Knowledge Management: An Engineering Perspective

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Knowledge Management An Engineering Perspective

• Dr. Christian Hicks
• Professor Paul Braiden
• University of Newcastle upon Tyne

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Capital Goods Companies

• Products and processes usually complex
• Customised to meet individual customer
  requirements
• Engineered-to-order
• Low volume, lumpy, erratic demand

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Classification of ETO Companies

• Product / project focus
• Normal / Radical design
• Established / ad-hoc business processes

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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.

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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.

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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.

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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.

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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.

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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

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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.

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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

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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)

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Routines

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

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Knowledge Classification

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

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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 KMAs.
• The performance of the associated business
  processes will be compared.
• Research methodology proposed