goods Companies. Products and processes usually complex Customised to meet individual customer requirements Engineered-to-order

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Knowledge Management: An Engineering Perspective

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  1. Knowledge Management: An Engineering Perspective Dr. Christian Hicks Professor Paul Braiden University of Newcastle upon Tyne

  2. Capital Goods Companies • Products and processes usually complex • Customised to meet individual customer requirements • Engineered-to-order • Low volume, “lumpy”, erratic demand

  3. Classification of ETO Companies • Product / project focus • “Normal” / “Radical” design • Established / ad-hoc business processes

  4. ETO Challenges • Focus on return on capital has led to change in ETO company structures. • ETO companies need to coexist in several alliances / joint ventures simultaneously. • Need to assure the processes by which knowledge is used within the firm and supply chain. • Knowledge needs to be gathered from transitory supply chain relationships • Need to comply with regulatory / de-regularity environments.

  5. ETO Processes • Physical / non-physical. • Multistage - tendering, contract execution, operations, maintenance. • All processes complex, interrelated and knowledge based. • Processes dynamic and often reconfigured. • General shift towards the outsourcing of physical activities.

  6. Product Development Process • 75-80% of cost and delivery commitments result from early stages design decisions • There is high levels of uncertainty and sparse knowledge. • A holistic view of multistage processes is required including design, manufacture, construction, operation and maintenance • Tendering is often subject to severe time pressure and resource constraints.

  7. Product Development Processes • Normal design - product development, modification of existing products • Radical design - creation of new type of product, sparse knowledge base, engineers work from first principles, high levels of experimentation / modelling.

  8. Business Processes • With normal design there is sufficient knowledge to have established business processes • Radical design often requires business processes to be developed on an ad-hoc basis. • ETO companies lie on a continuum between these two extremes.

  9. Product Description • Changes in both form and detail • Starts with high ambiguity, sparse description and high uncertainty • Finishes with full product description and limited uncertainty • Different functions have different views • Functional decomposition • Physical decomposition • Top down vs bottom up • Geometric / materials / properties

  10. Systems Analysis and Modelling Different types of model based upon graphical notations • Functional models - decompose systems using a hierarchical, top-down approach. Helpful for understanding processes and interrelationships. • Information models - “flat structure”define data structures for database systems in terms of entities and relationships. • Dynamic models - describe dynamic characteristics • Other models - decision trees etc.

  11. Modelling Engineering Systems • Quality Function Deployment - mapping customer requirements into engineering characteristics • Precedence relationships between processes and knowledge important • Matrix based approaches - Steward / Epping, identify • Serial processes • Parallel processes • Coupled processes

  12. Research • Objective is to identify new or improved knowledge management activities which will yield benefits. • Some companies have established processes, whereas others develop them as required on a project basis. • Knowledge workers operate within defined business processes and informal routines • Business processes and routines established through observation of processes and routines. • Formal methods used for mapping business processes (SSADM/IDEF)

  13. Routines • Identification of drivers and actors • People / system driven • Identification / dissemination of internal / external knowledge

  14. Knowledge Classification • Knowledge processing - generation, transfer, utilisation, identification, capture / retrieval, format, codification, assurance • Domains - internal/ external, technical area, focus • The part of the organisation’s performance affected by the knowledge management activity • Formality - time and location dependency, MIS

  15. General Conclusions • ETO companies are complex and dynamic organisations • Interactions between processes may be separated by a time lag. • Formal processes modelled. • Current research is focused upon identifying, classifying and documenting processes / routines • Object: to identify / improve KMA’s. • The performance of the associated business processes will be compared. • Research methodology proposed

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