You are presented with multiple paper abstracts, alongside the associated literature review and chapter titles. Given the provided information, you are going to do a literature review. Please generate a coherent literature review that synthesizes the content, draws connections between different works, highlights major findings, and identifies any gaps in the existing research.

Literature Review Title: Managing knowledge within the manufacturing enterprise: an overview 
Chapter Title:  Design analysis and support systems 
1. Abstract of Cited Paper (BIB001):  Information with imprecision and uncertainty is inherently presented in engineering design and manufacturing. The nature of imprecision and uncertainty is incompleteness. Product data model, being a core of intelligent manufacturing system, consists of all concerned data in the product life cycle. It is possible that crisp data as well as incomplete data are involved in product data model. So EXPRESS, being a powerful tool to develop a product data model, should be extended for this purpose. Using fuzzy sets and possibility distributions, this paper extends the EXPRESS to make it possible to model fuzzy engineering information

Literature Review:
Aziz and Shappasis develop an intelligent system to support gear design. Knowledge bases are used for concept design, detail design, manufacturability evaluation, and manufacturing process design (Aziz & Chassapis 2005) . Harding et al. develop a fuzzy expert system that applies Quality Function Deployment (QFD) type principles to relate customer requirements to product parameters ). Howard and Lewis developed an expert system linked to AutoCAD to provide comparison data on material and process combinations. A material and manufacturing database was incorporated into the system. Process specific rules require analysis of the 3D model to judge suitability of the method. Material properties include mechanical, thermal, electrical and environmental BIB001 . Kumara et al. developed an expert system combining AutoCAD and AutoLISP to assess manufacturability of sheet metal parts. Production rules are loaded into AutoCAD, which checks design features against ease of manufacture . Shehab and Abdalla developed a knowledge-based system (KBS) to support process cost modelling and design for automation. The system supports the selection of assembly technique, estimates assembly time and cost, and performs analysis of design for automation ). Valentincic and Brissaud developed a manufacturing expert system to support design. The system selects an appropriate process for a given product feature. The system also highlights features that are weak from the manufacturing perspective . Ma applies fuzzy sets and possibility distributions and extends EXPRESS to make it possible to model fuzzy engineering information BIB002 ). Mok and Wong develop a design evaluation system. They suggest that Feature recognition is "the first prominent stage for any automatic design evaluation system". Their methodology can recognise features of injection moulded parts using a hybrid approach: graph theoretic and logic. Features are classified as: primitive, complex and high level complex . Swift et al. suggest that probabilistic design should be more widely adopted, since deterministic design fails to provide an understanding of the variable nature of manufacture, materials properties and product use (Swift et al., 2001 ).