Capturing intelligence as a reusable framework for manufacturing decision processes

M. Marefat, P. Banerjeej, R. L. Kashyap, C. L. Moodie

Research output: Contribution to journalArticlepeer-review

4 Scopus citations


A reusable framework consisting of hierarchical knowledge representation, preliminary design, iterative modification, four information flow and reasoning paths, and solution validation is conceived as a common substrate for addressing multiple components in manufacturing decision processes. The problems are represented in a state-space framework. An investment is made to design a rich representational scheme and to discriminate the promising solution states by utilizing its many implicit constraints in contrast to investing in heuristics operating on a more simplified representation of the problem. Although isolated segments of the described framework (e.g. hierarchical problem solving, abstraction) have been previously mentioned in knowledge-based problem solving, the framework distinguishes itself by exploring the nature of the interaction of these concepts in actually obtaining end results for manufacturing problems. Although hard to quantify, it is stated that the involved ‘intelligence’ from the manufacturing systems integration standpoint is the amount of reusability in the framework for different components of manufacturing decision processes. The reusability of the framework is illustrated by two such components: (i) integration of design and process planning, and (ii) facilities layout.

Original languageEnglish (US)
Pages (from-to)1767-1795
Number of pages29
JournalInternational Journal of Production Research
Issue number8
StatePublished - Aug 1993

ASJC Scopus subject areas

  • Strategy and Management
  • Management Science and Operations Research
  • Industrial and Manufacturing Engineering


Dive into the research topics of 'Capturing intelligence as a reusable framework for manufacturing decision processes'. Together they form a unique fingerprint.

Cite this